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ROAD DEICING SALT IMPACTS ON URBAN WATERQUALITY
A THESIS
SUBMITTED TO THE FACULTY OF THE GRADUATE SCHOOL
OF THE UNIVERSITY OF MINNESOTA
BY
Eric Vladimir Novotny
IN PARTIAL FULFILLMENT OF THE REQUIREMENTS
FOR THE DEGREE OF
Doctor Of Philosophy
September, 2009
c© Eric Vladimir Novotny 2009
ALL RIGHTS RESERVED
Acknowledgements
I would like to acknowledge all of the people who have helped me in the completion of
this thesis. I would first and foremost like to acknowledge my advisor Dr. Heinz G.
Stefan for his guidance throughout my graduate studies. I know that the knowledge
and experience gained under his direction has prepared me well for my future and has
contributed significantly to the researcher and person I have become over the past 5
years.
I would also like to acknowledge the co-PI of my research project, Dr. Omid Mohseni,
and the three members of my PhD committee, Dr. John Gulliver, Dr. Paul Capel and
Dr. Bruce Wilson, for their contributions and suggestion to help improve my thesis.
Many other people have also contributed to my studies. I would like to acknowledge
Chris Ellis and Ben Erickson, of the St. Anthony Falls Laboratory at the University
of Minnesota, for their design expertise in building, setting up and installing lake-
monitoring equipment. Karen Jensen at the Metropolitan Council for helping obtain
data from area waste water treatment plants. Amy Myrbo and Kristina Brady at the
LacCore facility at the University of Minnesota for their help in obtaining and analyzing
sediment cores. The members of my technical advisory panel including Wayne Sand-
berg, Connie Fortin, Biz Colburn, Andrew Kubista, Debra Fick, Kathleen Schaefer,
Norm Ashfeld, Greg Felt, Jeff Goetzman, Eric Macbeth, Tom Struve, and Ann McLel-
lan. And my co-workers Andrew Sander, Ben Janke, Jeremiah Jazdzewski and the rest
of the staff and students at the St. Anthony Falls Laboratory for helping me with many
aspects of the project.
i
I would also like a acknowledge all of the sources of funding that have allowed me
to pursue my research goals. This includes the Minnesota Local Road Research Board
(LRRB), which funded a two-year study on environmental effects of road salt in the state
of Minnesota. Also the Silberman fellowship, University of Minnesota Doctoral Disser-
tation Fellowship and the University of Minnesota - Civil Engineering summer graduate
student fellowship, all of which provided me with the financial means to conduct my
research.
ii
Dedication
I dedicate this thesis to the people closest to me. First to my wife Susan. With out
you by my side this accomplishment would never have been possible. Thank you for
being there when I needed you, for being brutally honest when it was warranted and
for keeping me focused on what really mattered.
I also dedicate this to my parents Lynn and Vladimir and my brother Paul. Thank
you for making me the person I am today and providing me with guidance and support
throughout the years. The examples you set for me have been a guiding light towards
my accomplishments.
iii
ROAD DEICING SALT IMPACTS ON URBAN WATER QUALITY
by Eric Vladimir Novotny
ABSTRACT
Salt is widely used for ice and snow control on roads in the US, Canada and other
parts of the world affected by adverse winter driving conditions. The primary product
applied in North America for deicing of roads is sodium chloride (NaCl), a readily avail-
able and inexpensive material. The use of sodium chloride as a road deicing chemical
has increased dramatically in the northern areas of the United States over the last 50
years with about 23 million tons used in 2005.
The primary objective of my research was to determine how road salt applications
influenced the water quality in a major metropolitan area (Twin Cities metropolitan
area (TCMA) of Minneapolis/St Paul, Minnesota, USA). This objective was met by
collecting and analyzing data from area lakes, streams and rivers and through the de-
velopment 0 Dimensional (0D) and 1 Dimensional (1D) models.
It was determined that on average over 70% of the chloride applied annually in the
TCMA was retained in the watershed instead of entering the Mississippi River and
eventually exported to the Gulf of Mexico. Salinity cycles were observed in area lakes
with high concentration in the winter followed by lower concentrations in the spring
and summer. Mean annual concentrations in 38 lakes in the TCMA rose on average 1.4
mg/L per year over 22-years matching a similar trend in the amount of rock salt the
state of Minnesota purchased over the same time period.
Salt water inflows changed the natural mixing behavior of area lakes. In some lakes
monomictic behavior developed with mixing events only occuring in the fall. The pres-
ence of a saline layer at the bottom of the lake prohibited dissolved oxygen from reaching
the benthic water layer in the spring extending the anoxic period of this water layer by
iv
6 months. Simulations conducted without the presence of a saline layer showed com-
plete mixing and oxygenation of the benthic layers in the spring and fall. Rising Cl
concentrations in lakes are expected to continue. If the annual inputs of salt to the
lakes were stopped it would take 10 to 30 years to reach chloride concentrations equal
to predevelopment concentration.
Chloride retention in urban areas where road salt is applied should cause much concern.
Mitigation measures, best management practices (BMPs) for road salt application and
alternatives to NaCl need to be examined.
v
Contents
Acknowledgements i
Dedication iii
Abstract iv
List of Tables x
List of Figures xi
1 Overview 1
1.1 Problem Definition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2
1.2 Background Information . . . . . . . . . . . . . . . . . . . . . . . . . . . 2
1.2.1 Biota . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2
1.2.2 Heavy metal transport . . . . . . . . . . . . . . . . . . . . . . . . 7
1.2.3 Soil chemistry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
1.2.4 Lakes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
1.3 Study Objectives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
1.4 Methodology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
1.5 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14
1.6 Overall Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
2 Chloride ion transport and mass balance in a metropolitan area using
road salt 19
2.1 Abstract . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20
vi
2.2 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21
2.3 Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22
2.3.1 Metro area chloride balance . . . . . . . . . . . . . . . . . . . . . 22
2.3.2 Inflows and outflows . . . . . . . . . . . . . . . . . . . . . . . . . 25
2.3.3 Chloride sources . . . . . . . . . . . . . . . . . . . . . . . . . . . 26
2.3.4 Chloride balances in sub-watersheds . . . . . . . . . . . . . . . . 28
2.4 Results and Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29
2.4.1 Inflows and outflows of chloride in the major rivers . . . . . . . . 29
2.4.2 Metro area chloride sources . . . . . . . . . . . . . . . . . . . . . 31
2.4.3 Metro area chloride balance calculation . . . . . . . . . . . . . . 33
2.4.4 Sub-watershed chloride balance calculation . . . . . . . . . . . . 35
2.4.5 Sodium retention . . . . . . . . . . . . . . . . . . . . . . . . . . . 38
2.4.6 Sensitivity of the results . . . . . . . . . . . . . . . . . . . . . . . 38
2.4.7 Comparison to other metro areas . . . . . . . . . . . . . . . . . . 41
2.4.8 Chloride retention in the TCMA watershed . . . . . . . . . . . . 41
2.5 Summary and Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . 44
3 Increase of urban lake salinity by road deicing salt 46
3.1 Abstract . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47
3.2 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48
3.3 Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50
3.3.1 Data collection . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50
3.3.2 Data analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54
3.4 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56
3.4.1 Ionic composition and relationship to specific conductance . . . . 56
3.4.2 Seasonal salinity cycles and salinity stratification . . . . . . . . . 58
3.4.3 Effects of salinity on seasonal mixing and dissolved oxygen . . . 61
3.4.4 Salinity in lake sediment cores . . . . . . . . . . . . . . . . . . . 61
3.4.5 Salinity trends in TCMA lakes . . . . . . . . . . . . . . . . . . . 63
3.4.6 Relationships between lake salinity and watershed characteristics 64
3.5 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66
3.5.1 Comparison of ionic composition with other freshwaters . . . . . 66
vii
3.5.2 Indicators of the salinity sources . . . . . . . . . . . . . . . . . . 68
3.5.3 Salinity, temperature and dissolved oxygen stratification . . . . . 69
3.5.4 Seasonal flushing of salt from the TCMA lakes . . . . . . . . . . 70
3.5.5 Convective mixing of saline lake water with pore water in the
sediments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71
3.5.6 Salinity trends in TCMA lakes . . . . . . . . . . . . . . . . . . . 72
3.5.7 Relationships between lake salinity, lake bathymetry and water-
shed characteristics . . . . . . . . . . . . . . . . . . . . . . . . . . 73
3.6 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74
4 A 0-D modeling approach to study long-term chloride concentration
in lakes receiving runoff containing road salt 76
4.1 Abstract . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77
4.2 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78
4.3 Lake Chloride Model Fomulation . . . . . . . . . . . . . . . . . . . . . . 79
4.3.1 Zero-dimensional model formulation . . . . . . . . . . . . . . . . 79
4.3.2 Daily time scale model . . . . . . . . . . . . . . . . . . . . . . . . 79
4.3.3 Annual time scale model . . . . . . . . . . . . . . . . . . . . . . . 82
4.3.4 Model assumptions . . . . . . . . . . . . . . . . . . . . . . . . . . 83
4.4 Lake data collection and model calibration . . . . . . . . . . . . . . . . . 84
4.5 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 86
4.6 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 91
4.6.1 Model Sensitivity . . . . . . . . . . . . . . . . . . . . . . . . . . . 91
4.6.2 Model projections . . . . . . . . . . . . . . . . . . . . . . . . . . 92
4.7 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93
5 Road salt impact on vertical lake mixing 95
5.1 Abstract . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 96
5.2 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 97
5.3 Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 99
5.3.1 Field Investigation: Data Collection/Sampling Site . . . . . . . . 99
5.3.2 Model Formulation: Simulation of Summer Stratification in a
Lake with a Benthic Saline Layer . . . . . . . . . . . . . . . . . . 100
viii
5.3.3 Model Simulation of Dissolved Oxygen Transfer in a Lake with a
Saline Benthic Layer . . . . . . . . . . . . . . . . . . . . . . . . . 108
5.4 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 111
5.4.1 Saline Layer Formation: Continuous lake monitoring results . . . 111
5.4.2 Lake Stratification: Model calibration results . . . . . . . . . . . 115
5.4.3 Lake Stratification and Vertical Mixing: Model simulation results 116
5.4.4 Dissolved Oxygen Modeling Results . . . . . . . . . . . . . . . . 122
5.5 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 126
5.5.1 Interpretation of Measurements (2007-2009) and Simulation Re-
sults (2007-2008) . . . . . . . . . . . . . . . . . . . . . . . . . . . 126
5.5.2 Effects of Benthic Saline Layer Formation on Lake Water Quality 128
5.6 Summary and Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . 129
References 131
Appendix A. Data Sets 146
ix
List of Tables
2.1 Names of sampling points and data collection organizations . . . . . . . 24
2.2 Estimates of average chloride concentrations, flow rates, and total mass
of Cl in effluents from major WWTPs . . . . . . . . . . . . . . . . . . . 32
2.3 Stream watershed information and road salt application rates within each
sub-watershed . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36
3.1 Lake and watershed information . . . . . . . . . . . . . . . . . . . . . . 52
3.2 Median ionic concentrations of water sampled from 9 lakes . . . . . . . . 56
3.3 Salinity (Cl-) cycles in TCMA lakes. . . . . . . . . . . . . . . . . . . . . 60
3.4 Historical average, trend and maxima of chloride concentrations, and
bathymetric and watershed data for 38 TCMA lakes . . . . . . . . . . . 65
3.5 Correlation coefficients of chloride concentrations with lake and water-
shed parameters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66
3.6 Ionic composition (mg/L) of selective surface waters in North America
and the nine lakes studied in 2006/2007. . . . . . . . . . . . . . . . . . . 67
4.1 Lakes modeled . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85
4.2 Model parameters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 86
4.3 Maximum and minimum chloride concentrations at equilibrium . . . . . 88
4.4 Chloride loading rates, flushing flow rate and flushing rate . . . . . . . . 91
5.1 Comparison of specific conductance recorded by the Buoy system to val-
ues measured with the YSI Model 63 probe . . . . . . . . . . . . . . . . 112
5.2 Best fit parameters from model calibration . . . . . . . . . . . . . . . . . 115
x
List of Figures
1.1 Sodium chloride deicing salt used for the United states and the state of
Minnesota . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
1.2 Density current intrusion of snowmelt water into a lake (schematic). . . 11
2.1 Watershed boundaries of the Twin Cities metropolitan area and major
rivers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
2.2 Median concentrations of sodium and chloride from the two major rivers 29
2.3 Flow-weighted average monthly chloride concentrations and flow rates at
the inflow and outflow of the major rivers . . . . . . . . . . . . . . . . . 30
2.4 Grab sample chloride concentrations from the effluents of the four WWTPs 32
2.5 (A) Monthly chloride fluxes (t/yr) from point sources entering or exiting
the Twin Cities metropolitan area watershed (B) Monthly differences
between the Outflow and the Inflow + WWTP . . . . . . . . . . . . . . 34
2.6 Average annual chloride concentrations vs. amount of chloride applied
per watershed area for the 10 subwatershed streams . . . . . . . . . . . 37
2.7 (A) Daily averages of specific conductance from 15-minute continuous
monitoring (B) Cumulative normalized distribution functions of daily
specific conductance values. . . . . . . . . . . . . . . . . . . . . . . . . . 39
2.8 Chloride concentrations in two streams of the Twin Cities metropolitan
area . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42
2.9 Chloride concentration in wells located throughout the Twin Cities Metropoli-
tan area . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43
3.1 Chloride concentrations in Battle Creek . . . . . . . . . . . . . . . . . . 49
3.2 Locations and watersheds of lakes sampled . . . . . . . . . . . . . . . . . 51
3.3 Relationship between chloride and specific conductance . . . . . . . . . 57
xi
3.4 Chloride concentrations in each lake . . . . . . . . . . . . . . . . . . . . 58
3.5 Seasonal salinity (Cl-) cycles . . . . . . . . . . . . . . . . . . . . . . . . 59
3.6 Chloride concentration, dissolved oxygen concentration and water tem-
perature vs. depth in Tanners Lakes . . . . . . . . . . . . . . . . . . . . 62
3.7 Ionic composition of pore water in sediment cores . . . . . . . . . . . . . 63
3.8 Average normalized specific conductance in 38 Twin Cities Metro Area
lakes and total rock salt purchases by the State of Minnesota. . . . . . . 64
4.1 Modeled and observed chloride concentrations . . . . . . . . . . . . . . . 87
4.2 Projected future chloride concentrations . . . . . . . . . . . . . . . . . . 89
5.1 Lake location and bathymetry for Tanners Lake . . . . . . . . . . . . . . 99
5.2 Schematic of Buoy set up . . . . . . . . . . . . . . . . . . . . . . . . . . 101
5.3 Weather parameters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 109
5.4 Specific conductance for uncorrected and corrected data . . . . . . . . . 112
5.5 Recorded temperature and specific conductance . . . . . . . . . . . . . . 113
5.6 Specific conductance data and weather data for buoy system. . . . . . . 114
5.7 Modeled and observed water temperature and specific conductance . . . 117
5.8 Temperatures and specific conductance at the surface, at mid-depth and
at the bottom of Tanners Lake . . . . . . . . . . . . . . . . . . . . . . . 118
5.9 Root mean square error between modeled and observed data . . . . . . 119
5.10 Data used as initial conditions for simulations . . . . . . . . . . . . . . . 120
5.11 Time vs. depth plot of model simulation results . . . . . . . . . . . . . 121
5.12 Profiles of density gradients caused by salinity and temperature . . . . . 123
5.13 Daily hypolimnetic eddy diffusion coefficients near the lake bed . . . . . 124
5.14 Results from the case study dissolved oxygen simulation . . . . . . . . . 125
xii
Chapter 1
Overview
1
2
1.1 Problem Definition
In the snow-belt regions of the U.S. and other northern countries deicing agents are
applied to remove snow and ice from roadways in winter in order to increase driving
safety. The primary agent used for this purpose is rock salt consisting mainly of sodium
chloride (NaCl). Other agents in the road salt mixture, such as ferrocyanide, which is
used as an anti-clumping agent, and impurities consisting of trace elements (phosphorus,
sulphur, nitrogen, copper and zinc), can represent up to 5% of the salt weight [1].
In the U.S. annual rock salt use for road de-icing increased from 163,000 tons in
1940 to over 23 million tons in 2005 according to the United Stated Geological Survey
(USGS) mineral yearbooks [2, 3]. In the state of Minnesota annual rock salt purchases
increased during the same time period from 60,000 tons to over 900,000 tons [2](Figure
1.1. Other deicing agents are available (e.g. calcium or magnesium chloride (CaCl2)
or potassium acetate), but because of a large difference in cost NaCl is applied most
frequently [4].
Road salt applications keep roads free of ice for safe winter travel in northern climate
zones, however this practice comes at a cost to the infrastructure and the environment,
especially in urban areas with high road densities. The rock salt applied to the roads
dissolves in the melting snow and ice separating into sodium and chloride ions. The
salt- containing water runs off into streams, lakes or storm sewers or infiltrates into the
soil eventually reaching the groundwater. It affects the chemistry and biota in the soil
and water [5]. The overall scope of my PhD research project was to analyze the fate and
transport of road deicing salt (NaCl) in the environment and the water quality issues
associated with road salt applications in a major metropolitan area (Minneapolis/St.
Paul Twin Cities Metropolitan Area, Minnesota, United States).
1.2 Background Information
1.2.1 Biota
Chloride and sodium levels can influence terrestrial and aquatic biota. Chloride levels
of 1000 mg/l can have lethal or sub-lethal affects on aquatic plants and invertebrates
[6]. Continuous levels as low as 250 mg/L have been shown to be harmful to aquatic life
3
0.0
0.2
0.4
0.6
0.8
1.0
1.2
0
5
10
15
20
25
1930 1940 1950 1960 1970 1980 1990 2000 2010 M
inn
es
ota
Ro
ck
Sa
lt U
se
(M
illi
on
to
ns
)
Un
ite
d S
tate
s R
oa
d S
alt
Us
e (
Mil
lio
n t
on
s)
United States Road Salt Use
Minnesota Rock Salt Use
Figure 1.1: Total amount of sodium chloride (NaCl) used as deicing salt throughoutthe United States and the annual amount of rock salt (NaC) purchased by the state ofMinnesota [2].
4
and to render water non-potable for human consumption [6]. In the state of Minnesota
chloride standards of 860 mg/L for acute exposure events and 230 mg/L for chronic
exposure have been established by the Minnesota Pollution Control Agency (MPCA)
for surface waters designated as important for aquatic life and recreation (Minnesota R.
Ch. 7050 and 7052). The groundwater standard for chloride has been set at 250 mg/L
by the USEPA and is a secondary standard relating to the taste of the water.
Increases in sodium and chloride concentrations have been show to decrease the bio-
diversity in wetland areas and waterways [7, 8]. Wood frog species richness in wetlands
in northwestern and southwestern Ontario have been negatively impacted by increased
stress, increased mortality, and altered development resulting from acute and chronic
exposure to road salts [9]. Fish diversity and richness also decreased as sodium and
chloride concentrations increased along with an increase in impervious surfaces in river
watersheds in the Twin Cities area [10]. Macroinvertebrates on the other hand are not
affected by levels of chloride found in wetlands [11, 12]. Chloride ranks third among
chemical ion species for the regulation of diatom species, and is therefore used by paleo-
limnologists to reconstruct chloride levels in lakes from sediment cores [13, 14].
Microorganisms and bacteria can also be influenced by the salinity of the water.
Microorganisms are classified into four groups based on how they react to salt concen-
trations [15]. The first two groups are classifications for nonhalophiles. Nonhalophiles
can be either salt sensitive or salt tolerant. Salt sensitive bacteria can only grow in
media containing less that 2 percent salt (20,000 mg/L). On the other hand salt tol-
erant bacteria grow best in media containing less that 2 percent salt, but will grow in
media containing more that 2 percent. Halophiles can also be classified in two groups:
facultative and obligate. Facultative halophiles will grow in media containing less that
2 percent salt, but will grow best in media containing more that 2 percent. Obligate
on the other hand can only grow in media containing more that 2 percent growth.
These four groups are also known as nonhalophiles, halotolerant bacteria, halophiles
and extreme halophiles respectively [16].
The presence of salts influences the waters activity (amount of water available for
biological processes). Water activity is defined as the ratio between the vapor pressure
of a solution to the vapor pressure of pure water resulting in a value of 1 for pure
water and 0.98 for seawater (3.5% salinity) [16]. Water flows from regions of low solute
5
concentrations to regions of high solute concentration through osmosis [16].
In most bacteria the cytoplasm of a cell has a higher concentration of solutes than
the surrounding environment resulting in a flow of water into the cell[16]. If the salinity
outside the cell causes the activity of the water to be lower than that of the cytoplasm
inside the cell, the flow will reverse will happen causing dehydration of the bacteria.
The loss of water from the cytoplasm results in the fastest and most lethal consequence
high salinity can have on a bacteria [17]. Most freshwater and marine organisms are
stenohaline, i.e. they can not handle wide fluctuations in salinity, but some organisms
have the ability to withstand increases in salinity from their normal environment with
a reduction in growth rates (halotolerant)[17].
In order to adjust to the decrease in water availability in the media around the cell,
most halotolerant and halophilic bacteria must maintain a cytoplasm with a much lower
salt concentration then their surrounding environment. The bacteria accomplish this
by creating low molecular weight organic compounds that help provide osmotic balance
between the medium and the cell cytoplasm [18]. The low molecular weight solutes
accumulate in the cytoplasm creating a high intracellular concentration allowing for the
flux of water to continue to flow into the cell. These solutes are preferred due to their
protective nature against inactivation, inhibition, and denaturalization of enzymes and
macromolecular structures [17].
The solutes that respond to external osmotic pressures are called osmotica. Osmotica
share three main qualities, they are polar, highly soluble molecules and show only
limited interactions with proteins. Polyols (glyceral, arabitol, mannitol, erythritol)
sugars (sucrose, trehalose), hetersides (glucosylglycerol), betaines (trimethylammonium
compounds) thetines (dimethylsulfonium comounds), amino acids (proline, glutamate,
glutamine and derivates), glutamine amide derivative, and ectoines are some of the
most important know osmotica [18]. The ability of the cells to create these osmotica
allows them to regulate the solute concentration inside the cell according to the salt
concentration outside the cell. This change in solute concentration can be achieved
rapidly when the outside concentration is changed allowing these bacterial to withstand
fluctuations in salt concentration.
High salinity concentration can also influence the solubility of proteins. They can
create a ’salting out’ or ’salting in’ effect depending on the anions or cations in the
6
medium. Salting out ions strengthen the hydrophobic bonds in proteins causing them
to become less soluble. Salting in ions do the opposite, making the proteins more soluble
by decreasing the hydrophobic bonds [17]. The changes in solubility of proteins can also
influence the hydrophobic and hydrophilic interactions responsible for the stability of
the lipid bilayers in the cell. The ions can dehydrate this layer by out competing the
lipids for water. Some solutes can even partition into the hydrophobic domain [17].
In general all halophilic and halotolerant bacteria have a certain number of adapta-
tions that are required to survive in environments with high fluctuations in salt concen-
trations. These include having the ability to adjust the solute concentration inside the
cytoplasm of the cell causing a reduction in the water availability that closely matches
the osmotic pressure in the outside medium. With out this ability the cell could either
burst with a sharp reduction in salinity in the outside medium or dehydrate with a
sharp increase salinity. The second adaptation that all halophilic bacteria have is the
ability to prevent toxic ions such as sodium and chloride from entering the cell into the
cytoplasm.
A third property of halophilic bacteria is that they have created adaptations to their
external structures such as the cell wall, membranes, and extra cellular and membrane
enzymes. This third adaptation of halophilic bacteria represents the greatest difference
between bacteria that can live in high salt environments and other non-salt tolerant
species [17]. This adaptation is due to the evolutionary process that changes the syn-
thesis of structural molecules. This adaptation also explains how halophilic bacteria are
dependent on high salt concentrations since the extra cellular materials are irreversibly
adapted to salt [17].
If a small stream receives snowmelt runoff directly from roadways treated with salt
(NaCl), concentrations of sodium and chloride will spike during the winter and spring
months, and decline quickly once the salt application has stopped [19]. In the state of
Minnesota data are available showing high concentrations of chloride traveling through
streams and storm sewers during the winter months. The large fluctuation in salinity
could negatively effect organisms that are not able to adapt quickly to the salinity
change reducing the biodiversity in the stream.
Four streams (Shingle Creek, Nine Mile Creek, Beavens Creek and Battle Creek)
7
in the Minneapolis/St. Paul Twin Cities Metropolitan Area (TCMA) have been desig-
nated in 2008 as impaired waters and placed on the Clean Water Act section 303d Total
Maximum Daily Load (TMDL) list because of salt pollution [20]. In one of those streams
(Shingle Creek) the highest recorded concentration of chloride reached 12,000 mg/L in
the winter [21]. Median concentrations at the same locations were 150 mg/L and mini-
mum concentrations were 64 mg/L during the summer months. Chloride concentrations
in grab samples of storm sewer effluents reached 35,000 mg/L during the winter [20]. In
storm sewers emptying into the Mississippi River, concentrations of chloride reached 900
mg/L during January while the maximum concentrations were less that 130 mg/L in
the summer. Other regions have shown similar elevated chloride concentrations [22, 4].
Chloride concentrations in urban streams of the northeastern United States have been
measured as high as 5000 mg/L during the winter months [23].
1.2.2 Heavy metal transport
NaCl is not the only constituent in snowmelt runoff that can have environmental conse-
quences. In urban environments, specifically on roadways, heavy metals are deposited
by automobile traffic. Sources of the metal pollutants are tire wear, engine and break
parts, fluid leakage, vehicular component wear, atmospheric depositions and road sur-
face abrasion [24, 25]. These metals are transported by runoff from rainfall or snowmelt
into receiving water bodies resulting in the contamination of soils, lakes, streams, wet-
lands and groundwater. Heavy metal concentrations in stormwater runoff can reach
levels high enough to be toxic or even severely toxic to biota especially in runoff from
major highways [26]. Copper, zinc, lead, cadmium, sediments, PAHs, and deicing salts
represent the main source of pollution found in runoff from roads [27]. Heavy metals are
the most consistent pollutants in roadside runoff [28] ], and the highest concentrations
of metals come from major highways [29].
Heavy metals accumulate in the snowpack and on roadways during the winter
months. This accumulation combined with the increased corrosion of metals and wear
on the roadways in winter results in both higher concentrations and a higher total load
of metals during snowmelt compared to rainfall [24, 30, 26, 31, 32]. Concentrations of
metals in snowmelt runoff can be two to four times higher than during rainfall; the
8
highest concentrations occurring during rainfall on a snow pack [32]. The higher con-
centrations of heavy metals and the presence of deicing salts in snowmelt runoff cause a
larger number of toxic and severely toxic events to occur compared to rainfall events [26].
This increase in toxicity can reduce the diversity in the benthic and plant communities
[33].
De-icing salts, mostly NaCl, and temperature increase the mobility of metals in soil
environments [34]. The increase is caused by a change in the partitioning coefficients
between the dissolved and particulate phases of the metals especially cadmium, zinc,
and copper. When the salinity is increased or the temperature drops, the partitioning
coefficients decrease resulting in an increase of the bioavailable dissolved phase portion
of the metals to increase [35, 34, 36]. Increased mobility of metals, such as Cd Cu, Fe,
Pb, due to road salt applications has been observed in the environment.
Cd and Zn mobilization is affected by metal-chloride complexation as well as ion
exchange with Na, Ca or H [37, 38, 39]. The transport of Pb and Cu on the other
hand are influenced by the dispersion of organic matter and colloid-assisted transport
[40, 37, 39]. The increase in colloid-assisted transport was caused by the presence of high
concentrations of sodium attached to the soil particles. Soils with high concentrations of
sodium swell due to the relative size of the Na ion compared to Ca or Mg. This swelling
results in the breakup of the soils, a reduction in the soils hydraulic conductivity and
an increase in colloid dispersion [41]. Colloidal facilitative transport can be a dominant
process in the transport of strong sorbing materials [42].
In Sweden Pb, Cu, and Zn were found to be suceptable to increased mobilization
in roadside soils and leaching into the groundwater where high concentrations of NaCl,
reducing conditions and lowered pH were present [43]. In Germany Cd and Zn concen-
trations in roadside soils in winter and fall were observed to be extremely different from
those in summer and spring due to leaching from applications of deicing salts (NaCl)
[36].
At the sediment/water interface of a small pond near a major highway in Ontario,
Canada, Cl and Na concentration were measured greater than 3 and 2 g/L respectively.
These concentrations decreased gradually with depth into the sediments, but 40 cm
into the sediments Cl concentrations were still 1.5 g/L. These high concentrations in the
sediment pore waters increased the dissolved concentrations of Cd resulting in increased
9
toxicity of the water to benthic organism [44].
Concentrations of metals in snowmelt runoff are related to the runoff hydrograph.
Dissolved pollutants (50%-90%) are transported primarily in the first fraction of the
snowmelt runoff while most of the particulate matter, and the metals adsorbed to those
particles, are found in the last part of the snowmelt runoff [45][46]. A higher percentage
of metals in the snowmelt runoff are incorporated in the particulate phase, while the
majority of metals in rainfall events are in the dissolved phase. This is mostly due to
the higher concentrations of suspended solids and particulate matter in snowmelt runoff
compared to rainfall, except for high intensity, short duration, rainfall events [32].
1.2.3 Soil chemistry
Soil particles have a net negative charge for two reasons: 1) isomorphic substitution of
Al by Mg or Fe or Si by Al, resulting in a permanent change on the clay particles [47]
and 2) organic matter functional groups such as carboxyls, and or surface hydroxyls of
inorganic material, resulting in a variable change dependent on pH and ionic strength of
the soil solution [48]. Isomorphic substitution is the replacement of an atom by another
atom of similar size in the clay structure. In the case of Al being substituted by Mg,
the sizes of the atoms are similar but the charges are different. Al has a net charge of
+3 and Mg has a net positive charge of +2 resulting in a net negative charge on the
clay particle after substitution. The variable charge forms by the donation of protons
from the organic matter functional groups or surface hydroxyls. When the pH of the
soil environment increases the weak acid functional groups donate a hydrogen proton
resulting in a net negative charge.
The net negative charge on the soil particles is balanced by the adsorption of cations
consisting mostly of Ca, Mg, Na and K but also H, Fe, and Al. Typically Ca and Mg
are preferred over Na due to the smaller size of the ions and the divalent change, but
when water with high concentrations of sodium infiltrates the soils, sodium becomes pre-
ferred inducing ion exchange between the sodium and primarily calcium and magnesium
[49][50][38][41][45]. The process increases the concentration of calcium and magnesium
in surface and groundwater and decreases the Na/Cl ratio.
In a study on Mirror Lake, NH, the Na/Cl ratio was 1.01 from 1970 to 1975. After the
construction of an interstate highway in the watershed, highway deicing salts caused a
10
fourteen fold increase in Cl and a decrease in the Na/Cl ratio to 0.68 [51]. Ion exchange
can increase the mobility of hydrogen ions and decrease the pH of the water in the
process [38][45]. The change to soil chemistry by road salt applications is typically
restricted to a distance of 10 m from the road. The most significant soil exchange
processes occur within 6 m of salt applications [41]. The sodium continues to exchange
with calcium, magnesium and even potassium until equilibrium is reached; from then
on sodium will act conservatively [50].
The adsorption of the sodium ions onto the clay particles influences the properties of
the soils. Due to the relatively large size, single electrical charge and hydration status of
sodium ions, when sodium replaces calcium and magnesium the forces binding the soils
particles are disrupted causing separation, dispersion and swelling [52]. Soil dispersion
hardens soils and blocks water infiltration by causing clay particles to plug soil pores
reducing soil permeability. Soil dispersion also reduces the hydraulic conductivity of the
soil, i.e. the rate at which water flows through the soil [52]. In general, clays containing
mostly Na-ions are sticky and impervious while clays containing mostly Ca-ions are
workable and permeable [53]. Because sodium can change the permeability of soils,
brines are used in reservoirs to convert calcium clays to sodium clays in order to make
the bottom sediments less permeable [53].
1.2.4 Lakes
Streams and storm sewers capturing snowmelt water from roadways are likely to cause
seasonal salinity variations in lakes into which they discharge. Salt concentrations in
urban streams during the winter months are sufficiently high to cause density currents
and chemical stratification in the receiving lakes (Figure 1.2). This phenomenon has
been documented in Minneapolis where a saline density current, occurring synoptically
with above freezing air temperatures and snowmelt runoff, proceeded to the deepest
part of a small lake where it remained until spring [54]. A NaCl concentration of 1
g/L (Cl concentration of 600 mg/L) can increases the specific gravity of water by
approximately 0.0008 [55]. This density change by salinity is significant in relation to
a temperature-induced density change, especially at low temperatures. For example,
a temperature change from 4o to 5o C produces the same specific gravity change as a
salt concentration increase of 10 mg/L [55]. A saline water layer can cause a lake to
11
become permanently density stratified at the bottom. In such a meromictic lake, the
bottom waters never mix completely with the surface waters. Naturally meromictic lakes
exist in dry regions of the world and the consequences often include dissolved oxygen
depletion and high concentrations of phosphate, ammonia, and hydrogen sulfide at the
sediment water interface. Small lakes and deep lakes are more vulnerable to becoming
meromictic; large lakes have more fetch and therefore experience more powerful wind
mixing [6]. Shallow lakes require a smaller amount of wind energy to fully mix than
deep lakes.
Figure 1.2: Density current intrusion of snowmelt water into a lake (schematic).
The formation of meromixis in a lake is of concern because it can have many con-
sequences. Chemical stratification impedes vertical mixing preventing dissolved oxygen
(DO) from reaching the benthic layers of the lake. The low DO conditions that develop
below the chemocline can result in the loss of all but the most resilient deep water species
[6]. Meromixis can also limit transfer of DO and other solutes at the sediment/water
interface. This is significant because phosphorus and heavy metals are more readily
released from anoxic sediments [6]. Elevated salinity decreases the partition coefficient
of some metals, thus causing a release of soluble toxic metal forms from the sediment
[4]. These issues can become important for lakes receiving runoff from snowmelt that
contains road salt.
Road salt applications have been shown to increase the salinity in lakes near major
roadways especially in urban watersheds [14, 51, 56]. Extreme cases have been reported:
chloride concentrations reached up to 5190 mg/L in a pond draining a major urban
highway in Canada; other ponds showed concentrations up to 3000 mg/L during the
12
winter [57, 58, 44]. Road salt applications in rural areas have affected lakes within a few
hundred meters. In urban environments, the presence of storm sewer can increase the
distance of this influence [6]. A more comprehensive summary of existing research on
this subject can be found in a summary report commissioned by Environment Canada
and Health Canada [59].
1.3 Study Objectives
This PhD dissertation examines road salt transport in an urban environment. The study
is conducted in the urban watershed of the Twin Cities metropolitan area (TCMA) of
Minneapolis/St. Paul in Minnesota. Four major questions are addressed in separate
chapters:
• How much of the roadsalt (NaCl) applied on TCMA roadways each year is leaving
the watershed by the Mississippi River, and how much Is accumulating in the lakes
and groundwater of the TCMA?
• What are current and historical chloride concentration dynamics in different lakes
of the TCMA?
• What are the projections for future salinity levels in lakes of the TCMA?
• How is a saline water layer formed at the bottom of a lake, and how does this
saline water layer influence vertical lake mixing dynamics?
The research was motivated by the overall hypothesis that an excessive accumulation
of roadsalt (NaCl) in surface waters and groundwater could have serious, and possibly
unacceptable consequences (e.g. violations of water quality standards) by changing the
chemistry and ecology of these waters. Road salt practices may have to be changed
to avoid the formation of monomictic lakes and widespread exceedances of chronic and
acute water quality standards in urban lakes.
1.4 Methodology
Metro area chloride budget: Road salt application data were obtained from cities,
counties and state agencies in the TCMA, flow rates and effluent chloride concentrations
13
from wastewater treatment plants in the TCMA, and flow and chloride data from area
streams and rivers were assembled for the years 2000-2008. With this data the rates of
total annual salt (chloride and sodium) imports to the TCMA, rates of salt addition and
transport within the TCMA, and rates of salt exports from the TCMA in the Mississippi
River were calculated and analyzed. The difference between total annual rate of salt
import and export gives an estimate of how much road salt is retained in the TCMA,
i.e. stored in the soils, the lakes and the groundwater throughout the TCMA. This
component of the overall salt budget can cause progressive environmental degradation.
Sub-watershed chloride budgets: Chloride budgets for 10 sub-watersheds within
the TCMA, were analyzed in a similar way. None received input from a wastewater treat-
ment plant. The sole chloride input was from road salt applied in each sub-watershed.
Historical data analysis: Historical water quality data for lakes and streams
including sodium and chloride concentrations were assembled and analyzed. Data sets
were obtained from the MPCA environmental data access database for 72 lakes in the
Twin Cities metropolitan area (TCMA). Of those 72 lakes 39 had at least 10 years of
data over the last 22 years. These data sets were normalized with the average concen-
tration between 2001 and 2005 and averaged together to obtain a time series of lake
chloride concentrations. The results could then be correlated with the amount of rock
salt purchased by the state of Minnesota over the same time period. Other historical
data were obtained from other Minnesota State Agencies and the Metropolitan Council.
Lake profiling: Profiles of water temperature and specific conductance in 9 area
lakes were measured every 6 weeks between January 2006 and November 2008. A rela-
tionship between chloride concentrations and specific conductance was determined using
water samples taken in these lakes. Using the conductivity vs. chloride relationship the
profiles of specific conductance were converted to chloride profiles to see chemical strat-
ification. Seasonal changes in stratification and volumetric concentration averages were
then obtained for each lake.
Continuous lake monitoring: To get a data set of high temporal resolution, sen-
sors and recording equipment were installed under a buoy in one of the lakes (Tanners
Lake near I-94 in Oakdale) to continuously monitor temperature and specific conduc-
tance at 2-minute intervals from November 2008 to August 2009. Thirteen temperature
and specific conductance probes were connected to a data logger that stored the data
14
and could be interrogated by remote access. The data collected were used to analyze the
intrusion of saline runoff into the lake during the winter, and vertical lake-mixing during
the following open water season. The data were correlated to weather parameters.
Lake modeling: Two deterministic and unsteady lake simulation models were
developed to analyze and project lake chloride concentrations at two timescales. The
first model was a 0-D model simulating the accumulation and flushing of salt at a weekly
time scale in lakes receiving runoff containing road salt. Seven lakes were simulated and
each lake was treated as completely mixed with accumulation of salt occurring in winter
and early spring, and flushing by runoff from rainfall in late spring, summer and fall.
Specific conductance profiles measured every 4-6 weeks over 3 to 5 years were used to
calibrate the model. Simulations were run with the calibrated model to predict future
chloride concentration under difference salt loading scenarios, i.e. road salt application
practices.
The second simulation model was created to simulate vertical lake mixing during
the summer stratification period using a 1-D model and a daily time scale. This model
predicted vertical profiles of temperature, specific conductance (salinity) and dissolved
oxygen (DO) at a daily timestep using daily weather parameters and lake bathymetry
as inputs. Initial temperature and salinity profiles were taken after ice out. The model
was applied to Tanners Lake and simulations predicted temperature, salinity and DO
profiles throughout the ice-free period of the lake.
1.5 Results
Results of the field data collection, analysis of historical and recent data, and simulations
of 7 TCMA lakes with the 0D model, and of Tanners Lake with the 1D model provided
answers to the four questions posed earlier.
In chapter 2 the retention of chloride from road deicing salt (NaCl) application in the
watershed encompassing the TCMA was examined. A chloride budget for the TCMA
watershed, including river inflows and outflows, and major salt inputs from household,
industrial, commercial and road salt applications was prepared at an annual timescale. It
was found that 317,000 metric tons of road salt (NaCl) are applied annually In the seven
county TCMA (4150 km2 surface area). The TCMA watershed Is a little smaller and
15
accounts for a smaller amount of roadsalt. Length of roads, not surface area, were used
to make the adjustment. 77% of the chloride in this amount of road salt is retained in the
TCMA watershed. Salt retention depends foremost on the hydrologic drainage system,
which in the TCMA includes many lakes, wetlands, and detention/infiltration basins,
along with an extensive storm sewer system, many small streams, and an extensive
groundwater system of shallow and deep confined aquifers. Chloride concentrations in
many TCMA surface water bodies are now considerably higher than the pre-settlement
background levels of less than 3 mg/L. Wastewater treatment plants receiving most of
the NaCl used in water softeners, industrial and commercial applications, have effluent
Cl concentrations on the order of 200 to 400 mg/L. Chloride concentrations in some wells
of the surficial aquifers were as high as 2000 mg/L. Chloride concentrations reported for
wells in the TCMA aquifer system indicate a decrease of chloride concentrations with
depth below the surface, and with distance from major roadways.
In chapter 3 salinity and temperature profiles from lakes located throughout the
Minneapolis/St. Paul Twin Cities Metropolitan area (TCMA) were examined. Thir-
teen lakes in the TCMA were studied over 46 months to determine if and how they
respond to the seasonal applications of road salt. Sodium and chloride concentrations
in these lakes were 10 and 25 times higher, respectively, than in other non-urban lakes
in the region. Seasonal salinity/chloride cycles in the lakes were correlated with road
salt applications: high concentrations in the winter and spring, especially near the bot-
tom of the lakes, were followed by lower concentrations in the summer and fall due
to flushing of the lakes by rainfall runoff. The seasonal salt storage/flushing rates for
individual lakes were derived from volume weighted average chloride concentration time
series. The seasonal flushing rate ranged from 9 to 55% of a lakes minimum salt con-
tent. In some of the lakes salt concentrations near the lake bottom were high enough
to stop spring turnover preventing oxygen from reaching the benthic sediments in sum-
mer. Salt concentrations in the water layer above the sediments were high enough to
induce convective penetration of the denser saline water into the fresher sediment pore
water. A regional analysis of historical water quality records of 38 lakes in the TCMA
showed increases in average chloride concentrations of 1.4 mg/L per year from 1984 to
2005. These increases were highly correlated with the amount of rock salt purchased
by the State of Minnesota. Chloride concentrations in individual lakes were positively
16
correlated with the percent of impervious surface area in the watershed and inversely
with lake volume.
In chapter 4 a 0-D model was developed to simulate the seasonal chloride cycle of
loading and flushing, as well as the long-term accumulation of chloride in seven urban
lakes receiving runoff from roads. The model was used to determine steady state concen-
trations under different loading conditions. The model was calibrated using five years
(2004-2008) of monthly salinity profiles from the lakes in the TCMA, four model pa-
rameters and an initial concentration. Three of the seven lakes are headed towards year
round volume averaged chloride concentrations above the 230 mg/L chronic standard
for impairment to aquatic habitat. The two lakes with the lowest projected equilibrium
concentrations of chloride have already reached equilibrium. It was projected that one
lake will take up to 40 years to reach equilibrium. If road salt application rates are
reduced in future winters, lakes will respond with noticeably lower Cl concentrations
within 5 to 10 years. If road salt applications were discontinued altogether, chloride
concentrations should reduce to nearly natural levels within 10 to 30 years in all seven
lakes.
In chapter 5 three questions were addressed: How is a saline layer formed at the
bottom of a lake, how does a saline water layer at the bottom of a lake influences vertical
lake mixing dynamics, and how is the vertical transfer of dissolved oxygen influenced by
these mixing dynamics? The continuous specific conductance and temperature records
recorded at 2-minute interval in Tanners Lake give a detailed picture of saline water
build-up at the bottom of the lake. The saltwater intrusion and the resulting build-up
of the benthic saline layer occur in episodes correlated with warm weather periods and
snow melting. The very last salt water intrusion occurs after ice-out presumably due to
a lag in watershed runoff processes. Spring turnover after ice-out is not able to erode
the chemocline completely. The chemocline is weakened throughout the summer, but
the seasonal thermocline a few meters below the lake surface removes much of the wind
energy necessary to do the hypolimnetic mixing. The dynamic 1-D lake temperature and
salinity model was developed and matched to data from records of specific conductance
and temperature. The model was able to reproduce measurements from 2007 and 2008.
In 2007 the lake mixed completely in both spring and fall. In 2008 the lake did not mix
in spring allowing the saline layer to persist throughout the summer. In the fall of 2008
17
due to weakening of the saline layer and warming of the benthic waters, the lake was
able to completely mix. In 2009 the observed lake stratification behavior was similar to
2008. Inclusion of the lake number in the calculation of the hypolimnetic eddy diffusion
parameter made the mixing in the hypolimnion stronger when the lake was unstable in
the fall and spring and weaker in the summer when thermal stratification had formed.
Density stratification after ice out is dominated by salinity, but is quickly overtaken by
temperature stratification as the epilimnion warms. The existence of the saline layer
after ice out is strong enough to prevent oxygen from reaching the deeper water layers
in the lake. The presence of the saline layer causes the lake to switch from dimictic
behavior to monomictic behavior. As a result the lake sediments are oxygenated by
mixing of above only once per year at the fall turnover of the lake.
1.6 Overall Conclusions
Road salt is used to increase driving safety in the Twin Cities metropolitan area (TCMA)
of Minnesota. In this dissertation data for the TCMA area of 4150 km2 and a population
of 2.8 Million were collected and analyzed. Simulation models were developed to project
some of the consequences of road salt application for the water resources in the TCMA.
The results, as well as the methods by which they were obtained, are presented in detail
in Chapters 2 to 5 of this dissertation. Highlights are:
(1) A chloride budget for the TCMA watershed based on data from 2000 to 2008
revealed that of the 142,000 metric tonnes (t) of chloride applied annually in the TCMA
as road salt, only 23% (33,000 t) were exported through the Mississippi River and
109,000 t or 77% were retained in the TCMA watershed. Chloride budgets for 10 sub-
watersheds within the TCMA, analyzed in a similar way, gave an average retention rate
of 72% for road salt.
(2) The salt imported in the TCMA but not exported by the Mississippi River has to
be accumulating in the area soil, lakes and groundwater. Evidence of chloride retention
is widespread in the TCMA. Four streams in the TCMA are on the MPCAs 2008 list
of chloride-impaired surface waters. Salinity cycles have been observed in TCMA lakes
with high concentrations in the winterand spring followed by lower concentrations in the
summer and fall. Mean annual concentrations in 38 lakes in the TCMA have been rising
18
on average 1.4 mg/L per year over a 22-year period with current median concentrations
in the surface waters at 87 mg/L. This trend matched a similar trend in the amount of
rock salt the state of Minnesota has purchased over the same time period.
(3) The saline water input is changing the natural mixing behavior of some TCMA
lakes. In some lakes monomictic behavior has occurred with full turnover only happening
in the fall. The presence of a saline layer at the bottom of the lake inhibits dissolved
oxygen from reaching the deep lake sediments in the spring extending the anoxic period
of this water layer by several months. Simulations conducted without the presence of
a saline layer showed two turnover events (dimictic behavior) and oxygenation of lake
sediments in spring and fall.
(4) A few TCMA lakes will reach average chloride levels in violation of current
state standards for chronic exposure if current road salt application rates are continued.
Lakes in the TCMA can recover from current salinity levels in periods of 10 to 30
years if road salt applications are stopped completely. Groundwater, especially deep
groundwater will recover much more slowly, and may take hundreds and thousands of
years to recover.
(5) Chloride retention in urban areas where road salt (NaCl) is applied should cause
concern. Mitigation measures, best management practices (BMPs) for road salt appli-
cation and alternatives to NaCl need to be examined. If no changes are made some area
lakes and groundwater wells would be expected in the foreseeable future to exceed the
current water quality standards set by the USEPA.
Chapter 2
Chloride ion transport and mass
balance in a metropolitan area
using road salt
Eric V. Novotny, Andrew R. Sander, Omid Mohseni, and Heinz G. Stefan
St. Anthony Falls Laboratory,
Department of Civil Engineering, University of Minnesota
Minneapolis, Minnesota 55414
c© 2009 by AGU.org
19
20
2.1 Abstract
In the Twin Cities metropolitan area (TCMA) of Minneapolis/St.Paul, Minnesota, USA,
an estimated 317,000 metric tonnes (t) of road salt were used annually for road de-icing
between 2000 and 2005. To determine the annual retention of road salt, a chloride
budget was conducted for a 4150 km2 watershed encompassing the populated areas of
the TCMA. In addition to inflows and outflows in the major rivers of the TCMA, mul-
tiple sources of chloride were examined, but only road salt and wastewater treatment
plant (WWTP) effluents were large enough to be included in the analysis. Accord-
ing to the chloride budget 235,000 t of chloride entered the TCMA annually with the
Mississippi and Minnesota Rivers, and 355,000 t exited through the Mississippi River.
Of the 120,000 t of chloride added annually to the rivers inside the TCMA watershed
boundaries, 87,000 t came from WWTPs and 33,000 t came from road salt. Of the
142,000 t of chloride applied annually in the TCMA watershed as road salt (241,000 t
NaCl), only 23% (33,000 t) were exported through the Mississippi River and 109,000 t
or 77% were retained in the TCMA watershed. Chloride budgets for 10 sub-watersheds
within the TCMA analyzed in a similar way, gave an average chloride retention rate of
72%. The retention is occurring in the soils, surface waters (numerous lakes, wetlands
and ponds) and in the groundwater. Chloride concentrations in many of these urban
water bodies are now considerably higher than the pre-settlement background levels of
less than 3 mg/L with concentrations as high as 2000 mg/L in shallow groundwater
wells. The continued accumulation of chloride in the groundwater and surface waters is
a cause for concern.
21
2.2 Introduction
It has been reported that 21 million metric tonnes (t) of road salt were used in the United
States in 2005 to improve driving safety in the winter [2]. In the seven county Twin
Cities metropolitan area (TCMA) of Minneapolis/St.Paul, Minnesota, an estimated
317,000 t of road salt were used annually for road de-icing between 2000 and 2005 [60].
Road salt (mostly NaCl) is highly soluble in water resulting in the sodium and chloride
ions dissociating from one another when snowmelt occurs. Chloride and sodium ions are
both transported from roads to receiving waters along three pathways: 1) a rapid runoff
pathway from impervious surfaces, 2) a shallow subsurface pathway through the soil, and
3) a deeper and slower pathway through underground aquifers [4]. All three pathways
can result in the retention of sodium and chloride in the surface water and groundwater
of a watershed [61]. In addition to the accumulation that can occur in the surficial and
deep groundwater aquifers, small amounts of chloride and more so sodium could also
be retained through interactions with soils and organic matter [40, 62, 50, 63]. The
major factors influencing retention in soils and groundwater include soil permeability,
vegetation cover, topography, and roadside drainage techniques [64].
The accumulation of sodium and chloride ions in the environment degrades the wa-
ter quality in a watershed [64, 6, 61]. Increased chloride concentrations decrease the
biodiversity of waterways and roadside vegetation [6]. If chloride reaches the groundwa-
ter it can contaminate drinking water supplies [65]. Not only has chloride been shown
to affect organism, it can also increase the transport and bioavailability of heavy metals
such as cadmium, lead, chromium, copper and even mercury in the environment, which
are also harmful to biota [4]. Other secondary consequences of road salt applications
in lakes include the ability to inhibit or delay natural mixing events limiting the oxy-
genation of benthic waters and sediments and facilitating the release of heavy metals,
mercury and phosphorus stored in the sediments [64].
Elevated and/or increasing chloride concentrations attributable to road salt applica-
tions are present in groundwater and surface waters in urban environments in northern
climate regions[66, 67, 68, 69, 22, 23, 70, 38, 1, 71, 5]. Mass balance studies on in-
dividual streams with watershed areas less than 450 km2 indicate that between 27%
and 65% of the road salt applied was retained within the individual urban watersheds
22
[72, 73, 74, 75, 76].
Unlike previous studies, which analyzed small watersheds located in urban environ-
ments, this study examines an entire metropolitan area encompassing a surface area of
4,150 km2 including rural, suburban, and urban communities. By examining an entire
metropolitan area, a better understanding of the total retention and the holistic effect
of road salt applications on groundwater and surface waters can be obtained. This
study also used data collected over an 8-year period. Potential environmental damage
will affect the entire metropolitan area, and policies on road salt applications cannot
be developed by extrapolation from small sub-watersheds. Overall this study draws at-
tention to a developing problem that will affect around 3 Million people in a 4,150-km2
area and provides insight for other major metropolitan areas on the affects of road salt
applications.
The purpose of the study was to examine the spatial and temporal chloride transport
dynamics and to develop a chloride budget for an entire metropolitan area. This analysis
was used to estimate how much of the road salt applied annually is exported from the
watershed by the Mississippi River and how much is retained in the soils, groundwater
and surface waters.
2.3 Methods
2.3.1 Metro area chloride balance
The Minneapolis/St. Paul Twin Cities metropolitan area (TCMA) is an urbanized area
with a population of 2.8 million [77], many watercourses and 950 lakes. Located in the
north central U.S., the TCMA experiences cold climate with an average annual snowfall
of 1420 mm between November and April [78]. The hydrologic drainage system of the
TCMA includes many small streams, lakes and wetlands along with an extensive storm
sewer systems and hundreds of detention and infiltration basins. Under the TCMA
is a system of several aquifers, some of which are used for urban water supply. Two
major rivers, the Minnesota and the Mississippi, flow through the TCMA. The combined
watersheds of these two rivers encompass 4,150 km2 of the seven-county metropolitan
area, and provide the natural boundaries for a control volume to be used in a chloride
mass balance (Figure 2.1).
23
Figure 1: Watershed boundaries (bold gray lines) of the Twin Cities metropolitan area and major
rivers (Mississippi, Minnesota and St. Croix). Numbers label each of the data collection or
sampling points listed in Table 1. Data from unlabeled chloride sampling points were not used in
the budget analysis, but to plot Figure 2.
Figure 2.1: Watershed boundaries (bold gray lines) of the Twin Cities metropolitanarea and major rivers (Mississippi, Minnesota and St. Croix). Numbers identify each ofthe data collection or sampling points listed in Table 2.1. Data from unlabeled chloridesampling points were used in Figure 2.2, but not used in the budget analysis
24
Table 2.1: Names of sampling points and data collection organizations for flow ratesand chloride concentrations used in the budget analysis. Locations are shown in Figure2.1.Number Name Organization
1 05330000 Minnesota River at Jordan U.S. Geological Survey2 05288500 Mississippi River at Anoka U.S. Geological Survey3 05331000 Mississippi River at St. Paul U.S. Geological Survey4 Upper Mississippi River Mile 871.6 Metropolitan Council5 Minnesota River Mile 39.6 Metropolitan Council6 Upper Mississippi River Mile 815.6 Metropolitan Council7 Blue Lake WWTP Metropolitan Council8 Seneca WWTP Metropolitan Council9 Metro WWTP Metropolitan Council10 Eagle Point WWTP Metropolitan Council
The chloride ion, known to be harmful to biota [64, 61] and more conservative in
water than sodium [40, 62, 50, 63], was chosen to develop an annual chloride mass
balance (Eq. 2.1) for the TCMA control volume.
I +Mp +Mnp −O = S(t/yr), (2.1)
Where I is the total annual inflow (t/yr) through the Mississippi River at Anoka and
the Minnesota River at Jordan, Mp and Mnp represent the total annual mass of chloride
added inside the watershed from point sources and non-point sources respectively, O is
the total annual mass of chloride exported through the Mississippi River at Hastings
and S is the annual retention of chloride (t/yr) in the TCMA. Chloride is highly soluble
in water, and has been treated as conservative once it is in solution.
Once the water reaches the Minnesota or Mississippi Rivers storage potential is
limited. It is expected that the mass of chloride entering the TCMA at the inflow
stations will exit at the outflow stations. Likewise, all of the chlorides discharged directly
to the rivers through point sources are expected to reach the outflow station. However,
the hydrological transport from nonpoint sources of chloride is unknown. Non point
sources of chloride can infiltrate into soils, can accumulate in wetlands or lakes, can
travel through storm sewers or can reach the groundwater. Only some of the salt
applied as a non-point source in the TCMA is expected to reach the Mississippi River.
Therefore, chloride can only be retained in the watershed if it comes from a non-point
25
source. This assumption allows for the rearrangement of Eq. 2.1 to (Eq. 2.2).
O − I −Mp = mnp(t/yr) (2.2)
Where mnp = Mnp S. We first calulated mnp and then S knowing Mnp. The value of
mnp represents the amount of chloride from non-point sources that entered the river
system and was flushed out of the watershed system at the Mississippi River outflow
station.
2.3.2 Inflows and outflows
Sodium and chloride concentrations as well as river flow rates were measured by state
and federal agencies at gauges and sampling points on the Mississippi and the Min-
nesota Rivers (Figure 2.1). The Metropolitan Council Environmental Services (MCES)
collected grab samples for chemical analyses at six locations along the Mississippi River
and two locations on the Minnesota River two to five times per month between January
2000 and December 2007. For the same time period, daily average, and monthly average
flow rates were obtained from the United States Geological Survey (USGS).
The watershed area upstream from the grab sampling station at Anoka is 48,900 km2,
while the watershed area upstream from the USGS stream gauging station is 49,500 km2,
a difference of only 1.2%. Therefore, the flow rates and the grab sample concentrations
were used together without adjustment. The USGS St. Paul gauging station is located
38 km upstream from the outflow grab sample location at Hastings. The watershed
areas for these two locations are 95,300 km2 and 95,900 km2 respectively, or a difference
of 0.6%. The only major inflow between these two points is the Metro wastewater
treatment plant (WWTP). The river outflow rate from the TCMA was therefore taken
to be the flow rate at St. Paul plus the outflow from the Metro WWTP. Using the daily
flow data and grab sample concentrations from 2000 to 2007, flow weighted monthly
average chloride concentrations were calculated. Each of these concentrations (mg/L)
were multiplied by the associated mean monthly flow rate (m3/s) to estimate the mean
monthly chloride mass transport rate (t/yr).
26
2.3.3 Chloride sources
Sodium and chloride sources include natural weathering of minerals, natural deposition
from rainfall, processing of agricultural products, industrial production of chemicals
and food, processing in the metal-, paper-, petroleum-, textile-, and dying-industries,
household uses, water softening, and road salt applications of NaCl [79]. Point sources
of chloride in the watershed include WWTP effluents and industrial discharges to the
Mississippi or Minnesota Rivers. Most industrial sources of chloride are connected to
the WWTPs and are included in the point-source discharges from the WWTPs. Non-
point sources of chloride are natural sources (atmospheric deposition, weathering), rural
household septic systems, fertilizer applications, and snowmelt runoff containing road
salt.
Point sources: Wastewater treatment plants (WWTPs). Effluents from
WWTPs are a significant source of chloride from domestic (foods and water softening)
and industrial NaCl uses. Chloride concentrations in effluent grab samples were mea-
sured by the Metropolitan Council (MCES) from June 2007 to June 2008 in two-week
intervals at the four major wastewater treatment plants within the TCMA watershed.
Locations of the WWTPs are shown in Figure 1. The annual average chloride con-
centrations and the annual average flow rates determined from daily WWTP effluent
flow data were used to determine the mean annual rates (t/yr) of chloride input to
the rivers from the four WWTPs. The majority of industries and 2.4 million of the
2.8 million people living in the TCMA contribute wastewater through sanitary sew-
ers to the four-wastewater treatment plants discharging within the boundaries of the
TCMA watershed. The majority of the other 400,000 people are either located outside
the boundaries of the watershed or contribute to one of the three other wastewater
treatment plants that do not discharge within the control volume. Combined sewers in
the TCMA have been reduced to a minimum. Therefore, all household and industrial
sources of chloride within the control volume boundaries in the TCMA are included in
the effluent values from the four major wastewater treatment plants.
Non-point sources: Natural sources. Natural sources of chloride and sodium,
in general, include mineral salt deposits, weathering of geological formations, and wet
deposition from ocean evaporation[3]. Mineral salt deposits and geological sources of
chloride are negligible in the TCMA. The annual average concentration of chloride in
27
rainwater was measured at a site in the northern part of the TCMA from 2000 to 2007
to be 0.07 mg/L [80]. This value combined with an annual average rainfall of 747 mm
was used to estimate natural source loads of chloride.
Septic systems of rural households. In 1997 around 70,000 households in the 7
county TCMA were using a septic system [81]. Of those 70,000 household around 60%
were located outside of the watershed boundaries. This population estimation was used
to determined chloride loads from private septic systems.
Agricultural sources of chloride. Farming in the outskirts of the TCMA is lim-
ited to 19% (77,000 ha) of the total watershed area. This percentage was calculated
using land use data from 2005 provided by the Metropolitan Council. For the produc-
tion of corn 36 kg/ha of potassium chloride are required according to the Minnesota
Department of Agriculture [82] A value of 49.9 kg/ha per year was used in a study of
fertilizer and manure contributions to streams in Sweden [5].
Road salt. The total mass of road salt (NaCl) applied annually (2000 to 2005 aver-
age) to roads and parking lots within the seven-county TCMA by government agencies
and commercial/private users was estimated to be 317,000 t/yr [60]. 241,000 or 76%
came from public applications (i.e. city, county and state agencies), the other 24% or
76,000 t was estimated to come from commercial/private applications. The commercial
percentage provided by the American Salt Institute for the years 2005 and 2006 was
based on market share information for road salt purchases. Commercial/private appli-
cations were determined to be the amount of bulk salt purchased by non-government
agencies plus the amount of package deicing salt purchased by both homeowners and
commercial applicators.
The TCMA watershed boundaries do not coincide with the political TCMA bound-
aries (Figure 2.1). For that reason the amount of road salt applied within the political
seven county TCMA had to be adjusted using road kilometers. City, county and state
road data were obtained from the GIS database of the Metropolitan Council. Road
lengths were divided by government entity into total kilometers of city roads for each
city, of county roads for each county and state road. Fractions (percent) of road lengths
inside the watershed vs. the total length inside a municipality, county, or state jurisdic-
tion were multiplied by the total mass of road salt applied by each individual agency
to estimate the total mass of salt applied in the watershed. The total mass of road salt
28
applied by private and commercial uses on parking lots, sidewalks etc. was added to the
public road salt applications by using a value equal to 24% of the total salt applications.
2.3.4 Chloride balances in sub-watersheds
The chloride budget study for the entire TCMA was supplemented by a chloride budget
study for 10 sub-watersheds of small streams located entirely within the TCMA. This
study was done to determine if salt retention rates obtained at a geographic scale of less
than on tenth the TCMA were comparable to those obtained for the entire TCMA.
The analysis of the sub-watersheds was based on Eq. 2.1. The inflow (I) for the
sub-watersheds was based on the estimated chloride concentration in the streams that
would be expected if road salts were not applied in the watershed. This value is different
from the overall TCMA study and was defined as the background concentration in the
stream. The background concentration was estimated from a linear relationship between
the annual average chloride concentrations in the streams vs. the mass of chloride from
road salt applied per ha per year within the watersheds. The background concentration
was found by extrapolating the linear relationship to a chloride application rate of zero.
The background concentration was multiplied by the annual average discharge (flow)
from the watershed to obtain the inflow loading (I).
The only internal chloride source (M) in the watershed was from road salt appli-
cations. No WWTP effluents or other chloride sources besides road salts were being
applied in the sub-watersheds. The mass of road salt applied to the roads was deter-
mined using the methods described for the TCMA watershed analysis explained above.
The percentage of the watershed covered by impervious surfaces and the total watershed
areas were found using GIS data from the University of Minnesota Remote Sensing and
Geospatial Analysis Laboratory (http://land.umn.edu/index.html).
To calculate the annual export rate of chloride mass (O) exiting each sub-watershed,
daily average flow data and grab sample data, collected by the Metropolitan Council
Environmental Services (MCES) two to five times per month between 1/1/2000 and
12/31/2007, at the outflow from each sub-watershed were used.
29
2.4 Results and Discussion
2.4.1 Inflows and outflows of chloride in the major rivers
The hydrologic transport of sodium and chloride in the TCMA was inferred from the
concentrations in its major rivers. Average annual concentrations measured in these
rivers show significant changes with distance through the TCMA (Figure 2.2). Increased
Na+ and Cl− concentrations in the Mississippi River were most pronounced downstream
from the confluence with the Minnesota River and the Metro WWTP where mean annual
chloride concentrations increased from 16 mg/L to 33 mg/L. The Minnesota River
arrived in the TCMA with higher concentrations than the Mississippi River. Discharges
into the Minnesota River include effluents from the Blue Lake and the Seneca WWTPs
as well as surface runoff from populated areas, resulting in a mean annual chloride
concentration increase from 30 mg/L to 42 mg/L. The St. Croix River is outside the
TCMA and carries much lower chloride concentrations ( 5 mg/L) because the watershed
is largely undeveloped. Inflow from the St. Croix River caused a decrease in chloride
concentrations in the Mississippi River downstream from the TCMA. In all three rivers
sodium and chloride follow similar concentration distributions with distance.
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Figure 2: Median chloride concentrations (2000-2008) of sodium and chloride in grab samples (2000-2007)
from the two major rivers of the Twin Cities Metropolitan Area. Arrows denote locations of WWTP
discharges or river junctions. Figure 2.2: Median concentrations of sodium and chloride in grab samples (2000-2007)from the two major rivers of the Twin Cities Metropolitan Area. Arrows denote loca-tions of WWTP discharges or river junctions.
Where the Mississippi enters the TCMA at Anoka mean monthly flow weighted
chloride concentrations were between 15 and 20 mg/L (Figure 2.3). Individual grab
30
samples showed only small variations for a particular month with the exception of Jan-
uary, February and November. In the Minnesota River inflow to the TCMA at Jordan,
mean monthly chloride concentrations ranged from 20 to 40mg/L (Figure 2.3). Flow
weighted mean monthly concentrations were highest between December and February
and lowest from March to August. Variability between individual grab samples for a
given month were highest in February.
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Figure 3: Flow-weighted average monthly chloride concentrations and flow rates at the inflow and
outflow of major rivers in the TCMA watershed (2000 - 2007). Figure 2.3: Flow-weighted average monthly chloride concentrations and flow rates atthe inflow and outflow of the major rivers in the TCMA watershed (2000 - 2007).
At the Mississippi River outflow station in Hastings mean monthly concentrations
ranged between 20 and 50 mg/L with a strong seasonal variation (Figure 2.3). The
high concentrations occurred between January and March, and the lows between April
to July. Individual grab sample concentrations varied the most in March, and the least
in June.
Estimates were made for the total mass of chloride passing through the inflow and
31
outflow observation points in Figure 2.3 for every month. The annual mass (rates)
of chloride entering the TCMA by the Minnesota and Mississippi River inflows were
determined to be 119,000 and 116,000 t/yr, respectively. The mass (rate) of chloride
flowing out of the TCMA watershed with the Mississippi River was found to be 355,000
t/yr. Roughly 50% more chloride was found to be exiting the watershed than what was
entering with the Mississippi and Minnesota Rivers combined.
2.4.2 Metro area chloride sources
Point sources: The only point source of chloride in the TCMA is the wastewater
discharged from four wastewater treatment plants 2.4. Effluent chloride concentrations
increased during the winter months at the Metro WWTP. Domestic and industrial
waste loads to the wastewater treatment system were expected to remain fairly con-
stant throughout the year, as was shown for the other three WWTPs. Therefore, the
increase at Metro during the winter was attributed to the addition of road salt to the
system through car washes, a small number of combined sewers and possible seepage
into the sanitary sewer system. To avoid double counting road salt inputs, the average
Cl− concentration between June and November was used for the entire year in the an-
nual chloride budget. Although the other three WWTPs did not display a significant
concentration increase in winter, the same procedure was used for consistency. The
(June 2007-Nov 2007) average chloride concentrations in the WWTP effluents and the
annual average effluent flow rates are shown in Table 2.2. The associated mass (rate)
of chloride entering the river system from the four WWTPs, including domestic and in-
dustrial wastewater, but excluding chloride from road salt applications, was estimated
to be 87,000 t/yr.
Non-point sources: Non-point chloride loads from natural sources, septic systems,
agricultural sources and road salt were evaluated. Using recorded rainfall amounts
and measured concentrations of chloride in precipitation in the TCMA, the chloride
contribution from natural sources was estimated to be around 220 t/yr.
The majority of people within the TCMA watershed boundaries are connected to one
of 7 WWTPs by sanitary sewers and a majority of the households using a private septic
system are located outside the watershed boundaries. If as many as 60,000 people,
i.e. the number of people connected to the Eagle Point WWTP, were using septic
32
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Figure 4: Chloride concentrations from grab samples from the effluents
of the four WWTPs. Dates are MM/DD/YY. Figure 2.4: Grab sample chloride concentrations from the effluents of the four WWTPs.Dates are MM/DD/YY.
Table 2.2: Estimates of average chloride concentrations, flow rates and total mass of Cl-in effluents from major WWTPs in the TCMA each year. Average chloride concentra-tions are flow weighted and for the period June 2006 to June 2007 excluding the wintermonths. Average flow rates are from 2000 to 2007.Name of WWTP Chloride (mg/L) Flow (m3/s) Mass (t/yr)Metro 227 8.63 62000Blue Lake 387 1.18 14000Seneca 280 1.01 9000Eagle Point 348 0.18 2000Total 11.00 87000
33
systems within watershed boundaries the 2000 t of chloride discharged annually from
this WWTP would be a reasonable estimate of chloride releases from septic tanks (Table
2.2). For agricultural loads, using a value of 49.9 kg/ha of chloride from fertilizer and
manure results in only 3,800 t of chloride added to the watershed. If all of the designated
agricultural land were instead only used to grow corn this value would only be 2,800
t/yr of chloride.
The largest non-point source of chloride in the TCMA was road salt. It was deter-
mined that 241,000 t of the 317,000 t of road salt applied annually in the seven county
metropolitan area was applied within the watershed boundaries shown in Figure 2.1.
This translates to a non-point source input of 142,000 t/yr of chloride from road salt
applications. It was determined that natural deposition, agricultural inputs and septic
sewer systems would only contribute an additional 1-3%, depending on the calcula-
tion method, to the total chloride load (from point and non-point sources). Therefore
the loads from these sources were neglected, leaving road salt applications as the only
significant non-point source of chloride within the watersheds boundaries.
2.4.3 Metro area chloride balance calculation
The individual chloride balance components (Mississippi River inflow, Minnesota River
inflow, Mississippi River outflow, road salt application, WWTP effluents) presented in
the previous sections were combined in a chloride mass balance using equation (2.1) on
a monthly timescale.
Mean monthly mass fluxes (t/month) of chloride entering or exiting the TCMA wa-
tershed from the two major rivers and the four WWTPs are illustrated in Figure 2.5A.
Dashed lines in Figure 2.5A give cumulative contributions by month from WWTP efflu-
ents, the Minnesota River and the Mississippi River, up to the total Inflow + WWTP
curve. The Outflow curve is from the Mississippi River outflow station in Hastings. Fig-
ure 2.5A is a graphical representation of Equation 2.2, showing the difference between
the mass of chloride exiting the watershed (O) and the sum of the amount entering the
watershed (I) and the amount added by point sources (Mp). Figure 2.5B represents the
amount of chloride added to the river system from non-point sources (mnp in Eq 2.2.).
Since road salt is the only significant non-point source of chloride inside the watershed
Figure 2.5B also represents the monthly mass of chloride from road salt applications
34
exported by the Mississippi River from the TCMA watershed. The monthly non-point
source chloride contribution to the Mississippi River outflow was highest (Figure 2.5B)
during the winter months when road salt was being applied to the roads. The high De-
cember to April values can be interpreted as the direct impact of road salt applications
and snowmelt water runoff through systems of storm sewers and small streams to the
big rivers. Delays occur because winter is a low flow season, and only when snowmelt
sets in does the routing processes accelerate. The small contributions in late summer
can be attributed to the flushing of chloride from lakes and wetlands [71] or to delayed
transport to the rivers through interflow or groundwater flow [4].
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Figure 5: (A) Monthly rates (mass) of chloride fluxes (t/yr) from point sources entering or exiting the Twin cities metropolitan
area watershed. Shaded areas between dashed lines give monthly contributions from four wastewater treatment plant (WWTP)
effluents, the Minnesota River and the Mississippi. Values are additive up to the total "Inflow + WWTP" curve. The
"Outflow" curve is from the Mississippi River outflow station in Hastings, downstream from the Twin Cities metropolitan
area. (B) Monthly differences between the “Outflow” and the “Inflow + WWTP” (solid lines) from panel A. Panel B gives the
algebraic sum of monthly inflow, outflow and point source loads of chloride to the river. By virtue of the mass balance in Eq.
(1) the plotted values also give the monthly amounts of non-point source chloride exported by the river as well as the
uncertainties in the mass balance.
Figure 2.5: (A) Monthly chloride fluxes (t/yr) from point sources entering or exitingthe Twin Cities metropolitan area watershed. Shaded areas between dashed lines givemonthly contributions from four WWTP effluents, the Minnesota River and the Mis-sissippi. Values are additive up to the total ”Inflow + WWTP” curve. The ”Outflow”curve is from the Mississippi River outflow station in Hastings, downstream from theTwin Cities metropolitan area. (B) Monthly differences between the Outflow and theInflow + WWTP (solid lines) from panel A. By virtue of the mass balance in Eq.(2.2)the plotted values give the monthly amounts of non-point source chloride exported bythe river as well as the uncertainties in the mass balance.
In March the difference between the mass of chloride exported and the mass im-
ported had a maximum. Road salt applied in the TCMA watershed accounted for
34% of the chloride passing the Mississippi River outflow station in March, WWTPs
contributed 19%, and the inflows from the Mississippi and Minnesota Rivers into the
TCMA watershed provided 47% (Figure 2.5A). The total amount of chloride exported
from the system during this month was 13,000 t (Figure 2.5B). By adding the values
35
for all months in Figure 2.5B, the annual mass of chloride from road salt exiting the
control volume (the TCMA watershed) was found to be 33,000 t/yr. It had previously
been estimated that 142,000 t of chloride/yr were applied as road salt to the TCMA
watershed area. If 33,000 of the 142,000 t were carried away by the Mississippi then
109,000 t or 77% of the chloride applied annually had to stay behind in the TCMA
watershed system (S in Eqs 2.1 and 2.2).
2.4.4 Sub-watershed chloride balance calculation
The average annual chloride concentrations in the 10 small streams within the larger
TCMA watershed ranged from 37 mg/L in Carver Creek to 185 mg/L in Shingle Creek;
annual average flow rates were from 0.093 m3/s in Riley Creek to 1.685 m3/s in Min-
nehaha Creek (Table 2.3). The total watershed area, the percentage covered by imper-
vious surfaces and the mass of road salt applied annually were also determined (Table
2.3). Chloride application rates in the 10 sub-watershed ranged from 0.08 to 0.82 t/ha
per year.
36T
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000
0.65
2,60
063
Tot
al45
,300
12,5
0072
37
A background concentration of 18.6 mg/L (+/- 34.9 mg/L at the 95% confidence
interval) was determined using a linear regression analysis between annual average Cl-
concentrations in the stream (mg/L) and total Cl- applied (t/yr) per watershed area
(Figure 2.6; R2 = 0.79). The background concentration of 18.6 mg/L matched with
concentrations in the Mississippi River before it entered the TCMA. Retention of chlo-
ride in each individual sub-watershed was calculated to be from 55% to 83% (Table 2.3).
The total combined mass of chloride applied in the 10 sub- watersheds was 45,300 t/yr,
which represents 32% of the amount applied in the entire TCMA watershed. The total
amount of chloride exported from the 10 sub-watersheds was estimated at 12,500 t/yr.
This means that only 28% of the salt applied was exported from the 10 sub-watersheds
each year, and therefore 72% was retained. Due to the large confidence interval around
the background concentrations an analysis was conducted by setting the background
concentration to 0 mg/L. This represents a scenario where all of the chloride exiting the
watershed in a given year is from road salt applications during that year. This analysis
resulted in the lowest possible retention rate. If the background concentration was set
to 0 mg/L the amount of road salt exiting the watershed would be raised to 15,900 t/yr
reducing the retention rate to 65%. The retention estimates of 72% and 65% are lower
than the 77% value obtained for the entire TCMA watershed, but comparable.
!"#"$%&'(%)"*"$+',,+"
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012345"6375388192"
:.;"<92=1>32<3"12?35@4A"
B17C53",D"EA9?"9="4@35473"422C4A"<FA951>3"<92<32?54?1928"@8"4G9C2?"9="<FA951>3""
4HHA13>"H35"I4?358F34>"4534"=95"?F3"$&"8CJI4?358F3>"8?534G8'""K2?35<3H?"I48"
C83>"48"J4<L759C2>"<92<32?54?192"12"?F3"8C>I4?358F3>"JC>73?"424A!818'"Figure 2.6: Average annual chloride concentrations vs amount of chloride applied perwatershed area for the 10 sub-watershed streams. Intercept was used as backgroundconcentration in the sub-watershed chloride budget analysis
38
2.4.5 Sodium retention
The retention of chloride from road salt applications in a watershed encompassing the
Twin Cities metropolitan area was determined to be around 77%. While an analysis was
not conducted on the other ion in rock salt, sodium, due to its slightly less conservative
behavior a value equal to or higher than 77% would be expected. Sodium interacts
more readily with soils through ion exchange allowing for the possibility that higher
amounts could be stored in the soil column [40, 50]. The assessment of chloride (road
salt) retention was made with the best information available, however assumptions,
which had to be made, do influence the results obtained. The sensitivity of the findings
to the assumptions was therefore investigated.
2.4.6 Sensitivity of the results
The assessment of chloride (road salt) retention was made with the best information
available, however assumptions, which had to be made, do influence the results ob-
tained. The sensitivity of the findings to three assumptions and procedures used was
therefore investigated: the sampling frequency of the grab samples at the inflow and
outflow stations, the method of calculations for chloride exported from the watershed,
and the estimations method for the non-point sources of chloride.
Sampling Frequency
An analysis was conducted to determine if continuous monitoring or more frequent
sampling was needed to capture chloride concentrations in snowmelt events of short
duration at the inflow and outflow stations on the Mississippi and Minnesota Rivers
[75]. To test the sensitivity to sampling frequency, records of daily average specific
conductance in the Mississippi River near Hastings (outflow station) were used from a
continuous monitoring station maintained by the Metropolitan Council (Figure 2.7A).
Although a direct relationship between chloride and specific conductance could not be
obtained, due to the dampening of the chloride signal in relation to other ions from the
high flow rates, snowmelt events could be clearly detected by fluctuations in specific
conductance during the winter. A Comparison was conducted between the continuous
time series of daily specific conductance values and the specific conductance and chloride
39
values recorded on the grab sample dates. This analysis provided evidence that a suit-
able representation of the chloride dynamics was obtained with the biweekly sampling
frequency used (Figure 2.7A). Furthermore, the cumulative distributions of specific con-
ductance values obtained from the continuous daily time series and the values on the
days when chloride grab samples were taken were virtually identical (Figure 2.7B). It
was concluded that the sampling frequency used was adequate to estimate the annual
load of Cl- (salt) exiting or entering the TCMA watershed over the study period.
10
20
30
40
50
60
70
80
90
100
110
120
130
140
150
160
170
0
100
200
300
400
500
600
700
800
900
1/1/00 1/1/01 1/1/02 1/1/03 1/1/04 1/1/05 1/1/06 1/1/07
Ch
lorid
e (
mg
/L) Sp
ecific
Co
nd
ucta
nce
(µ
s/c
m) !" #"
!"#$%&'()'*+,'-."/0'.1&%.#&2'34'25&6"4"6'6378$69.76&'4%3:';<=:"7$9&'6379"7$3$2':37"93%"7#'*23/"8'/"7&,>'-.02'?@&7'6@/3%"8&'#%.A'2.:5/&2'?&%&'
9.B&7'.%&':.%B&8'A0'''''*935,>''C@/3%"8&'6376&79%.9"372'4%3:'#%.A'2.:5/&2'A0'''''*A3993:,>'-.9.'.%&'4%3:'9@&'D"22"22"55"'E"1&%'3$94/3?'29.9"37'"7'
F.29"7#2>'*G,'C$:$/.9"1&'73%:./"H&8'8"29%"A$9"37'4$769"372'34'8."/0'25&6"4"6'6378$69.76&'1./$&2>'I@&'23/"8'/"7&'%&5%&2&792'9@&'25&6"4"6'
6378$69.76&'1./$&2'37/0'43%'8.02'?@&7'.'6@/3%"8&'#%.A'2.:5/&'?.2'9.B&7>'I@&'8.2@&8'/"7&'$2&2'.//'8."/0'1./$&2'2@3?7'"7'+>'Figure 2.7: (A) Daily averages of specific conductance from 15-minute continuous mon-itoring (solid line). Days when chloride grab samples were taken (top). Chloride con-centrations from grab samples (bottom). Data are from the Mississippi River outflowstation in Hastings. (B) Cumulative normalized distribution functions of daily specificconductance values. Specific conductance values only for days when a chloride grabsample was taken (solid line) and all daily values shown from panel A (dashed line).
Chloride export
Other pathways of chloride export such as airborne transport of salt particles or chlori-
nation of natural organic matter were not analyzed. Salt particles can become airborne
behind vehicles and during strong winds, however they are typically deposited within
100 m of the road [83]. Cl- has also been found to interact with natural organic matter
forming chlorinated organic matter when transported through soils [84]. It is therefore
possible that some of the Cl− from road salt applied in the TCMA was exported in the
Mississippi River while attached to organic matter and is thus not accounted for. Our
40
budget analysis did not include airborne or organic matter transport mechanisms. If
incorrect, this assumption would cause an overestimation of chloride retention in the
watershed. If as much as 10% of the road salt applied in the TCMA were exported
by alternative and not included transport mechanisms, the total export would rise to
47,800 t/yr from 33,000 t/yr, and the road salt retention estimate for the TCMA would
be lowered to 64%.
Non-point chloride sources in the TCMA
Only road salt was considered as a significant non-point source of chloride in the water-
shed. Others sources, such as natural deposition, septic tank seepage from residences
not connected to a WWTP or fertilizer applications, were assumed negligible. If an
additional 3% (4,500 t) of chloride were added to the system by outside processes, the
estimated Cl- retention in the watershed would increase slightly.
The 24% commercial road salt application rate was taken from market share infor-
mation provided by the American Salt Institute for the entire United States. While
this value is based on national statistics it is the best estimate for a large metropolitan
area for a number of reasons. The diversity in area including suburban, urban and rural
land uses and the size of the watershed studied allow for a comparison with the national
scale. National trends in municipal salt purchases match Minnesota trends in rock salt
purchases [60]. Finally, obtaining information from commercial road salt appliers and
estimating application rates or areas where road salt was applied commercially is very
difficult. The results from this analysis would likely include more error than accurate
national sales data. If the 24% commercial road salt application rate were lowered to
10%, a value reported in a Canadian study[6], the chloride contribution from road salt
applications would be reduced to 122,000 t/yr, the water-borne export rate from the
TCMA would be raised to 27%, and the retention rate in the watershed would only
drop to 73%.
If all effects reducing the retention rate were combined (commercial application
rate reduced from 24 to 10% of total application rate; increased export of 10% of the
applied amount) the application rate would be lowered to 122,000 t/yr, and the export
rate would be raised to 33,000 + 12,200 = 45,200 t/yr. The total export rate would
then be 37% and the retention rate 63%. In other words, even with extremely favorable
41
assumptions for road salt flushing from the TCMA the estimated retention rate remains
high.
2.4.7 Comparison to other metro areas
Other studies have shown significant retention of chlorides in urban watersheds, but
the estimated retention percentages vary significantly. Most studies were conducted in
small, urbanized watersheds ranging in size from 104 to 435 km2. Retention percentages
were found to be 55% in a stream watershed in the greater Toronto, Canada area [73],
50 - 65% in Helsinki, Finland [75], 28 - 45% in Chicago, Illinois, USA [76], 59% in
Rochester, New York, USA [72] and 35% in Boston, Massachusetts, USA [74].
In Toronto, Ontario, Canada the accumulation of salt in the watershed due to deicing
practices has seriously compromised the shallow aquifers [65]. In Waterloo, Ontario
chloride concentrations in the aquifers had not reached equilibrium after 57 years of
road salt applications. It was estimated that on the order of another 100 years will be
required to reach equilibrium concentrations under current conditions [85]. In shallow
aquifers near Chicago, Illinois, chloride concentrations have increased since 1960. 24%
of the wells studied in the 1990s had concentrations above 100 mg/L, when median
values before 1960 were less than 10 mg/L, and 15% of the wells had rate increases
greater than 4 mg/L per year [70]. The accumulation of salt in shallow groundwater
also affects base flow concentrations in streams [1]. Baseline salinity in urban streams
and streams near roadways have been increasing in the northeastern part of the United
States [22, 23], in the Greater Toronto Area, Canada [68] and in Sweden[38, 5].
2.4.8 Chloride retention in the TCMA watershed
Evidence of significant chloride retention within the TCMA watershed is provided in
streams lakes and aquifers. Four streams (Minnehaha Creek, Battle Creek, Shingle
Creek and Nine Mile Creek) in the TCMA are on the MPCAs 2008 list of impaired
waters for chloride [20]. Pulses of very high chloride concentrations occur in these and
other small streams of the TCMA during the winter months (Figure 2.8).
Volume-weighted average chloride concentrations in 38 lakes of the TCMA have
increased from 1984 to 2005 by an average of 1.5 mg/L per year (range of 0.1 to 15 mg/L
42
!"
#!!"
$!!"
%!!"
&!!"
'!!!"
'#!!"
'$!!"
#!!#"#!!("#!!$"#!!)"#!!%"#!!*"#!!&"#!!+"
!"#$%&'()*+,-./)
0&1()2&#()!%((3)
!"
#!!"
$!!"
%!!"
&!!"
'!!!"
'#!!"
'$!!"
#!!#"#!!("#!!$"#!!)"#!!%"#!!*"#!!&"#!!+"
!"#$%&'()*+,-./)
4566#()!%((3)
Figure 8: Chloride concentrations in two streams of the Twin Cities metropolitan area from grab
samples obtained by the Metropolitan Council Environmental Services (MCES). Both streams are
on the 2008 list of chloride impaired waters (Minnesota Pollution Control Agency 2008).
Figure 2.8: Chloride concentrations in two streams of the Twin Cities metropolitanarea from grab samples obtained by the Metropolitan Council Environmental Services(MCES). Both streams are on the 2008 list of chloride impaired waters [20].
per year), following a pattern similar to the mass of road salt purchased by the state
of Minnesota over that same time period [71]. Median concentrations, in the surface
waters of the 38 lakes from 2001-2005, of 87 mg/L (range 31 to 505 mg/L) [71] were
much higher than the estimated presettlement concentrations of 3 mg/L [14]. In urban
lakes of the TCMA chloride concentrations tend to fluctuate seasonally, with maximum
in February or March and minimum in October or November. In the long term, a mean
annual equilibrium concentration is reached when all of the chloride added to a lake
during the winter season is flushed out during the summer and fall season. There was
an indication that smaller lakes with high summer flushing rates have already reached
equilibrium, while larger lakes and lakes with low flushing rates can be expected to have
rising mean annual chloride concentrations for years to come. If salt applications were
stopped completely, the recovery of many urban lakes would take from 10 to 30 years
[86].
Chloride concentrations in surficial sand and gravel aquifers throughout the state of
Minnesota vary substantially with land-use. Median chloride values were of 46 mg/L
were found in urban areas, 17 mg/L in agricultural areas, and 1.2 mg/L in forested area
[69]. 3% of the water samples taken from wells in the TCMA were found to exceed
the USEPA secondary chloride standard of 250 mg/L [69]. In a cross section of the
surficial aquifer in a northwestern subburb of Minneapolis, directly down gradient from
a high traffic roadway, chloride concentrations ranged from 200 mg/L at the watertable
3m below the soil surface, to 590 mg/L at a depth of 13.5m below the soil surface
43
1
10
100
1000
10000
0 20 40 60 80 100 120
Chlo
ride (
mg/L
)
Well Depth (m)
2004 2005
Figure 9: Chloride concentration in wells located throughout the
Twin Cities Metropolitan area in 2004 and 2005. Information was
collected by the Minnesota Pollution Control Agency. Figure 2.9: Chloride concentration in wells located throughout the Twin CitiesMetropolitan area in 2004 and 2005. Information was reported by the Minnesota Pol-lution Control Agency.
[67]. Concentrations of 380 470 mg/L were also measured downgradient from a major
Interstate Highway (I-94) in summer and late fall pointing towards a longterm storage
of road salt in the surficial aquifer [67]. Data collected by the Minnesota Pollution
Control Agency (MPCA) throughout the seven-county TCMA showed that the highest
chloride concentrations in groundwater, up to 2000mg/L, were found in shallow wells
(Figure 2.9).
Elevated chloride concentrations in aquifers may be delayed due to storage in the
subsurface [85, 70]. Shallow wells respond first resulting in some to have already reached
concentrations above state standards. The storage potential of the TCMA aquifer sys-
tem is very large. If road salt applications were completely stopped today, chloride
concentrations in deep wells may continue to increases for many years until subsurface
saline transport has reached equilibrium [85, 70]. Residence times in the aquifers can
be high ranging from tens to hundreds of years in the upper and surficial aquifers to
thousands of years in the deep aquifers. Residence times in lakes are smaller, on the
order of 3 to 14 years, but still provide a means of chloride storage [86]. The TCMA has
hundreds of lakes and wetlands, and hundreds of man-made detention and infiltration
44
basins. Policy has been to delay runoff from rainfall and snowmelt, and to increase infil-
tration by routing storm sewers into these systems. Although very useful in stormwater
management, these practices could be adding to the accumulation of road salt in the wa-
tershed by promoting retention of surface runoff and/or infiltration of the contaminated
water into the groundwater.
2.5 Summary and Conclusions
Road salt is used to increase driving safety in the Twin Cities metropolitan area (TCMA)
of Minnesota. A chloride budget for the TCMA watershed (Figure 2.1) with data from
2000 to 2007 revealed the final destinations of the road salt after it was dissolved in the
snowmelt water. The TCMA watershed analyzed covered an area of 4150 km2 with a
population of 2.8 Million. According to the annual chloride budget 235,000 t of chloride
entered the TCMA annually in the Mississippi and Minnesota Rivers, and 355,000 t
exited through the Mississippi River resulting in 120,000 t being added to the Mississippi
and Minnesota Rivers as they traveled through the TCMA. Of the 120,000 t of chloride
added annually 87,000 t came from the four WWTPs (point sources) and 33,000 t came
from road salt (non-point source). Of the 142,000 t of chloride applied annually in the
TCMA as road salt, only 23% (33,000 t) were exported through the Mississippi River
and 109,000 t or 77% were retained in the TCMA watershed. Chloride budgets for 10
sub-watersheds within the TCMA analyzed in a similar way, gave a retention rate of
72% for road salt.
Evidence of chloride retention is widespread in the TCMA. Four streams in the
TCMA are on the MPCAs 2008 list of Cl- impaired waters, 38 lakes in the TCMA
had a rising mean annual Cl- concentration over a 22-year period [71], and elevated
Cl- concentrations in groundwater have been measured [67, 69] Chloride retention in
urban areas where road salt (NaCl) is applied should cause much concern. Mitigation
measures, best management practices (BMPs) for road salt application and alternatives
to NaCl need to be examined.
Aknowledgements
45
We acknowledge and thank the following individuals and institutions: the Minnesota
Local Road Research Board (LRRB) in cooperation with the Minnesota Department of
Transportation (Mn/DOT) and the University of Minnesota for providing the funding
for this research; the Technical Advisory Panel, lead by Wayne Sandberg of Washington
County, for input and suggestions to our research; Karen Jensen of the Metropolitan
Council Environmental Services, the Metropolitan Council (MCES) and the United
States Geological Survey (USGS) for providing data used in this study; numerous indi-
viduals in cities, counties and Mn/DOT for providing data on road salt applications.
Chapter 3
Increase of urban lake salinity by
road deicing salt
Eric V. Novotny, Dan Murphy and Heinz G. Stefan
St. Anthony Falls Laboratory,
Department of Civil Engineering, University of Minnesota
Minneapolis, Minnesota 55414
c© 2008 by Elsevier.com
46
47
3.1 Abstract
Over 317,000 tonnes of road salt (NaCl) are applied annually for road de-icing in the
Twin Cities Metropolitan Area (TCMA) of Minnesota. Although road salt is applied to
increase driving safety, this practice influences environmental water quality. Thirteen
lakes in the TCMA were studied over 46 months to determine if and how they respond
to the seasonal applications of road salt. Sodium and chloride concentrations in these
lakes were 10 and 25 times higher, respectively, than in other non-urban lakes in the
region. Seasonal salinity/chloride cycles in the lakes were correlated with road salt
applications: high concentrations in the winter and spring, especially near the bottom
of the lakes, were followed by lower concentrations in the summer and fall due to flushing
of the lakes by rainfall runoff. The seasonal salt storage/flushing rates for individual
lakes were derived from volume weighted average chloride concentration time series.
The rate ranged from 9 to 55% of a lakes minimum salt content. In some of the lakes
studied salt concentrations were high enough to stop spring turnover preventing oxygen
from reaching the benthic sediments. Concentrations above the sediments were also
high enough to induce convective mixing of the saline water into the sediment pore
water. A regional analysis of historical water quality records of 38 lakes in the TCMA
showed increases in lake salinity from 1984 to 2005 that were highly correlated with
the amount of rock salt purchased by the State of Minnesota. Chloride concentrations
in individual lakes were positively correlated with the percent of impervious surfaces
in the watershed and inversely with lake volume. Taken together, the results show a
continuing degradation of the water quality of urban lakes due to application of NaCl
in their watersheds.
48
3.2 Introduction
In the snow-belt regions of the United States de-icing agents are used to increase driving
safety on public roads in the winter. The primary agent used for this purpose is rock
salt consisting mainly of sodium chloride (NaCl). Its cost is considered moderate, and
storage, handling and dispersing on surfaces are relatively easy [4]. Other agents in
the road salt mixture, such as ferrocyanide, which is used as an anti-clumping agent,
and impurities consisting of trace elements (phosphorus, sulphur, nitrogen, copper and
zinc), can represent up to 5% of the salt weight [1].
In the U.S., annual rock salt use for road de-icing increased from 163,000 tons in
1940 to over 23 million tons in 2005 according to the United States Geological Survey
(USGS) mineral yearbooks [2, 3]. In the state of Minnesota annual rock salt purchases
increased during the same time period from 60,000 tons to over 900,000 tons [2]. Other
deicing agents are available (e.g. calcium or magnesium chloride (CaCl2) or potassium
acetate), but because of a large difference in cost, NaCl is applied most frequently [4].
Road salt applications can keep roads free of ice for safe winter travel; however
this practice comes at a cost to the infrastructure and the environment, especially in
urban areas with high road densities. Much of the rock salt applied to the roads is
dissolved in the melting snow and ice. The salt containing water runs off into streams,
lakes or storm sewers or infiltrates into the soil eventually reaching the groundwater
affecting the chemistry and biota in the soil and water [5]. Organisms in streams and
shallow, small lakes and ponds are particularly vulnerable to road salt application and
chloride pollution [6]. Chloride standards of 860 mg/L for acute events and 230 mg/L
for chronic pollution have been established for surface waters designated as important
for aquatic life and recreation by the Minnesota Pollution Control Agency (MPCA)
Minnesota Rules Chapter 7050 and 7052.
Small streams flowing through urban areas are known to exceed the chronic and
acute chloride levels periodically [23, 19]. If a stream receives snowmelt runoff directly
from roadways treated with salt (NaCl), concentrations of sodium and chloride will
spike during the winter months and spring thaw, and decline quickly once the salt
application has stopped [19]. In the state of Minnesota, data are available showing high
concentrations of chloride traveling through streams and storm sewers during the winter
49
months (Figure 3.1). Four streams (Shingle Creek, Nine Mile Creek, Beavens Creek and
Battle Creek) in the Minneapolis/St. Paul Twin Cities Metropolitan Area (TCMA) have
been designated as impaired waters and placed on the Clean Water Act section 303d
Total Maximum Daily Load (TMDL) list [20] because of salt pollution. Other regions
have shown similar elevated chloride concentrations[22, 4] including the northeastern
United States where chloride concentrations in an urban stream were recorded as high
as 5000 mg/L [23]. In Sweden chloride concentrations in runoff from roadways has also
reached 3500 mg/L in the winter compared to values averaging 15.6 mg/L during the
summer [24].
0200400600800
100012001400
2001 2002 2003 2004 2005 2006 2007 2008 2009
Chl
orid
e (m
g/L)
Figure 3.1: Chloride concentrations in Battle Creek (3.5 km from its outlet into Mis-sissippi River). Battle Creek drains portions of East St. Paul (Metropolitan Councildata).
Streams and storm sewers capturing snowmelt water from roadways are likely to
cause seasonal salinity variations in lakes into which they discharge. Road salt applica-
tions have been shown to increase the salinity in lakes near major roadways of urban
watersheds [14, 5, 59, 51, 56]. Road salt applications in rural areas have been found
to affect lakes several hundred meters away [6]. In urban environments where runoff is
collected in storm sewers, the impact could be felt at much larger distances. The ap-
plication of road salt has been show to cause chemical stratifications in small lakes and
ponds strong enough to prolong or prevent lake mixing [87, 88]. In this study multiple
50
lakes throughout a metropolitan area will be examined to determine regional trends and
how different lakes react to road salt applications.
The Minneapolis/St. Paul Twin Cities Metropolitan area (TCMA) in the state of
Minnesota provides a perfect setting to study how lakes are influenced by road salt
applications. The seven county TCMA is an urbanized area with a population of 2.7
million that contains many watercourses and 950 lakes. Located in the north central
U.S., the TCMA experiences cold climate in the winter with a total annual snowfall of
1.4 meters [78], falling between the months of November to March. Due to these climate
conditions an estimated amount of 350,000 short tons (317,000 tonnes) of road salt/year
is used in the TCMA for winter road maintenance [60]. With an expanding population
and road system, more and more lakes in the TCMA are susceptible to pollution from
storm water and snowmelt runoff. This paper focuses on how road salt applications are
changing lake water quality; it has five objectives: 1) develop a relationship between
chloride and specific conductance in lake waters, and to determine if sodium and chloride
are the dominate ions causing observed changes and fluctuations in specific conductiv-
ity; 2) determine if observed concentrations of sodium and chloride in lakes receiving
runoff from major roadside environments are elevated above background concentrations,
and if these elevations can be contributed to road salt applications; 3) understand how
individual lakes are influenced by road salt applications in terms of chemical stratifica-
tion, seasonal salinity cycles and convective transport of NaCl into lake sediments; 4)
examine regional trends in lake chloride concentrations and 5) determine if relationships
exist between these concentrations and watershed/lake parameters.
3.3 Methods
3.3.1 Data collection
Two sets of lake water quality data from the TCMA were analyzed to meet the ob-
jectives of the study. The first set was collected by the authors and the second was a
historical data set. In addition, sediment cores were extracted from two lakes.
Lake data collection (Data Set 1) The first lake data set includes 13 lakes which
51
were selected to meet four criteria: 1) receive runoff from a major highway or road-
way through storm sewers, streams or overland flow; 2) have a maximum depth large
enough so that stratification, i.e. a seasonal thermocline and/or chemocline could form;
3) have previously been monitored by a public agency, e.g. by the Metropolitan Coun-
cil, Minnesota Pollution Control Agency (MPCA) or area watershed district, so that
long term unbiased information is available; 4) have data on bathymetry and water-
shed available. Locations of the selected lakes and their watersheds in the TCMA are
shown in Figure 3.2. Lakes are listed in Table 3.1 along with characteristics of each lake
and its watershed. Bathymetric data were obtained from the Minnesota Department of
Natural Resources and watershed delineations were gathered using GIS data obtained
from the Metropolitan Council. Impervious surface areas in the lakes watersheds in
2002 were obtained using GIS data from the University of Minnesota Remote Sensing
and Geospatial Analysis Laboratory (http://land.umn.edu/index.html).
Bryant
Cedar Isles
Brownie
Parkers
Bass
Medicine SweeneyGervais
McCarron
Johanna
Tanners
LegendMajor Roads
Lakes
Lakesheds´
Ryan
Minneapolis
St Paul
10Kilometers
Figure 3.2: Locations and watersheds of the 13 lakes sampled (Data Set 1) from 2004-2007 in the Minneapolis-St. Paul Twin Cities Metropolitan Area (TCMA).
52T
able
3.1:
Lak
ean
dw
ater
shed
info
rmat
ion
for
the
13la
kes
sam
pled
from
2004
to20
07(D
ata
Set
1).
Sam
plin
gpe
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repr
esen
tsth
eye
ars
inw
hich
each
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sam
pled
.04
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renc
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kes
sam
pled
betw
een
2/15
/200
4to
4/13
/200
5,06
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repr
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tsla
kes
sam
pled
betw
een
1/14
/200
6to
11/1
5/20
07an
d04
/07
repr
esen
tsla
kes
sam
pled
duri
ngbo
thti
me
peri
ods.
Max
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urf
ace
Wat
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ater
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/P
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nt
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olu
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a/D
epth
Su
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ace
Are
aIm
per
vio
us
Per
iod
(m)
(Ha)
(m3)
(ha/
m)
(ha)
(%)
(yea
r/ye
ar)
Bas
s9.
470
.467
3,00
07.
511
3116
215-
Apr
Bro
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e14
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000
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edar
15.5
68.4
4,43
3,00
04.
453
78
287-
Apr
Ger
vais
12.5
94.7
4,82
3,00
07.
611
4412
307-
Jun
Joha
nna
13.1
86.2
4,27
4,00
06.
611
8814
395-
Apr
Isle
s9.
444
.11,
120,
000
4.7
252
629
5-A
prM
cCar
ron
17.4
27.6
2,15
1,00
01.
654
920
247-
Apr
Med
icin
e14
.935
8.6
18,5
89,0
0024
4380
1229
5-A
prP
arke
rs11
.336
.91,
414,
000
3.3
340
927
7-Ju
nR
yan
117.
629
5,00
00.
777
1034
7-A
prSw
eene
y7.
626
.795
2,00
03.
515
1257
377-
Jun
Tan
ners
1428
.31,
848,
000
221
48
337-
Jun
53
These 13 lakes were sampled every 4-6 weeks during two sampling periods. All
of the lakes studied are natural lakes with inflows coming from streams and/or storm
sewers. Two of the lakes have special conditions: Brownie Lake and Sweeney Lake.
Brownie Lake has been known to be meromictic since 1925. It is a very small and
wind sheltered lake. The construction of a channel connecting Brownie Lake to Cedar
Lake and road construction drastically reduced the lakes surface area, resulting in a
low surface area to depth ratio[89, 90]. Road salt, while not the original cause, has
contributed to the current meromictic conditions. Sweeney Lake, on the other hand,
has an aeration system, which makes it an artificially mixed lake. In April 2007 this
system was shut off for the purpose of conducting a phosphorus TMDL study.
From 2/15/2004 to 4/13/2005 eight lakes were sampled: Bass, Cedar, Lake of the
Isles, Johanna, McCarron, Medicine, Ryan and Brownie. From 1/15/2006 to 11/15/2007
four of the previous lakes were sampled (Ryan, Cedar, Brownie and McCarron) and
5 new lakes were added (Tanners, Parkers, Bryant, Gervais, and Sweeney). Parkers
Lake was added on 5/7/2006 and Sweeney Lake, Tanners Lake and Lake Gervais were
added on 8/8/2006. Lakes that did not show strong salinity stratification after the
first sampling period were dropped, and other lakes with a high likelihood of salinity
stratification were added. Lake selection was thus biased towards lakes that would
receive high salinity runoff. Cedar Lake was kept as a reference lake that showed little
stratification.
In total, 173 specific conductivity/temperature profiles were measured in the 13 lakes
at 4- to 6- week intervals over a 46-month period. These measurements were made in
the water column every 0.5 meters at approximately the deepest location in each lake
using an YSI Model 63 probe [91]. Water samples were collected during the winter
(22 February 2007) when sodium and chloride concentrations are highest and in the
fall (15 November 2007) when maximum flushing of the lakes due to summer rainfall
has occurred. Water samples were taken 1 m below the waters surface and 1 m above
the bottom at approximately the deepest location in the 9 lakes sampled from 2006 to
2007. Samples were analyzed for major ion concentrations in the laboratory of Geology
and Geophysics at the University of Minnesota-Twin Cities. Anions were analyzed on a
Dionex ICS-2000 ion chromatography system consisting of an AS19 analytical column,
ASRS Ultra II suppressor, AS40 autosampler, and integrated dual piston pump and
54
conductivity detector. Cation samples were acidified with HCl to a pH of 2 and ana-
lyzed on a Dionex ICS-2000 ion chromatography system consisting of a CS16 analytical
column and guard column, CSRS Ultra suppressor, AS40 autosampler, and integrated
dual piston pump and conductivity detector.
Historical lake data(Data Set 2) The second set of lakes examined for this study
includes lakes sampled by watershed districts, consulting companies, and government
agencies in the TCMA, typically during the ice free months of May November with
limited data available during the winter months. This data set is available on the
MPCA Environmental Data Access website (http://www.pca.state.mn.us/data /eda/)
used to store environmental data from water bodies around the state. Historical chloride
concentrations in 38 TCMA lakes were selected based on the length and continuity of
the data set. Information on individual lakes was gathered from the same sources as
data set 1.
Lake sediment cores In order to examine if the salt water concentrating at the
bottom of the lakes in winter and spring is seeping into the lake sediments, and possibly
into the groundwater, sediment cores were extracted from two lakes. Tanners lake,
which displayed high concentrations of chloride at the bottom during the winter months
and Lake McCarron, which displayed much lower chloride concentrations. These two
lakes were chosen to make a comparison between the two conditions. One 1.2 m long
sediment core was extracted from each lake at the deepest part of the lake during the
winter (2/28/2007). The cores were separated into 4-centimeter sections and the pore
water was extracted using a centrifuge and filtered through a standard 0.045 µm filter.
The 4-centimeter sections allowed for the extraction of enough pore water to be used in
ion analysis. Five samples evenly distributed through the sediment core were analyzed
to give a representation of how ion concentrations are changing with depth.
3.3.2 Data analysis
A relationship was developed between specific conductance and all the major ions in
the water samples to determine which ions were dominant. Chloride concentration
and specific conductance data from different lakes, water depths and times throughout
the year were available (data set 2, in addition to our own water samples taken on
2/22/2007 and 11/15/2007 in 9 lakes) to create a robust relationship between specific
55
conductance and chloride concentration. The relationship was used to convert specific
conductance profiles measured in the lakes to chloride concentration profiles. Chloride
is a conservative ion with minimal natural sources in the TCMA and therefore useful
as an indicator of road salt.
Data set 1 was used to analyze objectives 2 and 3. The chloride vs. depth profile time
series were used to determine stratification patterns as well as seasonal cycles in the 13
monitored lakes. Volume-weighted average concentrations, using the bathymetric data,
were determined for each measured chloride profile in each lake and each measurement
date. For a more comprehensive view of the salinity cycles in the lakes, the volume-
weighted average concentrations for each survey date were normalized. The average
concentrations for each lake from May 2004 to April 2005 or from Sept 2006 to August
2007 were used as the reference for normalization of the 2004/2005 and 2006/2007 data
sets, respectively. This normalization was calculated by dividing the time series by
the reference value. The normalized data sets for all lakes were then combined, i.e.
averaged, for each sampling date to get a seasonal cycle for all the lakes combined.
Volume-weighted average concentrations were also used to determine the seasonal
storage and flushing of salt in the lakes. This normalized flushing rate is equal to
the maximum minus the minimum volume-weighted average chloride concentrations of
a lake for a particular year. This difference in concentrations multiplied by the lake
volume would give an idea of how much salt (tonnes/year) is being flushed through
a particular lake in the course of a year. This amount of salt was also expressed as
a fraction (percentage) by dividing the difference of maximum and minimum average
concentrations by the minimum concentration.
Profiles in specific conductance, temperature and dissolved oxygen were analyzed
for Tanners Lake. This lake was chosen because it changed from monomictic behavior
in 2006 to dimictic behavior in 2007. We sampled Tanners Lake starting on 8/8/2006
taking profiles of temperature and specific conductance. Profiles of dissolved oxygen
for the entire time period and temperature and specific conductance from 5/11/2006
to 7/12/2006 were available from the Minnesota Pollution Control Agency (MPCA)
Environmental Data Access; the measurements were made by the Ramsey-Washington
Watershed District.
Data set 2 was used for objectives 4 and 5. Annual average specific conductivity
56
values for the top 3 meters and annual maximum values were determined for each lake
and date of survey to obtain an estimate of how the salinity of the 38 lakes has been
changing over time. The time series for the top 3 meters between 1984 and 2005 was
used for a trend analysis. Each lake was normalized individually using the average
annual concentrations from 2001-2005 as a reference. Once a time series was developed
for each individual lake a combined time series was calculated by averaging each of these
series together resulting in a single time series of normalized specific conductance for
all 38 lakes. Correlations were also calculated between lake watershed and bathymetric
parameters with chloride concentrations.
3.4 Results
3.4.1 Ionic composition and relationship to specific conductance
The ionic composition in the lake water samples collected in 2007 (Table 3.2) shows
a difference between the winter (February) after some snowmelt water has entered the
lake and the fall (November) after the summer flushing of the lake by rainfall events.
Correlation coefficients between the specific conductance values and the individual ionic
concentrations for chloride, sodium, sulfate, potassium, calcium and magnesium were
0.99, 0.97, -0.09, 0.93, 0.12 and 0.28, respectively.
Table 3.2: Median ionic concentrations of water samples from 9 lakes in data set one.Water samples were taken in February and in November 2007. All concentrations arein mg/L. SC represents specific conductance (µs/cm). Top represents samples taken 1meter below the water surface and bottom represents samples taken 1 meter from thebottom.
2/22/2007 11/15/2007Top Bottom Top Bottom
Ca2+ 48 51 42 43Mg2+ 17 18 14 14Na+ 73 105 59 59K+ 3 3 3 3NH+
4 1 2 0 0SO2−
4 14 16 13 13Cl− 132 186 109 109SC 745 988 612 639
57
Using historical data from numerous other lakes in the TCMA in addition to the
above water sample data, a linear relationship between chloride and specific conductance
(Eq.3.1 with R2 = 0.94) was created (Figure 3.3).
[Cl−] = 0.25 ∗ SC − 37.25, (3.1)
where [Cl-] is the chloride concentration in mg/L and SC is the specific conductance
in µS/cm. This equation was used to convert specific conductance measurements in the
lakes to chloride concentrations.
y = 0.25x - 37.25
0
200
400
600
800
1000
1200
0 1000 2000 3000 4000 5000
Ch
lori
de (
mg
/L)
Specific Conductance (µS/cm)
Parkers McCarron
Cedar Carver
Diamond Gervais
Spring Pond Tanners
Loring pond Powderhorn
Como Battle Creek
Snail Valentine
2/22/2007 11/15/2007
Figure 3.3: Relationship between chloride and specific conductance. Individual lakevalues were obtained from the Minnesota Pollution Control Agency (MPCA) Environ-mental Data Access website and were sampled by government agencies or consultingcompanies in the TCMA. Data points marked 11/15/2007 and 2/22/2007 are watersamples from the 9 lakes monitored between January 2006 and September 2007.
58
3.4.2 Seasonal salinity cycles and salinity stratification
Lake surface waters had often lower specific conductance than lake bottom waters.
To document this stratification we plotted chloride concentrations measured at 0.5 m
depth below the lake surface and at 0.5 m above the lake bottom of each lake. Figure
3.4 documents the measurements taken from the 9 lakes sampled between 2006 and
2007. Volume-weighted average chloride concentrations were also plotted. For the lakes
sampled between 2004 and 2005 plots similar to Figure 3.4 are presented and discussed
in detail in [92]. Salinity stratification can be seen in all 13 lakes studied. The strongest
salinity stratification was found in Brownie Lake, Parkers Lake, Tanners Lake and Ryan
Lake; the least in Bass Lake and Cedar Lake.
0
200
400
Chl
orid
e C
once
ntra
tion
(mg/
L)
0
200
400
1/06 7/06 1/07 7/070
200
400
1/06 7/06 1/07 7/07 1/06 7/06 1/07 7/070 400 800
BottomTopAverage
Sweeney Tanners Ryan
GervaisMcCarronParkers
Cedar Bryant Brownie
Figure 3.4: Chloride concentrations 0.5 m below the surface and 0.5 m above the bottomof a lake, and volume-weighted average chloride concentrations in each lake sampledfrom January 2006 to September 2007. The dark lines on the x-axis represent monthswhen snowfall can be expected to accumulate on the ground (November March).
59
The combined normalized volume-weighted average chloride concentration time se-
ries gives a comprehensive view of seasonal salt accumulation and flushing from a lake
(Figure 3.5). How the numbers were obtained is described in the methods section. Al-
though the data are for two different time periods and lake sets, the results converge
nicely: the highest normalized concentrations occur in the winter - when road salt is
being applied - and the lowest concentrations occur in the summer and fall when fresh
rainwater runoff entered the lakes and flushed some of the salt away, except for the
meromictic Brownie lake where the seasonal salinity dynamics occur only above the
chemocline.
0.7
0.8
0.9
1
1.1
1.2
Jan-04 Jan-05 Jan-06 Jan-07 Jan-08Nor
mal
ized
Vol
ume-
Wei
ghte
d [C
l-]
MeanMedian
Figure 3.5: Seasonal salinity (Cl-) cycles illustrated by normalized (volume-weighted)average chloride concentrations, averaged for all lakes in each time period (Data set 1).Bars represent the standard deviation for the set of lakes.
Seasonal salinity cycles, expressed in terms of the amount of salt passing through a
lake in a year relative to its minimum salt content in that year, were present in all lakes
studied, but were more pronounced in some of the lakes than others. The strength of
the seasonal salinity cycle was calculated and analyzed (Table 3.3). Brownie Lake, Ryan
Lake, Lake of the Isles and Sweeney Lake had the strongest seasonal salinity cycles of all
the lakes studied. The highest annual salt turnover (accumulation and flushing) rates in
three years of observation were 54% and 55% of the minimum salt content in Sweeney
Lake and Lake of the Isles. The lowest annual salt turnover rates were obtained for
Bryant Lake and Parkers Lake; they were 9% and 11%.
60T
able
3.3:
Salin
ity
(Cl-
)cy
cles
inT
CM
Ala
kes.
Per
cent
chan
ge=
((M
ax-M
in)/
Min
)*10
0%Ja
n20
04-
Nov
2004
Jan
2006
-N
ov20
06Ja
n20
07-
Nov
2007
Min
Max
Per
cent
Min
Max
Per
cent
Min
Max
Per
cent
(mg/
L)
(mg/
Lch
ange
(mg/
L)
(mg/
Lch
ange
(mg/
L)
(mg/
Lch
ange
Bas
s76
9424
––
––
––
Isle
s88
135
54–
––
––
–Jo
hann
a11
212
714
––
––
––
Med
icin
e10
112
827
––
––
––
Bro
wni
e27
038
643
279
381
3625
633
332
Ced
ar88
106
2096
109
1410
111
817
McC
arro
n10
212
321
113
132
1712
113
915
Rya
n88
128
4585
103
2192
123
34B
ryan
t–
––
8997
910
011
010
Ger
vais
––
––
––
113
146
29P
arke
rs–
––
––
–14
716
311
Swee
ney
––
––
––
172
266
55T
anne
rs–
––
––
–13
116
727
61
3.4.3 Effects of salinity on seasonal mixing and dissolved oxygen
In addition to the salinity dynamics in the surface and bottom waters of each lake
it is of interest to consider the complete measured temperature, chloride and dissolved
oxygen profiles, and to study chemoclines, thermoclines and dissolved oxygen picnoclines
in relation to each other (Figure 3.6). Tanners Lake, with a chemocline capable of
preventing a full lake turnover in the spring but not in the fall, can be used to illustrate
the seasonal stratification cycles in more detail. Tanners Lake does not appear to be
meromictic, but monomictic at times. During the early spring and summer of 2006,
chemical stratification was present in Tanners Lake. Erosion of the chemocline through
the fall, due to cooling of the lakes surface, allowed for some of the chloride to be flushed
from the lake. During the winter months the chemocline reformed in the deepest portion
of the lake. The highest concentrations of chloride and the thickest layer of saline water
are seen in April. This is significant because the thermocline had already begun to
form. If the spring overturn of the lake were triggered by density differences due to
temperature only, the lake would have fully mixed by April. Similar patterns are seen
in Parkers Lake (Novotny et al. 2007).
Chloride concentration profiles in the other lakes studied (McCarron, Cedar, Bryant,
Ryan, Gervais) indicate that these lakes received salt, but not enough, to prevent full
mixing either in the spring or fall [93]. Inflows of salt water to the bottom of these
lakes during the winter can be inferred from the observed changes in chemical strati-
fication. This chemical stratification is not as strong as in Tanners Lake and Parkers
Lake. Sweeney Lake on the other hand acts more like a well-mixed body of water with
concentrations in the whole lake increasing in the winter and decreasing in the summer
and fall [93]. This behavior is caused by an artificial lake aeration/mixing system.
3.4.4 Salinity in lake sediment cores
To see if the saline water layer at the lake bottom is connected to the pore water in the
lake sediments, sediment cores were extracted from Lake McCarron and Tanners Lake.
In Tanners Lake the saline layer above the bottom of the lake is up to 7 m thick and
has chloride concentrations reaching 400 mg/L compared to maximum concentrations
of 240 mg/L chloride in Lake McCarron. The cores were sectioned and the pore water
62
!
Chloride (mg/l)
0 250
-12
-8
-4
0
De
pth
(m
)
5/1
1/2
00
6
0 250
6/1
4/2
00
6
0 250
7/1
2/2
00
6
0 250
8/8
/20
06
0 250
9/2
5/2
00
6
0 250
11
/8/2
00
6
0 2501
/24
/20
07
0 250
2/2
1/2
00
7
0 250
4/1
/20
07
0 250
5/1
7/2
00
7
0 250
7/1
3/2
00
7
0 250
9/1
7/2
00
7
0 250
11
/16
/20
07
Figure 3.6: Chloride concentration, dissolved oxygen concentration and water tempera-ture vs. depth in Tanners Lakes from May 2006 to Nov 2007. The Ramsey WashingtonWatershed District gathered all dissolved oxygen profiles along with specific conductiv-ity and temperature profiles between May and July 2006. The authors monitored allother data points for specific conductance and temperature between August 2006 andNovember 2007.
63
was extracted and analyzed for major ions. The profiles (Figure 3.7) show sodium
and chloride concentrations decreasing more or less exponentially with depth in the
sediments of both Lake McCarron and Tanners Lake. The chloride profiles in the pore
water start at the sediment surface with concentrations equal to those of the saline
water layer at the bottom of the lake. The concentrations of the other ions in the pore
water appear to stay about constant with depth into the sediment, but sodium and
chloride do not. The concentrations of sodium and chloride start at around 250 and
410 mg/L, respectively, in Tanners Lake and around 113 and 186 mg/l, respectively, in
Lake McCarron. Over the length of the core (1.2 m) these values are reduced to 36 and
78 mg/L in the Tanners Lake core and to 14 and 34 mg/L in the Lake McCarron core,
respectively.
-120
-70
-20
30
80
0 100 200 300 400Concentration (mg/L)
Dis
tanc
e ab
ove
and
belo
w
sedi
men
t wat
er in
terfa
ce (c
m) Tanners Lake
0 100 200 300 400Concentration (mg/L)
ChlorideSodiumCalciumMagnesiumSulfatePotasium
Lake McCarron
Figure 3.7: Ionic composition of pore water in sediment cores extracted from the deepestpoints of Lake McCarron and Tanners Lake. Values of chloride concentrations rightabove the sediments are also shown. Sediment cores were extracted on 2/28/2007.
3.4.5 Salinity trends in TCMA lakes
To determine if long-term changes in lake salinity are occurring, the average annual
specific conductance values of the 38 lakes from 1984 to 2005 (data set 2) were plotted
against time along with the amount of rock salt purchases by the state of Minnesota
from 1930 to 2005 (Figure 3.8). The trends for both the specific conductance (salinity)
of TCMA lakes and for the rock salt purchases by the state are strikingly similar. Both
64
time series show an increase from 1984 to 2005 and a correlation coefficient of 0.72.
Road salt applications vary somewhat from year to year with the number of snowfall
events [60]. To remove this variability, the correlation analysis was repeated with 5-year
running averages of the two time series, resulting in a correlation coefficient of 0.93.
y = 0.018x - 34.794
0.3
0.5
0.7
0.9
1.1
1.3
1930 1940 1950 1960 1970 1980 1990 2000 2010
Ave
rage
Nor
mal
ized
Spe
cific
Con
duct
ance
0
0.2
0.4
0.6
0.8
1
1.2
Min
neso
ta R
ock
Sal
t Use
(Mill
ion
tons
)
TC Metro area lakesMinnesota rock salt use
Figure 3.8: Time series of average normalized specific conductance in 38 Twin CitiesMetro Area lakes (Data Set 2) and total rock salt purchases by the State of Minnesota.
3.4.6 Relationships between lake salinity and watershed characteris-
tics
By collecting lake bathymetry, watershed information and chloride concentrations for
each of the 38 lakes in data set 2 (Table 3.4) correlations can be made with chloride
concentrations (Table 5). Lake surface area and lake depth, and even watershed area,
taken as single independent variables, have a very low correlation with chloride concen-
tration parameters in the lakes. The highest correlation was between lake surface area
65
and the chloride trend with a correlation coefficient of -0.44. Chloride concentrations
correlate better with the percentage of impervious surface areas in the watershed (Table
3.5). The ratio of impervious surface area in the watershed to a proxy for lake volume
(expressed as the product of lake surface area * lake depth) has the strongest correlation
with lake chloride concentrations (Table 3.5).
Table 3.4: Historical average, trend and maxima of chloride concentrations, and bathy-metric and watershed data for 38 TCMA lakes (Data Set 2). Chloride concentrations forthe top 3 meters are annual average value for the period 2001-2005. Trend is based onthe time series of annual average concentrations from 1984 - 2005 for the top 3 metersof each lake and normalized with the average value from 2001-2005 to get a percentchange per year. Annual Max chloride concentration is the average of the maximumconcentration in the lake for each year between 2001 and 2005, measured at any depth.
Years of [Cl-] top 3 Lake Max Watershed Percentdata meters Trend [Cl-] max area Depth area impervious
Lake (years) (mg/L) (%/year) (mg/L) (ha) (m) (ha) (%)Bald Eagle 22 42 0.6 87 513 11.0 2843 9Beaver 22 90 1.8 117 26 3.4 1446 26Bennet 22 63 2.2 100 9 2.7 293 36Brownie 15 105 2.1 798 5 14.3 136 33Calhoun 18 103 1.2 158 162 25.0 1408 35Cedar 18 84 0.8 142 68 15.5 537 28Como 22 89 2.1 166 25 4.6 591 32Diamond 17 142 2.1 467 47 1.8 268 44Gervais 22 100 2.4 178 95 12.5 1144 30Harriet 18 93 1.2 119 136 26.5 737 28Hiawatha 17 91 1.7 221 22 10.1 2378 45Independence 12 43 0.1 71 342 17.7 1630 3Island South 22 44 1.1 77 24 3.4 77 20Isles 18 87 1.0 134 44 9.4 252 29Johanna 22 107 2.2 167 86 13.1 1188 39Josephine 21 48 1.7 81 47 13.4 350 23Keller 21 87 2.4 113 29 2.4 329 23Kohlman 22 87 1.7 160 30 2.7 629 27Long NB 22 99 2.3 202 74 9.1 3781 25Loring 11 340 2.7 760 3 4.9 144 77Mccarron 22 85 1.7 189 28 17.4 549 24Medicine 14 88 1.4 204 359 14.9 4380 30Nokomis 18 66 1.1 99 83 10.1 1467 36Otter 18 25 0.6 50 134 6.4 382 7Owasso 22 44 1.2 81 141 11.3 1047 24Phalen 22 89 2.3 127 80 27.7 580 30Powderhorn 13 86 0.7 361 5 6.7 94 44Round 22 94 2.4 231 12 2.4 251 29Snail 22 57 2.4 102 61 9.1 477 22Spring 10 505 3.0 1018 2 2.1 30 47Tanners 11 104 1.1 288 28 14.0 214 33Turtle 22 42 1.2 70 166 8.5 316 12Valentine 20 117 2.5 208 24 4.0 664 33Wabasso 22 36 1.2 74 19 20.1 103 32Wakefield 22 97 2.9 178 9 3.0 563 32Weaver 11 53 0.7 85 60 17.4 203 17West Silver 21 57 2.2 225 29 14.3 208 30White Bear Lake 22 31 0.9 43 978 25.3 3059 11
66
Table 3.5: Correlation coefficients of chloride concentrations with lake and watershedparameters (Data Set 2). PI (percent impervious), SA (lake surface area), D (lake maxdepth).
Lake watershed PI/ PI *area Depth area Percent (SA*D) D/SA(ha) (m) (ha) Imperv. (1/m3) (1/m)
[Cl-] top 3 m -0.25 -0.29 -0.18 0.67 0.94 0.57[Cl-] ave. annual max -0.28 -0.26 -0.24 0.66 0.79 0.78Trend -0.44 -0.40 -0.18 0.54 0.43 0.26
3.5 Discussion
3.5.1 Comparison of ionic composition with other freshwaters
Are sodium and chloride concentrations measured in the urban lakes really different
from those measured in lakes and rivers outside the metropolitan area? If differences
in measured sodium and chloride concentration can be documented, are there similar
differences in other major ions? Answers to these two questions can be provided by
comparing the results in Table 3.2 for 9 urban lakes to similar measurements in other
water bodies. The comparison with six different natural waters is made in Table 3.6.
The ionic strengths measured in the 9 urban lakes after a summer and partial fall
season, are listed in the last column of Table 3.6 for comparison. It is apparent that
the urban lakes have much higher sodium and chloride concentrations than any of the
other waters, including the Mississippi and Minnesota Rivers which are by no means
pristine even before they enter the TCMA. Ionic strengths of other ions, such as calcium,
magnesium and potassium, sulfate and nitrate in the 9 urban lakes are comparable to
or lower than those in other surface water bodies. It can be concluded that the sodium
and chloride concentrations measured in the urban lakes are not found in other surface
water bodies.
67T
able
3.6:
Ioni
cco
mpo
siti
on(m
g/L
)of
sele
ctiv
esu
rfac
ew
ater
sin
Nor
thA
mer
ica
and
the
nine
lake
sst
udie
din
2006
/200
7.a
From
[55]
.b
From
Lon
gT
erm
Eco
logi
calR
esea
rch
(LT
ER
)si
te(N
orth
Tem
pera
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akes
(Tro
ut)
Reg
ion)
.c
Ave
rage
s(2
000-
2007
)fr
omM
etro
polit
anC
ounc
ilda
taba
se.
Loc
atio
nsar
ebe
fore
the
rive
rsen
ter
the
TC
MA
.dA
ver-
ages
from
lake
sin
Min
neso
ta[9
4].
eM
edia
nco
ncen
trat
ions
from
area
lake
sst
udie
ddu
ring
2006
/200
7.Sa
mpl
esta
ken
11/1
5/10
07. aC
onti
nen
tal
bD
ilu
tedM
inn
esot
aaN
orth
cM
issi
ssip
pi
cM
inn
esot
aeL
akes
Rai
nW
isco
nsi
nL
akes
Am
eric
anR
iver
atR
iver
atS
tud
ied
Lak
eR
iver
sA
nok
aJo
rdan
Ca2
+0.
2-
413
2921
5010
342
Mg2
+0.
05-
0.5
316
517
4714
Na+
0.2
-1
26
912
3259
K+
0.1
-0.
5–
31
35
3N
H4+
0.1
-0.
5–
––
––
0.1
SO42
-1
-3
–14
2017
162
13C
l-0.
2-
20.
34
817
3410
9N
O3-
0.4
-1.
3–
–1
0.8
60.
6
68
3.5.2 Indicators of the salinity sources
What is the source of the elevated sodium and chloride concentrations in the urban
lakes? The TCMA has minimal natural sources of chloride. Consequently, under natural
conditions Cl- concentrations would be expected to be low. Indeed, the median Cl-
concentration in TCMA lakes in 1800 and 1750 was estimated to be 3 mg/L by using
diatom assemblages in sediment cores [14]. Under current land use conditions lakes
in the North Central Hardwood Forests ecoregion of Minnesota, which includes the
TCMA as well as less developed areas surrounding the TCMA, have 4-10 mg/L of
chloride based on the inter-quartile 25th 75th percentile [95]. The increased sodium and
chloride concentrations in urban lakes of the TCMA are also apparent in a comparison
with lakes located throughout the state of Minnesota [94]. This set includes 91 lakes
overall, excluding lakes in western Minnesota where high specific conductance is due to
rich sulfur bearing minerals (gypsum and pyrite) and lakes in northeastern Minnesota
(Canadian shield area) with very low specific conductivity values. Chloride and sodium
concentrations in the TCMA lakes are between 10 and 25 times higher than in these
other lakes (Table 3.6). By comparison, calcium concentrations in the TCMA lakes are
only 1.4 times higher than in the other lakes throughout Minnesota. Overall, the nine
urban lakes in the TCMA appear to be chloride and sodium dominated waters differing
from other water bodies in the region, which are either calcium or sulfate dominated
[94, 96].
Because the TCMA has minimal natural sources of chloride, an anthropogenic salt
source has to be suspected. Since both Cl- and Na+ ions in urban lake waters are
elevated, it can be suspected that the common source is sodium chloride (NaCl). If Cl- is
derived solely from NaCl, a stoichiometric requirement is that the molar concentrations
of Cl- and Na+ should be in a 1:1 relationship. In the lake water samples gathered on
2/22/2007 and 11/15/2007 the molar ratio of Cl- to Na+ was 1.13:1. It is speculated
that the molar relationship is not exactly 1:1 because Na+ ions are known to adsorb
onto particles whereas Cl- is not (Lofgren 2001; Norrstrom and Bergstedt 2001; Oberts
2003). The molar ratio is, however close enough to 1: 1 to confirm that NaCl is the
likely source of elevated Na+ and Cl- concentrations in the TCMA lakes.
In addition to road salt use, domestic salt use for water softening and industrial/commercial
uses have to be considered. A major use of NaCl in the TCMA is for water softening but
69
a majority of the saline water from water softeners in the TCMA is discharged through
sanitary sewers into WWTPs and eventually into the Mississippi River bypassing any
lakes.
The presence of a seasonal lake salinity cycle points towards road salt as the source
of lake salinity. Snowmelt runoff containing dissolved road salt in winter and spring,
and rainfall runoff without road salt content in summer and fall would be expected to
cause a seasonal salinity cycle in lakes and streams. This pattern has been observed in
all 13 lakes studied (Figures 3.4 and 3.5 and Table 3.3). This same pattern was seen in
a lake in Sweden and modeled using estimated road salt applications, precipitation and
evaporation in the lakeshed [97].
3.5.3 Salinity, temperature and dissolved oxygen stratification
In all of the lakes studied the formation of a chemocline occurred in the winter coin-
cident with observed peak salt concentrations in streams of the TCMA (Figure 3.1).
The location and strength of the chemocline varied between individual lakes and from
year to year. The variability is associated with many parameters including the number
of snowfall events and snowfall amounts in a winter season, influencing the amount of
road salt applied, in addition to climate parameters such as air temperatures and solar
irradiance, influencing the timing and amount of runoff. Wind speed and direction as
well as surface cooling, which cause convective circulation to break the chemical strati-
fication in fall or spring when thermal stratification is weak, can also add to temporal
inconsistencies. Lake stratification simulations operating at high temporal resolution
can be used to relate salt inputs, lake mixing, temperature stratification and weather
patterns.
Among the nine individual lakes in Figure 3.4 five (Parkers, Tanners, Ryan, Brownie,
and McCarron) appear to have a stronger chemical stratification then the other four.
These five lakes also have the smallest surface area to depth ratios. It is interesting
to note, that a very similar parameter, the lake geometry ratio defined as the ratio of
maximum lake depth to the fourth root of the lake surface area was introduced [98] as
an indicator of the strength of temperature stratification of lakes. This parameter has
been very useful to distinguish between dimictic and polymictic temperature stratified
lakes [99, 100].
70
It is clear from the data that the chemical stratification in some of the lakes can be
strong enough to prevent mixing during either the fall or spring turnover periods or at
least delay the lake from fully mixing. In two lakes, Tanners Lake and Parkers Lake,
monomictic behavior was observed. In Tanners Lake mixing was prevented in the spring
of 2006 resulting in anoxia of the benthic waters (Figure 3.6). When the lake mixed in
the fall oxygen was circulated again over the full lake depth. In the following spring
of 2007 the turnover period was delayed due to the existence of chemical stratification,
but occurred later in the season.
The prevention or delay of the full lake turnover (vertical mixing), when the water
reaches maximum density of freshwater at 4oC, can adversely affect the lakes water
quality, especially near the lakebed. Oxygenation of the benthic waters is an impor-
tant process in the health of a lake. It is well known that phosphorus is released from
anoxic sediments into the water above at much higher rates than when the sediments
are well aerated. With longer anoxic periods more phosphorus could be released from
the sediments stimulating algal blooms in the surface mixed layer when the lake fi-
nally overturns. Certain fish typically migrate to deeper waters during the hot summer
months. If mixing is prevented in the fall the anoxic zone could be increased reducing
the inhabitable space for fish in the lake. Prolonged anoxic periods are shown in Figure
3.6 for the year 2006 when mixing was prevented in the fall. The next full mixing of
Tanners Lake occurred before the 5/17/2007 sampling period resulting in oxygenation
of the benthic waters.
3.5.4 Seasonal flushing of salt from the TCMA lakes
The strength or amplitude of the seasonal salinity cycle in the urban lakes (Table 3.3)
appear to be loosely related to the size of a lake relative to its depth, watershed area
and impervious area in the watershed (Tables 3.3 and 3.4). Sweeney, Brownie, Isles,
and Ryan Lakes have the highest seasonal flushing rate (percent change). The strongest
salinity cycle is seen in Sweeney Lake, which has a large watershed area to lake area ratio
and drains Interstate 394 and Highway 100, both heavily traveled roadways. Sweeny
Lake is artificially mixed throughout the year and has a small depth to surface area ratio
and a larger watershed area to lake surface area ratio, all of which appear to increase
the flushing (salt removal) from the lake. Seasonal salinity cycles had already been
71
found in grab samples collected from the surface of lakes near highways in the TCMA
from 1982-1987 [101]. That study was, however, limited to grab samples from the lakes
surface and did not include volumetric average concentrations or concentrations near
the bottom of the lake.
Seasonal fluctuations in chloride concentrations can also influence the aquatic life in
a lake. The chronic standard of 230 mg/L chloride required for the protection of aquatic
life was exceeded at some point in time in 5 of the 13 lakes studied (Tanners, Parkers,
Brownie, Ryan, Sweeney). These elevated concentrations were typically found during
the winter and spring months and occurred in the deepest portion of the lakes. Only
one lake (Sweeney) displayed chloride concentrations above the standard throughout the
entire water column because it was artificially mixed by an aeration system to control
eutrophication. The presence of this high salinity water for prolonged periods of time
could be changing the aquatic community in each of these lakes. Increases in sodium
and chloride concentrations have been shown to decrease the biodiversity in wetland
areas and waterways [7, 8]. Shifts in diatom communities to more salt tolerant species
have also been observed with increasing chloride concentrations in lakes [14].
3.5.5 Convective mixing of saline lake water with pore water in the
sediments
The presence of a high salinity layer at the bottom of the lake causes the convective pen-
etration of saltwater into the pore system of the lake sediments. It is the same process,
induced by density instabilities, that mixes the surface waters of a lake during cooling,
except that in the surface waters the density differences are caused by temperature and
not salinity differences, and no pores are present. Leakage of saline water into the less
dense pore water of lake sediments can be inferred from Figure 3.7. Similar chloride
profiles were found in a study of the benthic sediments of a stormwater detention pond
receiving runoff from a major roadway. In this detention pond chloride concentrations
were 3000 mg/L at the sediment-water interface and 1500 mg/L at a depth of 0.4m into
the sediment core [44]. The convective mixing in the sediment pore system of a lake or
pond receiving road salt runoff is driven by density instability. If the density of the saline
water above the sediments is higher than the density of the water in the pore system,
finger-like intrusions of the denser saline water into the fresher (lighter) pore water will
72
form; in turn the fresher (lighter) water will rise in finger-like formations through the
pore system. This process is slow, but persistent, and referred to as convective mixing.
As a result pore water with a low salt concentration and density moves upward and is
replaced by water with a higher salinity moving downwards into the sediment pores.
Convective transport of solutes into the sediment bed occurs also in estuaries when
the density of the overlaying water is greater then the sediment pore water [102]. Convec-
tive transport has been observed in laboratory experiments and in numerical simulations
of saline lakes. Instabilities created by density differences cause increased transport of
salt into the groundwater [103, 104, 105, 106]. The process was also found in tests of
sulfate reduction in sediment cores from Devil Lake, South Dakota [107]. Due to the
density differences between the overlying water and the sediment pore water the effec-
tive diffusion (dispersion) coefficient was found to be much larger then the molecular
diffusion coefficient.
These observations suggest that a loss of chloride into the sediments occurs during
the winter and early spring when saline water accumulates at the bottom of a lake. The
loss would be expected to continue until an impermeable sediment layer or stability
between the layers of water is reached. The penetration of saline water into the lake
sediments can cause the release of metals from the solids. Increased transport of heavy
metals (Zn, Cd, Cu and Pb) coincident with road salt applications have been observed
in road side soils in Germany, Sweden and the United States due to chloride complexes,
ion exchange, and even increased colloidal dispersion [39, 37, 38, 36, 40]. High NaCl
concentrations decrease the partitioning coefficients between the dissolved and particu-
late phases of these metals resulting in higher mobility and bioavailability [35, 34, 36].
By increasing the concentrations of metals in the dissolved phase they are free to move
with the water either further into the sediments due to convective mixing or to diffuse
into the overlying lake waters.
3.5.6 Salinity trends in TCMA lakes
Salt concentrations in the urban lakes are increasing. Short-term trends of chloride
concentrations in individual lakes can be seen in Table 3.3. Two of the four lakes
(Cedar Lake and Lake McCarron) analyzed for the entire field study period (2004-2007)
show increases in the annual minimum and maximum concentrations from year to year.
73
This increase represents an accumulation of salt in both lakes over time. Bryant Lake
displays the same pattern, but has only been studied for two years. These findings
give only a hint of increasing lake salinities. Long-term and regional trends are seen
in Figure 3.8. The slope of the normalized specific conductance in Figure 3.8 is 0.018
or 1.8% per year, i.e. specific conductivity in lakes of the TCMA increases annually
and on average by 1.8% (The reference value is the average chloride concentration for
the period 2001 to 2005). Trend values for individual lakes range from 0.1% to 3.0%
(Table 3.4). The average trend seems reasonable because hind-casting projects the year
of minimum (near zero) chloride concentration to be about 1950. This is the time when
road salt application began to increase dramatically throughout the state (Figure 3.8).
By extending the trend into the future a doubling of specific conductivity, and
therefore chloride concentrations in the 38 lakes, would occur in about 50 years, i.e.
around 2060. Chloride concentrations would increase from a current median value of
87 mg/L to 174 mg/L. In 100 years the average chloride concentration in many TCMS
lakes would exceed the current chronic chloride standard year round and throughout the
water column. Current efforts to reduce road salt use by public agencies, commercial
and private users, may be balanced by continued urban growth and possible increased
snowfall due to climate change (Seeley 2003) so that the trends seen in Figure 3.8 could
continue for some time into the future.
3.5.7 Relationships between lake salinity, lake bathymetry and water-
shed characteristics
Although trends and increased chloride concentrations are occurring throughout the
region, the magnitude of these parameters appear to be dependent on both lake and
watershed characteristics of the individual lakes. Table 3.4 gives parameters for the 38
individual lakes in database 2. Chloride concentrations in the surface layer throughout
the TCMA ranged from 31 mg/l in White Bear Lake, a large lake located in the northern
suburbs to 505 mg/l in Spring Lake which is a small lake receiving large amounts of
runoff from I-394 in downtown Minneapolis. The highest chloride concentrations all
occurred during the winter months and near the bottom of the lakes. These values
ranged from 43 mg/L in White Bear Lake to 1,018 mg/L in Spring Lake. Each of the
38 individual lakes shows an increasing trend in average annual chloride concentrations
74
(Table 3.4). Although small lakes, and lakes near major roadways seem to have the
strongest upward trends, the increase in chloride and sodium concentrations in urban
lakes due to road salt applications appears to be regional and not specific to a small
number of lakes located close to highways.
The strongest correlations between chloride parameters and lake or watershed pa-
rameters were found by examining what percentage of the watershed is impervious.
This is to be expected since road salt is applied to impervious surfaces such as streets
and parking lots and as this percentage is increased not only is more salt being applied
but a more direct route is available for the runoff to reach the lakes. When including
the proxy for lake volume the correlation was even higher. As the volume of the lake
increases there is more water to dilute the snowmelt runoff causing lower concentrations.
3.6 Conclusions
The water quality of urban lakes in the Twin Cities Metropolitan Area (TCMA) of Min-
nesota has been investigated to identify and quantify impacts of road salt applications in
their watersheds. Lakes in the TCMA especially near major roads have elevated chloride
and sodium concentrations compared to other non-urban Minnesota lakes. The almost
1:1 molar relationship between chloride and sodium in the lake waters points towards
sodium chloride (NaCl) as the source. Since natural sources of NaCl in the geology of
the TCMA and Minnesota in general are very limited or rare, the source of the NaCl
must be anthropogenic. In the TCMA sodium chloride (NaCl) is used predominantly
for water softening and road deicing. The seasonal cycles of lake chloride concentrations
(high in winter/early spring and low in fall) point to road salt applications as the cause
of lake salinity in the urban lakes.
Specific conductance in the TCMA lakes is strongly correlated with Cl- and Na+
ions. Specific conductance profiles showed chemical stratification in almost all urban
lakes investigated. Over the course of a year, specific conductance, Cl- and Na+ con-
centrations are cyclic, both in the surface and the bottom waters of the urban lakes.
Volume-weighted average chloride concentrations give the amount of seasonal salt stor-
age/flushing. In the 13 urban lakes investigated, the annual storage/flushing rate ranged
from 9 to 55% of the minimum salt content in the lake. Smaller lakes with larger
75
watershed areas and a higher percentage of impervious surfaces had higher seasonal
storage/flushing rates, as to be expected.
There are physical, chemical and biological consequences of increased lake salinity. In
two of the lakes (Tanners and Parkers Lake) chemical stratification near the lake bottom
was strong enough to prevent the lake overturn in spring of 2006. This behavior prevents
dissolved oxygen from reaching the lake sediments. Complete lake mixing resumed in fall
2006 and spring 2007 In several individual lakes chloride concentrations were observed
to exceed the chronic water quality standard for aquatic life. High salt concentrations
were also found in the sediments of Tanners Lake which can cause the release of heavy
metals from the solids into the pore water from where they are transported further into
the sediments or into the overlaying water.
Historical chloride concentration data from 38 lakes in the TCMA show an annual
average increase of 1.8% (range from 0.1 to 3.0%) throughout the TCMA. The increase
is strongly correlated with the amount of road salt purchased annually by the state of
Minnesota since the 1950s. Chloride concentrations in individual lakes are positively
correlated with the percent of impervious surface area in the watershed, and inversely
correlated to lake volume. Overall, the results show a progressive degradation of the
water quality of urban lakes due to application of NaCl in their watersheds. Road salt
is used to increase driving safety in winter, but current road salt application practices
do impair lake water quality in urban lakes.
Aknowledgements
We acknowledge and thank the Minnesota Local Road Research Board (LRRB) and
the Minnesota Department of Transportation (Mn/DOT) for providing the funding for
this research. We also thank the Technical Advisory Panel, lead by Wayne Sandberg of
Washington County, for input and suggestions to our research. We thank Amy Myrbo
and Kristina Brady of the Limnological Research Center (LacCore Facility) at the Uni-
versity of Minnesota, Department of Geology and Geophysics, for providing equipment
and expertise for the extraction and sectioning of the lake sediment cores. Karen Jensen
of the Metropolitan Council (MCES) provided valuable information on lake watershed
delineations and water quality information.
Chapter 4
A 0-D modeling approach to
study long-term chloride
concentration in lakes receiving
runoff containing road salt
Eric V. Novotny and Heinz G. Stefan
St. Anthony Falls Laboratory,
Department of Civil Engineering, University of Minnesota
Minneapolis, Minnesota 55414
76
77
4.1 Abstract
Chloride concentrations in lakes located in urban environments using road deicing salts
are increasing to levels that are changing natural lake mixing behavior and influencing
aquatic life. A 0-D model was developed to project the seasonal cycle of loading and
flushing of chloride as well as the long-term accumulation of chloride in urban lakes
receiving runoff from roads to determine steady state concentrations under different
loading conditions. The model was calibrated using five years (2004-2008) of monthly
salinity profiles from 7 lakes in the Minneapolis/St. Paul Twin Cities Metropolitan Area
of Minnesota, USA, four model parameters and an initial concentration. Three of the
seven lakes appear headed towards year-round volume averaged chloride concentrations
above the 230 mg/L chronic standard for impairment to aquatic habitat. The two lakes
with the lowest projected equilibrium concentrations of chloride have already reached
equilibrium. It is projected that one lake will take up to 40 years to reach equilibrium.
If road salt application rates are reduced in future winters, it is projected that the lakes
will respond with noticeably lower Cl- concentrations within 5 to 10 years. If road salt
applications are discontinued altogether, chloride concentrations are projected to reduce
to natural levels within 10 to 30 years in all seven lakes.
78
4.2 Introduction
Rising chloride concentration are present in many lakes located in urban environments
or near major roadways due to the application of road salt in the watershed [56, 87, 51,
108, 109, 97, 71]. Snowmelt runoff flows into these lakes through storm sewers, small
streams, overland flow and interflow. Road salt applications in rural areas can affect
lakes a few hundred meters away [6]. In urban environments runoff into the lakes is
extended by the presence of impervious surfaces and storm sewers providing a direct
path to the surface waters.
With increased chloride concentrations comes damage to the aquatic life. Ele-
vated chloride concentrations decrease the biodiversity of diatoms in lakes resulting
in halophilic taxa to increase in relative abundance [110]. Tadpoles of woodland frogs
have significantly lower survivorship, decreased time to metamorphosis, reduced weight
and activity, and increased physical abnormalities with increased salt concentrations
pointing to effects that could be affecting amphibians as a whole [9]. Flathead minnows
are affected at chronic concentrations as low as 298 mg/L [111]. Other aquatic species
have impacts at chronic levels ranging between 194 mg/L for sensitive species such as
various daphnia taxa, to 327 mg/L for the snail, Physa gyrina, to 561 mg/L for cad-
dis flies, Anaobolia nervosa and lemnephilis stigma, to 1,036 mg/L for bluegill sunfish
[59]. Not only are surface water communities affected, but also the biodiversity in lake
benthic sediments [109].
Over 317,000 tons of NaCl is being applied to the roads in the Minneapolis/St. Paul
Twin Cities Metropolitan Area (TCMA) with over 70% of the chloride being retained
and not flushed through runoff into the Mississippi River [112]. One of the sinks for
chloride in the watershed are lakes with seasonal chloride stratification and rising vol-
umetric chloride concentrations [71]. Background chloride concentrations before urban
development were around 3-10 mg/L [14]. From 1970 to 2000 in the TCMA significant
changes in lake chloride concentrations were detected using diatom assemblages with a
strong correlation to the percent of urban developments in each of the watersheds stud-
ied [13]. Similar increasing trends in chloride concentrations (an average of 1.5mg/L
per year and a range between 0.1 to 15 mg/L per year) were detected in 38 lakes of the
Twin Cities Metropolitan Area. That trend was correlated with the amount of rock salt
79
purchases by the state of Minnesota [71]. Median concentrations in the 38 lakes in 2005
were 87 mg/L well above the 3-10 mg/L observed during predevelopment times [71].
The objective of this study is to investigate chloride concentration trends in lakes
from a mechanistic point of view and determine if a 0-D lake chloride model can be
used to project seasonal salinity fluctuations and future lake chloride concentrations
based on recently acquired year round monitoring data. While chemical stratification
is common in lakes receiving runoff with high concentrations of salts our main interest
is not in the spatial distribution of chloride in lakes, but in the total amount of chloride
contained in each lake, and the variation of this chloride content over time. A water
quality model simulating inflow, accumulation and flushing of Cl- was created. The
model formulation, validation and model projections will be described. Lakes located
in the TCMA were used to simulate seasonal salinity cycles, long-term trends, ultimate
equilibrium chloride levels, and responses to reduced road salt application rates using
this model.
4.3 Lake Chloride Model Fomulation
4.3.1 Zero-dimensional model formulation
A model simulating the volume-weighted average chloride concentration C(t) in a lake
was formulated and used. The total amount of chloride (kg) in a lake is the volume-
weighted average concentration C(t) multiplied by the volume of the lake. The behavior
of C(t) in a lake can be reproduced by a 0-dimensional (0-D) model simulating inflow,
accumulation and flushing of Cl- over time. 0-D models have been used extensively
and very successfully to simulate phosphorus management scenarios for eutrophication
control of lakes [113, 114].
4.3.2 Daily time scale model
Chloride is a highly soluble substance that is not easily removed by chemical reactions
or biological processes once it is solution. In the model Cl- is therefore treated as a
conservative substance and the lake is treated as being fully mixed at all times. It is
assumed that chloride is added at a constant rate to the lake during the months when
80
snowmelt runoff occurs and that flushing occurs during the open water season at a
constant flowrate. The equations used (Eq. 4.1 and 4.2) for this model represent a fully
mixed continuous flow reactor for a conservative material (chloride) that is added at a
constant rate during one period and flushed at a constant rate during another.
Loading phase :dC
dt=M/D
V(4.1)
Flushing phase :dC
dt= −K ∗ C (4.2)
where M is the mass (g) of chloride added to the lake in the winter. D is the number
of days during which chloride is added to the lake, V is the lake volume (m3), K is
the flushing rate coefficient equal to 1/T, where T = V/Q is a hydraulic residence time
(days), and C is the volume-weighted average chloride concentration (mg/L). Solving
the differential equations (4.1) and (4.2) for these two phases with their respective initial
conditions results in equations (4.3) and (4.4).
@ t = tmin, C = Cmin : C(t) =M/(tmax − tmin)
V(t− tmin) + Cmin (4.3)
@ t = tmax, C = Cmax : C(t) = Cmaxe− 1
T(t−tmax) (4.4)
where t (days) is the day number in a particular year (t = 1 represents Jan 1 and
t = 365 represents Dec 31), tmax is the day number when the maximum concentration
(Cmax) is reached after all of the loading has occurred and tmin is the day number when
the minimum concentrations (Cmin) is reached after all of the flushing has occurred.
The other two variables M (g) and T (days) are mass and residence time, respectively,
as defined previously.
Equations (4.3) and (4.4) describe the seasonally cyclic nature of the Cl- concentra-
tion in the lake, starting at a minimum concentration in the late fall, accumulating to a
maximum concentration in the late winter and then flushing the salt out to a minimum
concentration in the following fall. By setting an initial value for Cmin, solving equation
(4.3) until the day equals tmax the value for Cmax can be obtained for equation (4.4).
This equation can then be solved until the day equals tmin thus obtaining the new Cmin
81
value to be used in equation (4.3). This cycle is repeated describing a time series (with
a daily time step) of chloride concentrations in the lake based on the mass of chloride
M that is entering the lake in a cold season, the lakes material residence time T, and
the dates when loading and flushing begin, tmin and tmax, respectively.
Two informative values in equations (4.3) and (4.4) are the minimum and maximum
concentrations. They tell the lowest and highest chloride values that can be reached in
a lake for a particular year. These parameters can be used to assess the stresses on the
aquatic life within a lake due to chloride, both the maximum concentration the aquatic
life will have to live in and the sustained concentration that will be felt throughout the
entire year. Equation (4.3) and (4.4) can be adjusted to an annual time step and solved
for the maximum and minimum concentrations in each year.
Setting C = Cmax and t = tmax in equation (4.3), setting C = Cmin and t = tmin in
equation (4.4), and introducing Tf = (tmin - tmax ) (the number of days in a year that
flushing occurs), allows the conversion of equations (4.3) and (4.4) to equations (4.5)
and (4.6) which define the maximum and minimum concentrations that can be obtained
in a particular year i.
Cmax(i) =M
V+ Cmin(i−1) (4.5)
Cmin(i) = Cmax(i)e−
TfT (4.6)
Equations (4.5) and (4.6) can be used to determine how the maximum and minimum
concentrations in a lake change from year to year based on the mass of chloride M(g)
entering the lake, the volume of the lake V(m3), and the length of a lakes flushing period
Tf = (tmin - tmax) relative to the hydraulic residence time T, i.e. Tf /T.
If the annual salt loading of a lake and the summertime flushing remain the same
year after year, each of the lakes will eventually come to a point where the amount of
salt entering that lake during the snowmelt runoff is equal to the mass of salt leaving the
lake due to flushing. At this point the minimum and maximum concentrations reached
from year to year will be the same. When this equilibrium is reached Cmin(i) will equal
Cmin(i−1) and equations (4.5) and (4.6) can be solved for Cmax(i) and Cmin(i) that are
then defined as the equilibrium concentrations Cmax(eq) and Cmin(eq) in equations (4.7)
82
and (4.8).
Cmax(eq) =M/V
1− e−Tf /T(4.7)
Cmin(eq) =M/V
eTf /T − 1(4.8)
The long-term effect of salt applications within a lakes watershed can be determined
from equations (4.7) and (4.8) if the total amount of salt M (g) entering the lake in a
winter season and the lakes hydraulic residence time (T ) are known and are constant.
Residence time (T) is related to lake volume (V) and water outflow rate (Q) from a
lake as T =V/Q. Since volumes of individual lakes in the TCMA are fairly constant
in the long term, except under severe drought conditions, the hydrology of a lakes
watershed has to remain fairly unchanged to assure a constant residence time T. How
the equilibrium concentrations would change based on reductions or increases in salt
applications in a lakes watershed can also be studied using the above equations.
4.3.3 Annual time scale model
The lake can also be modeled at an annual time scale. How the annual average con-
centration in the lake is changing from year to year can be determined from equation
(4.9).
VdC
dt= M∗ −QC (4.9)
where V (m3) is the volume of the lake, M∗(g/yr) is the total mass (rate)of chloride
added to the lake each year, Q is the total outflow from the lake and C is the current
annual average concentration in the lake. This equation can be solved with the initial
condition @ t = 0, C = Co. The solution is in equations (4.10 and 4.11).
ln
[M∗
V T − Co
M∗
V T − C
]=
t
T(4.10)
C =M∗
VT −
(M∗
VT − Co
)e−t/T (4.11)
83
where T = V/Q is again the residence time. At equilibrium, where dC/dt =0, the
annual average concentration would be:
CE =M∗
VT (4.12)
Equation 4.11 can be solved for the time necessary to reach x% of the equilibrium
concentration. (x = 100% requires an infinite amount of time, and x = 97% is a
considered a reasonable approximation). By substituting equation 4.12 and solving
equation 4.11 when C = .97 * CE @ t = tE equation 4.13 is created. This equation can
be used to find an estimate of the time it will take for a lake to reach an equilibrium
chloride concentration.
tE = ln
[CE − Co
0.03CE
]T (4.13)
4.3.4 Model assumptions
The five-parameter zero-dimensional model simplifies the actual lake processes consid-
erably, yet will be shown to capture the principal behavior of the time-variable chloride
concentrations. It is appropriate to briefly describe the actual inflow, mixing and out-
flow processes that produce the observed flow-weighted chloride concentrations, in order
to highlight the model simplifications.
The first minor shortcoming of the model is that the water budget is ignored, and a
constant lake volume is assumed. During the loading phase (tmin to tmax ) only dissolved
material (chloride), but no water is added to the lake. It is assumed that there is a net
inflow of chloride into the system during this phase and that any exported chloride is
outweighed by the mass entering the lake. The water flow rates into and out of the lake
are assumed to be equal. The outflow of water from the lake during the flushing phase
is also not explicitly accounted for although it is assumed to be equal to any inflow,
and the lake water budget is again ignored. A volumetric water outflow rate is hidden
in the residence time T of the chemical, which is equal to the hydraulic residence time,
i.e. the ratio of lake volume V divided by the water outflow rate, because the chemical
is conservative. During this flushing phase a net export of chloride is assumed, and
any delayed inflow of chloride through subsurface flows into the lake is assumed to be
84
outweighed by the flushing of chloride from the system.
The second assumption is that concentrations in the model are volume-weighted
averages for the entire lake, as if the lake were completely mixed all the time. How-
ever, strong chloride concentration gradients have been observed in TCMA lakes in
spring. The deepest lake waters typically have the highest chloride concentrations be-
cause snowmelt runoff containing dissolved sodium chloride flow to the bottom of a
lake as a density current [93, 71]. Since lake outflows are typically from the surface,
the saline water at the bottom cannot be flushed out until the lake has become fully
mixed vertically. Chloride-laden salt water at the bottom of a lake can also penetrate
by convective mixing into the pore system of lake sediments [71]. Some of this salt can
re-enter the water column after lake-mixing events. The net effect is an extension of the
residence time T of chloride in a lake when compared to the water residence time.
These assumptions would point towards the need of a 1-D model that accounts
for vertical stratification. However, a 0-D model is a very useful tool and sufficient
for the analysis of seasonal and long-term trends in overall lake salinity. Phosphorus
management in lakes for the control of eutrophication has benefited from 0-D modeling
since the 1970s. 0-D phosphorus models have been applied to lakes as large as the
Laurentian Great Lakes [113, 114].
Our 0-D lake salinity model has five parameters: the mass of chloride from road salt
(NaCl) entering the lake (M), the material residence time (T), the day (tmin) when the
average concentration in the lake has reached a minimum and new salt begins to enter
the lake, the day (tmax) when the concentration in the lake has reached a maximum and
flushing starts to dominate over salt accumulation, and the initial concentration (Co)
before the first year simulated. To obtain values of the five parameters for seven lakes
in the TCMA, the model was fitted to data (16 to 33 data points per lake) collected
over up to 5 years.
4.4 Lake data collection and model calibration
Field data from 13 lakes of the Twin Cities Metropolitan were available for periods
of up to five years [93, 71]. The model was applied to seven of the lakes with the
longest records and the characteristics given in Table 4.1 [93, 71]. Lakes were sampled
85
every 4-6 weeks between 2/15/2004 and 10/20/2008. All of the lakes were natural lakes
with inflows coming from streams, storm sewers or overland flow. Vertical profiles of
specific conductance were measured in the water column every 0.5 meters at the deepest
location in each lake using a YSI Model 63 probe [91]. A relationship between specific
conductance and chloride was previously determined [71], and the measured specific
conductance values were converted to chloride concentrations using that relationship.
This relationship existed because chloride and sodium ions were the dominant drivers
in changes in salinity. All other ions remained relatively constant throughout the year.
Table 4.1: Lakes modeledMaximum Lake Impervious
Lake Lake Lake Surface Watershed watershedname Volume Depth Area area area
(m3) (m) (ha) (ha) (%)Bryant 3,245,000 13.7 65.2 901 24Cedar 4,433,000 15.5 68.4 537 28McCarron 2,151,000 17.4 27.6 549 24Parkers 1,414,000 11.3 36.9 340 27Ryan 295,000 11 7.6 77 34Sweeney 952,000 7.6 26.7 1512 37Tanners 1,848,000 14 28.3 214 33
Volume weighted average chloride concentrations were determined for each of the
sampling dates [93]. The four model parameters (M, T, tmin tmax) were estimated
by fitting the model to the data. An initial concentration (Co) set at time tmin of
the first year of data was also determined. Least square errors between measurements
and model results were used to determine the best-fit model. A program was created
to cycle through permutations of the four parameters plus the initial concentration
until a combination was found that had the lowest root mean square error (Eq. 4.14)
between the model values and the measured values using the entire time series of the
measurements.
RMSE =
√(Cmodel(t)− CObserved(t))2
N − 1(4.14)
Numerical solutions of equations (4.3) and (4.4) with a time step of 1 day were used
for this simulation. Cmin and Cmax were calculated by applying equations (4.3) and
86
(4.4) sequentially. Once the best-fit parameters had been determined, simulations were
extended in time to project how chloride concentrations may change in the future, and
what maximum concentrations are expected if current loading and flushing conditions
continue. Estimations were made for the equilibrium concentrations using equations
(4.7) and (4.8) along with the time required to reach concentrations within 97% of
equilibrium if conditions were to remain constant. Finally simulations were run to
determine how changes in the amount of NaCl entering the lakes would influence the
final equilibrium concentrations of chloride.
4.5 Results
The best-fit model parameters for the seven simulated lakes are given in Table 4.2. tmin,
tmax, M and T and the initial concentration Cmin,o at the beginning of the simulation,
i.e. in the fall of the first simulated year (i = 1), is shown. Model simulations and
data are displayed in Figure 4.1 for all seven of the lakes. Identical patterns of chloride
accumulation in the cold season and flushing in the summer are apparent. With the
best-fit parameters, the model was used to project future equilibrium concentrations in
the seven lakes under different salt loading conditions.
Table 4.2: Model parameters. Cmin,o is the chloride concentration at the beginning ofthe simulation in fall (tmin) of the first simulated year (i=1). RMSE (%) is the ratioof root mean square error to average concentration over the record length. N is thenumber of data points used for model fitting.
tmin tmax M T Cmin,o RMSE N(mo/day) (mo/day) t/yr (yrs) (mg/L) (%)
Bryant 25-Dec 11-Feb 58 14 80 2.8 21Cedar 20-Oct 25-Feb 81 7 87 3.4 26McCarron 15-Dec 14-Feb 44 8 97 2.9 33Parkers 17-Oct 18-Mar 78 4.5 98 6.3 18Ryan 20-Oct 11-Feb 7 4 94 9.5 27Sweeney 17-Nov 14-Mar 104 3 113 7.7 16Tanners 23-Nov 21-Feb 37 7 145 3.5 16Average 14-Nov 24-Feb 58 6.8 102 5.16 22
Figure 4.2 illustrates how the chloride concentrations change with time, and how
87
21
Figure 4.1: Modeled and observed chloride concentrations in seven lakes of the TwinCities metropolitan area, Minnesota.
88
equilibrium is reached under four different chloride (salt) loading scenarios. The sce-
narios are: (a) current conditions continue in the future (1M), (b) loading is increased
by 50% (1.5M), (c) loading is decreased by 50% (0.5M) and (d) salt applications are
stopped and loading is reduced to 0 (0M). Figures 4.1 and 4.2 were created by using
the best-fit parameters for M, T, tmin and tmax (Table 4.2) in equations (4.3) and (4.4).
Cmax and Cmin for every year (i) were obtained from equations (4.5) and (4.6).
Equilibrium concentrations were determined by solving equations (4.7) and (4.8)
with the parameters listed in Table 4.2 and are given in Table 4.3. Another important
parameter is the time it will take to reach equilibrium. To obtain this value the con-
centrations were examined at an annual time scale. An initial concentration (Co) was
determined by averaging the simulated data from equation 4.3 and 4.4 between 1/1/2008
and 12/31/2008. The annual average equilibrium concentrations were also calculated
using the parameters in Table 4.2 and equation 4.12. These values were then inserted
into equation 4.13 to determine how long it would take for the lake to reach a concentra-
tion within 3% of the equilibrium concentration. Values obtained were between 0 and
41 years. If the equilibrium concentration was lower than the initial concentrations it
was assumed that the lake had already reached equilibrium and the time to equilibrium
was set to 0.
Table 4.3: Maximum (Cmax(eq)) and minimum (Cmin(eq) ) chloride concentrations atequilibrium determined by equations (4.7) and (4.8). C2008 is the average annual chlorideconcentration in the lake between 1/1/2008 and 1/1/2009 and is used as Co in equations(4.13) to find the time required to reach equilibrium (tE).
Cmax(eq) Cmin(eq) C2008 CE tE
(mg/L) (mg/L) (mg/L) (mg/L) (yrs)Bryant 259 241 114 250 41Cedar 137 119 111 128 10McCarron 174 154 131 164 15Parkers 277 222 178 248 10Ryan 107 84 103 95 0Sweeney 385 276 257 328 6Tanners 150 130 150 140 0
The observed seasonal patterns of lake chloride concentrations matched the model
results with an RMSE between 2.8 and 9.5%. On average, accumulation of chloride
89
22
Figure 4.2: Projected future chloride concentrations under four road salt loading condi-tions. Current loading (1M), 50% increase in loading (1.5M), 50% decrease in loading(0.5M) and zero loading (0M).
90
in the lakes started on Nov 14, and ended about 3 months later on Feb 24. Flushing
was evident during the remaining nine months in spring, summer and fall. Annual
fluctuations between maximum and minimum chloride concentrations are from 18 to 23
mg/L in five of the lakes, 55 mg/L in Parkers Lake and 109 mg/L in Sweeney Lake.
In five of the lakes (Cedar, McCarron, Parkers, Sweeney, and Bryant) volume-
weighted average chloride concentrations have been rising, both in the simulations and
the data. This shows that the lakes have not reached equilibrium with the amount of
salt applied in their watersheds annually. Two of the lakes have slight decreasing trends
(Tanners and Ryan) indicating that chloride concentrations had reached equilibrium
and fluctuations are possibly occurring due variations in salt application rates from
year to year. Current concentrations in Ryan and Tanners Lakes are slightly above (by
8 and 10 mg/L) their volume-weighted projected equilibrium Cl- concentrations of 95
mg/L and 140 mg/L, respectively. Two lakes (Cedar and McCarron) are currently 17
and 33 mg/L below their equilibrium concentrations of 128 and 164 mg/L, respectively.
Three lakes (Parkers, Bryant and Sweeney) are currently 70 to136 mg/L below their
equilibrium concentrations of 248, 250 and 328 mg/L, respectively. With current road
salt application rates, the two lakes (Tanner and Ryan) with the lowest equilibrium con-
centrations have already reached equilibrium, four will reach it in about 5 to 15 years,
and Bryant Lake with the second highest equilibrium concentration will take more than
40 years to reach it.
Three equilibrium concentrations for current road salt application rate are above
the 230 mg/L chronic level for impairment to aquatic life. Even though the other four
lakes are not projected to reach such high concentrations throughout the water column,
the standards may be exceeded at the bottom of the lake in winter and spring due to
salinity stratification. In Tanners Lake, for example, current volume-weighted chloride
concentrations are on average 150 mg/l, but concentrations as high as 400 mg/L have
been measured near the bottom of the lake after snowmelt events [71].
It is also of interest to examine how model parameters relate to watershed and
lake characteristics. Annual chloride loading (M ) of the seven lakes obtained from the
model fit are between 7 and 104 t/yr. Watershed areas range from 77 ha (Ryan) to
1512 ha (Sweeney) of which 24 to 37% are impervious surfaces. Road salt is applied
on impervious areas, and chloride loading rates per unit impervious watershed area are
91
given in Table 4.4 for each of the seven lakes. The annual salt application rates on
the impervious areas vary from 186 kg/ha to 850 kg/ha with an average of 445 kg/ha.
This is much lower then the average application rates in the major streamsheds each
of the lakes are located in of 2200 kg/ha impervious area [112]. The flushing rates are
really small, ranging from 2.3 to 20 L/s. This corresponds to only 60 to 370mm per
year with an average of 204mm per year of runoff from the impervious areas. This
is much lower than the typical annual precipitation of about 800 mm/yr in the Twin
Cities metropolitan area.
Table 4.4: Chloride loading rates (M) per impervious watershed area (Aimp) , flushingflow rate (Q = V/T ), and flushing rate (Q) per impervious watershed area, determinedby fitting of model parameters to measured lake chloride concentrations.
M/Aimp Q=V/T V/(T Aimp)(kg ha−1 yr−1) (L s−1) (mm/yr)
Bryant 269 7.3 110Cedar 540 20.1 150McCarron 333 8.5 120Parkers 850 10 340Ryan 267 2.3 280Sweeney 186 10.1 60Tanners 524 8.4 370Average 445 10.1 204
4.6 Discussion
4.6.1 Model Sensitivity
The maximum chloride concentration in a lake due to road salt applications depends
on three parameters: the annual mass of chloride entering the lake M, the material
residence time T and the lake volume V (Equations 4.7 and 4.8). Changes in any of
these parameters would influence chloride concentrations in the lake. For a lake with the
same residence time and volume, doubling the entering chloride mass M would cause a
doubling of the equilibrium concentrations. Likewise if the mass entering the lake were
cut in half the equilibrium concentration would be cut in half. These changes in the
mass of chloride entering the lake are shown in Figure 4.2.
92
The residence time T has a large influence on the final equilibrium concentrations in
the lake. In Lake McCarron the entering mass/volume (M/V) ratio is 20 mg/L while in
Bryant Lake that ratio is 18 mg/L. Even though the amount of chloride entering Lake
McCarron per lake volume every year is larger, the equilibrium concentration is much
lower, i.e. 174 mg/L and 259 mg/L for Lake McCarron and Bryant Lake respectively.
The equilibrium concentration is proportional to residence time (equation 4.12).
Lake volume has an inverse relationship with the equilibrium concentrations. If two
lakes had the same residence times and the same mass of chloride entering the lake, but
one lake had twice the volume, the equilibrium concentrations in the larger lake would
be half as high as in the smaller lake (equation 4.12).
In summary, changes in any of the three model parameters ( M, V and T) in the
future would influence the final equilibrium concentrations. Therefore, projections of
lake concentrations have been made with the assumption that current conditions will
continue in the future.
4.6.2 Model projections
While increasing chloride concentrations in 38 Twin Cities area lakes were observed
between 1984 to 2005 [71], if the application rates and lake parameters remain constant
the chloride concentration in these lakes would level off in the future eventually reaching
equilibrium. The assumption of constant application rates and lake parameters may
be correct for inner city lakes where development and road expansion have reached
a maximum, however, expanding roadways and increasing population densities in the
suburbs may push road salt application rates in some lake watersheds higher.
Climate, population, urban development and road salt application rates are dynamic
variables that can influence future chloride concentrations in urban lakes. Increased
precipitation in Minnesota is expected under climate change scenarios [115, 116]. More
days with precipitation and increased intensity of rainfall events in Minnesota are pre-
dicted resulting in more runoff reaching the lakes. The elevated runoff volume would
enhance the flushing of lakes causing lake residence times and equilibrium concentra-
tions to decrease. However, increased snowfall amounts and more snowfall events are
also projected causing higher road salt application rates and increased lake equilibrium
concentrations.
93
In addition, changes in populations and/or impervious surfaces in the lake water-
sheds would influence the final equilibrium concentrations. In the Twin Cities metropoli-
tan area the population is expected in rise by 30% from 2.8 million in 2008 to 3.6 million
by 2030 [117]. With this expansion come more roads and wider highways elevating the
amount of salt applied in the lake watersheds and exposing new lakes to chloride loads.
Impervious surfaces would also cover larger areas leading to higher flowrates entering
into the lakes, possibly decreasing the lakes residence times, but also increasing the flow
of salt into the lakes.
Another factor influencing the final equilibrium concentrations in the urban lakes is
training and awareness of best management practices (BMPs) designed to reduce the
amount of salt applied in a watershed. With added awareness of the environmental
impact of road salt applications, BMPs on how to more effectively apply road salt or
reduce its impact on water bodies, and alternative deicers that do not contain chloride,
decreases in road salt application rates could be expected. If practices were changed,
chloride concentrations in the lakes would quickly decrease since the hydraulic residence
time (T) in the Twin Cities urban lakes is typically small (3 to 14 years). It is uncertain
how much of the salt is being stored in the sediments or how much is also being stored
in the groundwater feeding the lakes, however rapid changes would still be expected if
the mass of salt entering the lakes were dramatically reduced. As shown in Figure 2,
if road salt applications were eliminated it would take only 10 to 30 year for chloride
concentrations to reach the level of predevelopment values of 3-10 mg/L [14]. Even
if chloride applications were reduced by only 50%, concentrations in all seven lakes
would be reduced to levels below the chronic standard (Figure 4.2). Current stormwater
management in the Twin Cities favors the routing of surface runoff to lakes and wetlands.
If the runoff is from rainfall, this practice may be favorable, although water quality
has to be considered. If the runoff is snowmelt water, the practice has unfavorable
consequences.
4.7 Conclusions
A model was successfully used to simulate the chloride seasonal cycle of loading and
flushing as well as the long-term accumulation of chloride in urban lakes affected by
94
road salt applications. With monthly data from several years, the 5-parameter model
was used to determine long-term equilibrium concentrations in a lake if hydrologic con-
ditions and salt loading rates remain constant as well as simulations based on either
reduction or increased loading. Seven lakes in the Twin Cities metropolitan of Min-
nesota area were modeled. Using five years (2004-2008) of monthly salinity profiles,
four model parameters and an initial concentration were determined and subsequently
used to project future chloride concentration in each of the lakes under several road salt
application scenarios. The following average model parameters were determined from
the lake data: an annual chloride loading rate of 445kg per ha of paved surface in the
watershed, a hydraulic residence time of 6.8 yrs, and an average flushing rate of 10 L/s
in the seven lakes studied. From the simulation it was determined that 3 of the 7 lakes
will reach chloride concentrations year round throughout the water column above the
230 mg/L standard for chronic impairment to biota under current salt loads. If road salt
applications were stopped or the high salinity water from snowmelt events was diverted
from the lake concentrations could be reduced to predevelopment concentrations of 3-10
mg/L within 10-30 years.
Aknowledgements
Funding for the project, especially the data collection, was provided by the Local Road
Research Board, St. Paul, MN and the James L. Record Fund, University of Minnesota.
The University of Minnesota provided a Doctoral Dissertation Fellowship for the senior
author.
Chapter 5
Road salt impact on vertical lake
mixing
Eric V. Novotny and Heinz G. Stefan
St. Anthony Falls Laboratory,
Department of Civil Engineering, University of Minnesota
Minneapolis, Minnesota 55414
95
96
5.1 Abstract
Runoff from roadways on which road salt (NaCl) has been applied for driving safety
in winter can form a saline water layer at the bottom of a lake, pond, reservoir or
river impoundment. Natural vertical mixing of such lentic surface water bodies can be
hindered by this benthic saline layer. To study the formation and disappearance of the
saline layer temperature and specific conductance profiles were measured intermittently
over two years (2007, 2008) in eight urban lakes of the northern temperate region and
recorded at high frequency during one year (2009) in one lake. A deterministic dynamic
1-D lake temperature and salinity model was developed and used to simulate the summer
stratification and mixing dynamics in Tanners Lake, Oakdale, Minnesota. Erosion of the
saline layer in the spring occurred in only one of the three years examined (2007). In the
other two years (2008 and 2009), the saline layer persisted throughout the summer, and
was destroyed only by fall turnover and mixing between the epilimnion and hypolimnion
when thermal stratification was at a minimum. Density stratification was dominated
by salinity after ice-out, but was quickly overtaken by temperature stratification as the
epilimnion warmed. Inclusion of the lake number in the calculation of the hypolimnetic
eddy diffusion parameter made the mixing in the hypolimnion stronger when the lake
stratification became unstable in the fall and spring and weaker in the summer after
thermal stratification had formed. It was demonstrated that the saline benthic layer
prevents dissolved oxygen from reaching the lake sediments. Overall the results show
how salinity from road salt applications can influence water quality and natural mixing
in urban lakes.
97
5.2 Introduction
Sodium and chloride concentrations have been on the rise in lakes, streams and ground-
water in northern regions where road deicing salt (NaCl) is applied [85, 65, 3, 88, 23, 118,
71, 86, 112, 51, 97, 5]. Lakes receive sodium and chloride from roadways by snowmelt
runoff directly through overland flow, streams and storm sewers within the watershed,
or indirectly through the soil and groundwater. Salt concentrations in urban streams
and drainage systems are sufficiently high during the winter months to cause density
currents and chemical stratification in the receiving water bodies, especially lakes, deten-
tion ponds and reservoirs. This phenomenon occurred synoptically with above freezing
air temperatures and snowmelt runoff in a Minneapolis lake. The saline water flowed to
the deepest part of a small lake where it remained until spring [54]. The density change
caused by dissolved NaCl is small, but significant in relation to temperature-induced
density changes. For example, a temperature change from 4 to 5oC produces the same
specific gravity change as a NaCl concentration of 10 mg/L [55].
A saline water layer can cause a lake to become permanently density stratified. In
such a meromictic lake the bottom waters never mix with the surface waters. The con-
sequences of a meromictic lakes often include dissolved oxygen depletion in the benthic
saline layer and high concentrations of phosphate, ammonia, and hydrogen sulfide at
the sediment water interface. Small lakes and deep lakes are more vulnerable to be-
coming meromictic than large lakes and shallow lakes [6]. The formation of meromictic
conditions due to road salt applications has been reported for a few individual small
lakes or ponds [87, 88]. No meromictic lakes due to road salt application have been
found in the Twin Cities metropolitan area of Minnesota, but monomictic behavior has
been observed [71]. In these monomictic lakes full mixing is prevented during the spring
overturn period, but not during the fall. The formation of meromixis or even monomixis
is important because it can have serious ecological consequences for a lake.
In addition to monomictic behavior, rising overall concentrations and seasonal cy-
cles of sodium and chloride ion concentrations have been observed in lakes of the Twin
Cities metropolitan area [71]. A 0-D model was previously developed and used to
98
project long-term salinity trends and seasonal salinity cycles [86]. The 0-D model cap-
tured volumetrically-averaged salinity concentrations, but a 1-D model lake stratifica-
tion model is needed to capture the dynamics of vertical salinity stratification in a lake
from the high concentrations at the bottom to the low salinity in the surface waters.
The main objective of this paper was to demonstrate the influence of saline water
inflow from road salt applications on the stratification dynamics of a freshwater lake.
This includes (1) the formation of a benthic saline layer, (2) the effect on the vertical
mixing mechanics of a lake including the disruption of natural turnover events, (3)
the dissipation of the saline layer during the summer and fall seasons, and (4) the
consequences of the saline layer for oxygen transfer dynamics throughout the water
column. To pursue these objectives a combined field study and modeling approach was
adopted. The field study had two components: (1) measuring monthly temperature and
salinity profiles over a period of several years and (2) continuous sensing and recording
of vertical temperature and salinity profiles. Both research components were conducted
in a lake located near a major interstate highway in the Twin Cities metropolitan area.
The simulation study also had two components: (1) simulate lake stratification and
vertical mixing in a lake during the open water season following a winter in which a
saline benthic layer had formed and (2) simulate vertical dissolved oxygen transfer in a
lake with a benthic saline layer had formed.
In the deterministic model simulations, principles and governing equations previ-
ously used in 1-D lake temperature simulation models were applied and extended. The
extended model was based on the MINLAKE hydrothermal model, which has been
used successfully to simulate lake temperature stratification in many individual lakes
[119, 120, 121, 122]. The model was extended to include density gradients due to salinity
and the Lake Number [123] in the calculation of effective hypolimnetic diffusion coeffi-
cients. To illustrate the consequences of the benthic saline layer on lake water quality,
the dissolved oxygen profiles in a lake without and with a saline layer were simulated.
99
5.3 Methods
5.3.1 Field Investigation: Data Collection/Sampling Site
Data were collected in Tanners Lake in the eastern Twin Cities metropolitan area (Oak-
dale, MN). Tanners Lake is located next to Interstate Highway I-94 and a high volume
county road (Figure 5.1a). The lake receives runoff from a 214 ha watershed area of
which 33% is covered by impervious surfaces [71]. The lake has a surface area of 30 ha
(0.30 km2), littoral area of 11 ha (0.11 km2) and a maximum depth of 14 m [124]. The
depth area profile for Tanners Lake is shown in Figure 5.1b.
TannersLake
´ 0.5Kilometers
§̈¦I-94
")120
(a)
!"!!#
$"!!#
%"!!#
&'"!!#
&("!!#
!"!!# &!"!!# '!"!!# )!"!!# $!"!!#
!"#$%&'()&
*+",&'%,)&
(b)
Figure 5.1: (a) Tanners Lake location in Oakdale, Minnesota and (b) Bathymetry ofTanners Lake
Data were collected in Tanners Lakes in two phases. In the years 2007 and 2008
specific conductivity/temperature profiles were measured in Tanners Lake, and eight
other lakes in the Twin Cities metropolitan area, at 4- to 6-week intervals [71]. These
measurements were made in the water column every 0.5 meters at approximately the
100
deepest location in each lake using a YSI Model 63 probe [91]. Supplemental data
for Tanners Lake collected by the Ramsey-Washington Watershed District in Tanners
Lake were obtained from the Minnesota Pollution Control Agency Environmental Data
Access website (http://www.pca.state.mn.us/data/edaWater/index.cfm). The District
takes profiles every two weeks between May and October.
In November 2008 a buoy system connected to a chain of sensors was installed in
Tanners Lake to monitor continuously temperature and specific conductance (Figure
5.2). Fourteen Sensorex CS150TC probes, installed at depth intervals from 0.5 m to
1.5 m with a higher concentration of probes in the bottom half of the lake, measured
temperature and specific conductance every two minutes. These sensors were connected
to a Campbell Scientific 32- channel relay multiplexor, which was connected to a Camp-
bell scientific CR-10X data logger. A Garmin GPS device was attached to the buoy
to record any movement from its original position at the end of the ice cover period.
Remote data access was installed for easy data retrieval from the laboratory.
The Sensorex probes measure voltage across resistors, which is converted to conduc-
tivity or temperature. The conductivity and temperature values were used to find the
specific conductance value at 25 oC. The probes were calibrated before being placed in
Tanners Lake. While the probes were operating in the lake, a verification/recalibration
was conducted. Temperature and conductivity profiles in the lake next to the buoy were
measured independently using a handheld YSI Model 63 probe. Profiles were taken on
11/19/2008, 2/24/2009 and 5/11/2009. These profiles were used to estimate creep in
the values recorded by the Sensorex probes. Temperature probes did not need to be
recalibrated.
5.3.2 Model Formulation: Simulation of Summer Stratification in a
Lake with a Benthic Saline Layer
Basic heat and salinity transfer equations
The 1-D temperature and salinity model is based on the following diffusion equations.
A∂T
∂t=
∂
∂z
(KzA
∂T
∂z
)+
Hn
ρwCp(5.1)
A∂C
∂t=
∂
∂z
(KzA
∂C
∂z
)(5.2)
101
Antenna Raven XTV CDMA Digital Cellular Modem
CR 10X Data Logger
AM16/32B Delay Multiplexer
Sensorex CS150 TC Temp/ Conductivity Probes
GPS16-HVS Geographical position receiver
SC932A interface
GPS516 – HVS RJ45 Cable
COAXSM-L cable (6ft)
Figure 5.2: Schematic of data acquisition and transmission system (”Buoy set-up”)to continuously record specific conductance and temperature profiles in Tanners Lake.Buoy has connection for remote data access.
102
where T(z, t) is the temperature of a water layer (oC) at time t (days) and depth z (m),
C is the total salinity expressed as specific conductance (µS/cm), A is the horizontal
area of the water layer (m2), Kz is the vertical effective diffusion coefficient (m2/d), Hn
is the strength of internal heat sources (kJ m−3 d−1), ρw is the density of the water
(kg/m3), Cp is the specific heat of the water (kJ/oC). Equations (5.1) and (5.2) include a
number of important assumptions: (1) Salinity is treated as conservative with no losses
of solute by chemical or biological processes. (2) changes in lake salinity are dominated
by the sodium and chloride ions derived from road salt. Previous studies [71] justify this
assumption. (3) Vertical transport of heat and of solute (salt) are analogous, i.e, the
same effective diffusion coefficient Kz can be used. (4) Because the salt layer is located
at the bottom of the lake and is associated with the colder heavier water during most
of the open water season double diffusion [125] can be ignored.
The boundary conditions include the heat flux across the lake surface between water
and air and the heat flux between water and sediments at the bottom of the lake. The
surface heat flux has to be calculated from daily weather data. The bottom heat flux
was ignored by imposing an adiabatic boundary condition at the bottom of the lake.
Computations progressed in daily time steps in the following sequence: The first
step was the computation of the surface heat flux using weather parameters and wa-
ter surface temperatures from the previous time step. This was followed by solving
equations (5.1) and (5.2) for vertical mixing by an effective diffusion coefficient (Kz).
Equations (5.1) and (5.2) were solved numerically in daily time steps and 0.5 m depth
increments using an explicit numerical scheme. Next, convective mixing was simulated
to remove density instabilities. If a layer had a greater density than the layer below
the two layers were mixed. Net convective mixing proceeded from the surface to the
bottom until the density profile was stabilized. Finally wind mixing was simulated to
determine the surface mixed layer depth.
Surface heat transfer
The air-water heat exchange at the lake surface can be estimated by equation (5.3)
[126].
Hn = Hsn +Han −Hc −He −Hbr (5.3)
where Hn is the strength of internal heat sources, Hsn is the difference between incoming
103
short-wave radiation and reflected short wave radiation, Han is the difference between
incoming long-wave atmospheric radiation and reflected atmospheric ration, Hc is the
heat loss from the water by conduction, He is the heat loss from the water body by
evaporation and Hbr is longwave back-radiation from the water to the atmosphere. The
net short wave radiation (Hsn) is defined by equations (5.4) to (5.6) [120].
Hsn(0) = (1− r)βHs (kJ m−2 day−1) (5.4)
Hsn(i) = Hsn(i− 1)exp(−µ∆z) (kJ m−2 day−1) (5.5)
µ = 1.84(ZSD)−1 (5.6)
Where Hs is the incoming solar radiation (kJ m−2 day−1), r is the reflection coefficient
defined by the albedo of the water surface (= 0.087; [127]), β is the surface absorption
factor (= 0.4; [128]), Hsn is the solar radiation at the top of each layer of water and µ
is the total shortwave radiation attenuation coefficient, which is related to secchi depth
ZSD by equation (5.6) [120]. The effect of long wave radiation was calculated using
equations (5.7) and (5.8).
Ha = σ∗εaT4a (kJ m−2 day−1) (5.7)
εa = (1− 0.261exp[−7.77 ∗ 10−4T 2a ])(1 + 0.17CC2) (5.8)
Where σ∗ is the Stefan Boltzmann constant (= 4.895*10-6 kJ m−2 K−4 day−1), Ta is
the air temperature (oK), εa is the atmospheric emissivity, and CC is the percent cloud
cover. The heat loss from convection was calculated using equations (5.9 and 5.10.
Hc = 0.47f(Ua)(Ts − Ta) (kJ m−2 day−1) (5.9)
f(Ua) = 86.32(9.2 + 0.45WFCTW2) (kJ m−2 mmHg−1 day−1) (5.10)
where f(Ua) is the wind function [126], Ts is the surface water temperature, WFCT is
the wind function coefficient to account for wind sheltering on the lake and W is the
104
daily average wind speed (m/s). The heat loss from evaporation was calculated by using
equations (5.11) to (5.13).
He = βbf(Ua)(Ts − Td) (kJ m−2 day−1) (5.11)
βb = 0.35 + 0.015Tm + 0.0012T 2m (mmHgC−1) (5.12)
Tm = (Ts + Td)/2 (5.13)
Where βb is the slope used to convert vapor pressures to temperatures [126] and Td is
the dew point temperature. Equation (Eq 5.14) was used to calculate back radiation.
Hb = εσ∗(Ts + 273.15)4 (kJ m−2 day−1) (5.14)
Where ε is the emissivity of water (=0.97).
Internal hypolimnetic mixing
The hypolimnetic effective diffusivity (Kz) was based on the maximum hypolimnetic
effective diffusivity and the stability frequency (N2) as expressed in equations (5.15)
and (5.16) [120].
Kz = 0.017Kzmax(N2)−0.43 (m2/day) (5.15)
N2 =g
ρ
(∆ρ∆z
)(s−2) (5.16)
Kzmax =α
LN(5.17)
where Kzmax is the maximum hypolimnetic eddy diffusion coefficient for a particular
day. Kzmax is dependent on α, a calibrated parameter, and the lake number (LN ). The
Lake Number is a dimensionless parameter relating the stabilizing forces from density
stratification to the destabilizing forces from wind and cooling [129]. The addition of the
Lake Number allows for Kzmax to change daily as wind speed varies and stratification
stability of a lake increases or decreases due to changes in temperature and salinity
profiles. The Lake Number has been used in other studies and models to simulate
105
hypolimnetic effective diffusion [130, 131]. The Lake Number is defined by equations
(5.18) and (5.19) [123].
LN =gSt(1− Zt/Zm)
ρmU∗2A0.5m (1− Zg/Zm)
(5.18)
St =1Am
∫ Zm
0(z − Zg)Az(1001− ρz)dz (5.19)
where St is the Schmidt Stability (kg m m−2), Zt is the thermocline height (m) defined
as the depth above the bottom of the lake with the largest density gradient, Zm is the
maximum depth of the lake (m), ρm is the density of the water at the surface (kg/m3),
U* is the water friction velocity due to wind stress (m/s) given later by equation (5.28),
Am is the surface area of the lake (m2), Zg is the center of lake volume in (m) above the
lake bottom, z is the height above the bottom (m), Az is the area of the lake a height
z (m2), and ρz is the density of water at depth z (kg/m3).
A Kz value was determined for each layer and then used in equations (5.1) and
(5.2) in an explicit numerical analysis scheme to solve for temperature and salinity
distribution with time. The minimum possible value for Kz is equal to the molecular
diffusion coefficient of heat in water (0.0125 m2/d) and the maximum value (0.216
m2/d) is determined from equation (5.20) using a relationship with lake surface area
[120]. This value is different from Kzmax in that Kzmax changes daily and can be lower,
but not higher than maxKz.
maxKz = 7.06 ∗ 10−3(Am)0.56(0.000075)−0.43 (5.20)
Convective mixing
Density instabilities throughout the water column develop during cooling of the lake
water from the surface. They lead to convective mixing in the water column. The
density of the water was determined using both temperature and salinity (equation
5.21).
ρw = ρT + ρS (5.21)
where ρT is the density of pure water based on its temperature and ρS is the density
increment of the water due to salinity. The change in density of pure water by temper-
ature alone is represented by equation (5.22) where T is the temperature of the water
106
[132]. This equation gives a maximum density of pure water at 3.98 oC temperature.
ρT = 999.869+6.6741∗10−2T−8.8556∗10−3T 2+8.2303∗10−5T 3−5.516∗10−7T 4 (5.22)
Salinity, i.e. the amount of dissolved salt in the water, adds to the density of pure
water. Salinity can be determined from a relationship with specific conductance given
by equations (5.23) and (5.24) [132]. Equation (5.23) is for high salinity (above 2000
mg/L) and equation (5.24) ) adjusts the value obtained in equation (5.23) for low salinity
(0 2000 mg/L). Equations (5.23) and (5.24) are for the ionic composition of sea water,
but are used here because, as in seawater, the major fluctuating solutes in Tanners Lake
are sodium and chloride [71].
S = 0.0080− .1692R0.5t + 25.3851Rt + 14.0941R1.5
t − 7.0261R2t + 2.7081R2.5
t (5.23)
S = S − 0.0081 + 1.5 ∗ 400Rt + (400Rt)2
(5.24)
where Rt is the ratio between the specific conductance values at 25 oC and the conduc-
tivity of standard seawater with a salinity of 35 g/L at 25 oC. Once the salinity of the
water is determined based on conductivity measurements the density increment due to
salinity can be determined from equation (5.25) [132].
ρS =S ∗ (0.824493− 4.0899 ∗ 10−3T + 7.6438 ∗ 10−5T 2 − 8.2467∗
10−7T 3 + 5.3875 ∗ 10−9T 4 + S1.5(−5.72466 ∗ 10−3 + 1.0277∗ (5.25)
10−4T − 1.6546 ∗ 10−6T 2) + 4.8314 ∗ 10−4S2
Convective mixing occurs if the density of water is greater in a layer above another
layer. This condition is unstable and induces convective mixing between the two layers.
Mixing continues downward until the density of the water increases from lowest to
highest throughout the water column going from the water surface to the lake bottom.
On occasion, the water temperature of a layer in the lake can increase or decrease
past the temperature of maximum density (TMD) during the daily time step to the point
where the new density of the layer is lower than that of the water layer below. This
apparent results masks the fact that during the period of cooling or heating the layers
temperature would have reached the point of maximum density resulting in instability-
induced mixing of the water layer of higher density above with the lower density layer
107
below it. This convective mixing could be missed due to the length of the time step
in the computations. Therefore a routine was added to the computations to check if
water temperature increased or decreased past TMD; if it did, convective mixing was
induced until the temperature of the overlaying layer reached a temperature past TMD
or until the density of the lower layer was higher than the density of the water at TMD.
Using equations (5.22) through (5.25), a linear approximation between TMD and specific
conductivity (C) was developed (equation 5.26).
TMD = 3.981− 1.22 ∗ 10−4C (5.26)
where TMD is in (oC) and C is specific conductivity in (/muS/cm ). According to
equation (5.26) a 0.22 oC decrease in the temperature of maximum density occurs for
every 1000 mg/L ( 1800 µS/cm) of salinity increase.
Surface wind mixing
The depth of the wind-mixed layer from the lake surface was determined from an en-
ergy balance consideration [133]. The ratio R (equation 5.27) is essentially the energy
transferred from the wind to the lake surface relative to the lifting work required to
deepen the mixed layer.
R =ρwWSCTU
∗3A∆tVm∆ρg(Zm − Zg)
(5.27)
U∗ = 0.0343W√CZ (5.28)
where ∆t is the time interval of one day, A is the surface area affected by wind, ρw is
the density of water, Vm is the volume of the surface mixed layer, ∆ρ is the density
difference between the mixed layer and the layer immediately below the mixed layer,
Zm is the depth of the mixed layer, Zg is the center of gravity of the mixed layer, CZ
is a drag coefficient on the water surface given by CZ = 0.0005√W when W < 15 m/s
or CZ=0.0026 when W >= 15 m/s [133]. U* is the wind induced water shear velocity,
W is the wind speed (m/s) and WSCT is the wind sheltering coefficient. When R is
greater that 1.0 mixing between the layers occurs. When R reaches a value below 1.0
wind mixing has reached it maximum depth.
108
Model calibration
Four model parameters were calibrated by minimizing the error between model results
and lake data. These parameters are WSCT , WFCT , α and ZSD. They appear in equa-
tions (5.27), (5.10), (5.17) and (5.6) respectively. The parameters WSCT and WFCT are
functions of wind sheltering. They represent the effective wind speed reduction for the
convective or evaporative heat transfer at the water surface, and for wind mixing at the
lake surface, respectively. The parameter α is used to determine the maximum vertical
effective diffusivity in the hypolimnion. The Secchi depth (ZSD) measures water trans-
parency, and is used to determine the attenuation coefficient of short wave radiation in
the lake water.
Simulations were run to obtain the best fit between the observed and modeled data
by changing the four calibration parameters. The set of parameter values that gave
the best combination of NSC-values between observed and modeled temperature and
specific conductance profiles was retained. This calibration was conducted with data
from the ice-free periods of 2008. The calibrated model parameter values were used for
model validation with data from 2007.
Weather data used as model input for the years 2007 and 2008 were obtained from the
Minneapolis/St. Paul International Airport (courtesy of Dr. X. Fang). The weather
station is about 19.8 km from the lake site. The weather data provided were daily
average values of air temperature (oF), dew point temperature (oF), solar radiation
(Langleys), wind speed (mph), and cloud cover (%). The values were converted to (oC)
for the temperatures, kj/m2 for radiation and m/s for wind speed (Figure 5.3).
5.3.3 Model Simulation of Dissolved Oxygen Transfer in a Lake with
a Saline Benthic Layer
Simulations were made to show how dissolved oxygen concentration profiles would
change in the lake under the following scenarios 1) uniform salinity concentrations
throughout the water column 2) observed salinity concentrations for 2008. The weather
data for the year 2008 were used along with the initial temperature profile. The initial
salinity profile was used for scenario 2 and a constant salinity was used for scenario 1.
A simplified dissolved oxygen model was used to simulate the vertical dissolved oxygen
109
0
10
20
30
Air
Tem
p (!
C)
-10
0
10
20
Dew
Poi
nt T
emp
(!C
)
5
10
Win
d sp
eed
(m
/s)
2,000
4,000
6,000
8,000
Sol
ar ra
diat
ion
(Kca
l/m2 )
04/18/07 07/27/07 11/04/070
0.5
1
Clo
ud C
over
(%
)
04/18/08 07/27/08 11/04/08
Figure 5.3: Weather parameters recorded at the Minneapolis/St. Paul InternationalAirport. and used as model input.
110
profile in the lake.∂O
∂t=
1A
∂
∂z
(AKz
∂O
∂z
)− SSOD (5.29)
where A, Kz and z are previously defined in equations 5.1 and 5.2, O is the dissolved
oxygen concentration (mg/L) and SSOD is the sediment oxygen demand (mg L−1 day−1).
All other sources and sinks of dissolved oxygen such as photosynthesis, plant respiration
and biochemical oxygen demand are ignored. Sediment oxygen demand (SSOD) is
defined by equations (5.30) and (5.31).
SSOD =Sb
A
∂A
∂z(5.30)
Sb = Sb20θT−20S (5.31)
where Sb is the sediment oxygen demand per unit area (g O m−2 day−1), A is the
horizontal lake area at a particular depth, and ∂A∂z is an estimate of the amount of
sediment surface area that is in contact with a particular water layer. A SSOD value
is calculated for each water depth. The Sb value is calculated using equation (5.31)
where Sb20 is an estimate of the sediment oxygen demand at 20 oC, θS is a temperature
adjustment coefficient and T is the temperature at the particular water depth. Sb20 is
estimated based on the trophic state of the lake. Tanners Lake is a mesotrophic lake. A
value of 1 g O m−2 day−1 was used for the value of Sb20 [134, 135]. Values for θS used
were 1.065 for T>10 oC and 1.130 for T <= 10 oC [136].
As a boundary condition, the DO concentration in the top layer of the lake was
always set to the saturation concentration of dissolved oxygen in water (equations (5.32)
and (5.33)) [136].
ln(CSO) =− 139.34411 +1.575701 ∗ 105
T− 6.642308 ∗ 107
T 2(5.32)
+1.2438 ∗ 1010
T 3− 8.621949 ∗ 1011
T 4
CS = CSO ∗ (1.0− 0.000035∆H) (5.33)
where T is the water temperature CSO is the saturation concentration at sea level and
CS is the dissolved oxygen saturation concentration adjusted for the elevation of the lake
111
above sea level (∆H (ft)). ∆H was set to 293.6 m [124]. The initial concentration profile
was set to 0 throughout the water column except for the surface layer, which was set to
the saturation concentration. In the computation of the DO profiles convective mixing
due to density instability and wind mixing in the surface layer were also accounted
for in separate computational steps, the same as in the transfer of salinity and heat
(temperature).
5.4 Results
5.4.1 Saline Layer Formation: Continuous lake monitoring results
The continuous record of water temperature and specific conductance profiles collected
in Tanners Lake from Nov 28 2008 to July 31 2009 showed the formation of a saline
water layer on the bottom of an urban lake in winter and the dissipation in spring
and summer. The conductivity probes experienced significant creep while in the lake.
Profiles were taken with the YSI Model 63 probe on Nov 19 2008, Feb 24 2009 and May
11 2009 and compared with daily average concentrations recorded by the Buoy (Table
5.1). ). On a plot of YSI data vs. buoy data a slope was determined representing the
daily creep for each of the buoy sensors. This daily creep value for individual probes
was subtracted from the recorded value for individual probes to produce the corrected
specific conductance values (Figure 5.4).
The water temperature and salinity record displayed the influence that runoff con-
taining road salt can have on a lake (Figure 5.5). In late fall of 2008 the salinity, defined
as the (specific conductance of the water,) was uniform throughout the water column.
As the winter progressed a saline water layer began to formed at the bottom of the lake.
The accumulation of saline water continued throughout the winter months resulting in
the formation of a saline layer approximately 5 meters thick above the bottom sediments
by April 2009.
The thickness of the saline benthic layers increased abruptly at certain times coin-
cident with daily average air temperatures above 0 oC (Figure 6 points A, B and C).
When the average daily air temperature reached above freezing causing the existing
snowpack to melt, the specific conductance (salinity) of the bottom waters in Tanners
Lake increased and/or the thickness of the saline layer expanded.
112
Table 5.1: Comparison of specific conductance recorded by the Buoy system to valuesmeasured with the YSI Model 63 probe. A slope representing the daily creep of theprobes was calculated using the difference between the values from the buoy system andthe values from a YSI Model 63 probe.Depth 11/19/08 2/24/08 5/11/08 Difference Slope
Buoy Probe Buoy Probe Buoy Probe 11/19 2/24 5/111.22 818 815 899 838 948 825 -4 61 123 0.732.13 818 814 897 838 889 829 -4 59 60 0.383.05 818 811 900 839 953 833 -7 61 120 0.736.1 818 820 935 864 978 842 2 71 136 0.787.62 818 804 927 890 933 850 -14 37 83 0.569.14 818 826 1064 965 1097 876 8 99 221 1.2210.36 818 821 1176 1070 1159 950 3 106 209 1.1810.91 818 818 1274 1140 1226 1000 0 134 226 1.3111.58 818 831 1388 1240 1412 1070 13 148 342 1.8812.19 818 815 1399 1300 1423 1230 -4 99 193 1.1312.8 818 830 1468 1340 1535 1320 11 128 215 1.1713.41 818 814 1491 1394 1583 1335 -4 97 248 1.44
!""#
$""#
%"""#
%&""#
%'""#
%!""#
%%(%$("$# "%(&)("*# "'(")("*# "!(%!("*#
!"#$%&%$'()*+,$-.*$#'/µ!0$12'
%+&&#,-./0#
%&+%*#,-./0#
%+&&#
%&+%*#
Figure 5.4: Specific conductance recorded at depths of 1.22 m and 12.19 m . Solid linesrepresent raw data collected by the probes. Dashed lines represent corrected data afterrecalibration.
113D
ep
th (
m)
11/28/08 01/07/09 02/16/09 03/28/09 05/07/09 06/16/09
2
4
6
8
10
12
Specific
Conducta
nce (!
S/c
m)
700
800
900
1000
1100
1200
1300
1400
1500
Dep
th (m
)
11/28/08 01/07/09 02/16/09 03/28/09 05/07/09 06/16/09
2
4
6
8
10
12
Tem
pera
ture
( !C
)
5
10
15
20
25
Figure 5.5: Isopleths of recorded (measured) specific conductance (top) and isotherms(bottom) in a depth vs. time plot. Values recorded in Tanners Lake from 28 Nov 2008to 31 July 2009.
114
600800
1000120014001600
Sur
face
wat
erC
ondu
ctan
ce
(!S
/cm
)
8001,0001,2001,4001,600
Ben
thic
wat
erC
ondu
ctan
ce(!
S/c
m)
Nov Jan Mar May0
0.5
1
Pre
cipi
tatio
nW
ater
Equ
ival
ent
(inch
es)
5
10
Sno
w D
epth
(inch
es)
0
20
40
Dai
ly A
vera
geA
ir Te
mpe
ratu
re("
C)
A B C D
Figure 5.6: From top to bottom: Specific conductance at the surface of the lake (seriesdepths from surface 1.2, 2.1, 3.0. 6.1 meters), Specific conductance at the bottom of thelake (series depths from surface in order of highest observed specific conductance valuesto lowest 13.4, 12.8, 12.2, 11.6, 11.0, 10.4, 9.1), daily average air temperature, dailyaverage snow depth, and precipitation water equivalent. Points A, B and C representstimes when accumulation of saline water occurred at the bottom of the lake. Point Drepresents when a fresh water intrusion was observed in the lakes surface water. Weatherdata were collected by the Minnesota Climatology working group.
115
The accumulation of salt laden (snowmelt) runoff water at the bottom of the lake
continued until ice-out. Ice-out occurred between March 31 and April 2, based on ice-out
dates of similar sized lakes located near Tanners Lake (Kohlman, Gervais, and Harriet;
[137]).
Right before ice-out a water intrusion occurred in the surface waters of the lake
(Figure 5.6 point D). During this time a layer with low specific conductance and tem-
peratures that reached 7 oC formed below the ice surface (Figure 5.4). The water for
these intrusions came from a few snowfalls that quickly melted and rainfall that oc-
curred from March 23 to April 1. The air temperatures during this period were above
freezing and likely most of the road salt had already been washed away allowing a warm
and less saline layer to form under the ice cover.
Shortly after the ice layer on the lake had melted, the lake began to mix (spring
overturn). Only the top 10 meters of the 14 m deep lake mixed after ice-out, resulting
in a saline water layer of about 4 m thickness at the bottom of the lake. The density
of this saline layer was strong enough to resist the convective and wind mixing events
right after ice out, i.e. the lake had become monomictic.
After ice-out the salinity of the benthic layers increased even though road salt ap-
plications had stopped. Shortly after the erosion of the saline layer began. This erosion
continued, but was not strong enough to remove the saline layer. By July 31st Tanners
Lake still has a saline benthic layer.
5.4.2 Lake Stratification: Model calibration results
The best-fit model parameters obtained by model calibration are given in Table 5.2.
WSTR and WFCT are wind-sheltering coefficients. Typical values for wind sheltering
coefficients range from 0.1 to 1 [120]. The value of 0.25 for Tanners Lake is low pointing
towards a well-sheltered lake.
Table 5.2: Best fit parameters from model calibrationWSTR 0.25WFCT 0.44Zsd (m) 3.00α (m2/day) 0.19
116
A maximum hypolimnetic effective diffusivity (Kzmax) was also determined by cali-
bration. The best-fit value for this parameter was 0.19 m2/day.
The Secchi depth determined by model calibration was 3 m. It matched the mea-
sured average Secchi depth in 2007 and 2008 in Tanners Lake of 3 meters with a range
from 1.8 to 5 m [124].
The temperature and specific conductance profiles obtained from the calibrated
model for the year 2008 were comparable to the observed values (Figure 5.7). Com-
parisons between observed and modeled values at three depths including the waters
surface, the mid-depth of the lake and the lake bottom depth are given in Figure 5.8.
Values obtained were consistent for temperature and salinity at the three depths. Dif-
ferences between the two years were significant. In 2007, values in the middle of the
lake decreased rapidly and remained even with the surface concentrations shortly after
ice out. The deep layer also eroded quickly, compared to the values in 2008, resulting
in the removal of the chemocline shortly after ice out for most of the water column. In
2008 the chemocline persisted until fall.
The average RMSE values for the temperature profiles in 2007 and 2008 were 1.06
and 1.10 oC respectively. The average RMSE values for the specific conductance profiles
in 2007 and 2008 were 57 and 60 µS/cm respectively. The temperature profiles for
both 2007 and 2008 compare well with the observed values throughout the year 5.9.
Calibration was only conducted with the 2008 data, yet the RMSE values for the 2007
temperature series are comparable to the 2008 values. The RMSE values for the specific
conductance are also consistent throughout the year 5.9. For the 2008 simulation, RMSE
values hover between 50 and 60 µS/cm. In 2007 values around 50 µS/cm are observed
during the first 5 months of the simulation, but increase beyond that point. In the later
months of the simulation concentrations in the surface waters of the observed dataset
are reduced in 2007. This is likely caused by freshwater inflows from rainfall. Rainwater
inflows are not included in the model resulting in an increase in RMSE values in the
epilimnion.
5.4.3 Lake Stratification and Vertical Mixing: Model simulation re-
sults
Temperature and specific conductance profiles
117
0
5
10
07-May-2008 30-May-20080
5
10
30-Jul-2008
Dep
th (m
)
15-Aug-2008
0 10 20
0
5
10
1525-Sep-2008
800 1,200 1,600 0 10 2023-Oct-2008
800 1,200 1,600
Temperature !C Conductance "S/cm Temperature !C Conductance "S/cm
Figure 5.7: Vertical profiles of measured (dashed line) and simulated (solid line) watertemperatures and specific conductance in Tanners Lake in 2008.
118
4/22/07 6/11/07 7/31/07 9/19/07 11/7/07
600
800
1000
1200
1400
1600
1800
Con
duct
ivity
(!S
/cm
)
0 m7 m14 m0 m14 m7 m
4/22/07 6/11/07 7/31/07 9/19/07 11/7/070
5
10
15
20
25
30
Tem
pera
ture
(!C
)
4/22/08 6/11/08 7/31/08 9/19/08 11/7/08
600
800
1000
1200
1400
1600
1800
Con
duct
ivity
(!S
/cm
)
4/22/08 6/11/08 7/31/08 9/19/08 11/7/080
5
10
15
20
25
30
Tem
pera
ture
(!C
)
Figure 5.8: Time series of specific conductance (left) and water temperatures (right) atthe lake surface (0m), at mid-depth (7m) and at the bottom (14m) of Tanners Lake,measured and simulated for 2007 (top) and 2008 (bottom).
119
!"
#!"
$!!"
$#!"
%!!"
%#!"
&!!"
&#!"
'!!"
(%"
($)#"
($"
(!)#"
!"
!)#"
$"
$)#"
%"
'*%+" ,*$," -*#" .*%'" $$*$&" !"#$%&'(#&)*+µ,-&./*
0).1)2('%2)*+"!/*
/012"!-" /012"!+" 3456"!-" 3456"!+"
Figure 5.9: Root mean square error (RMSE) between modeled and observed watertemperature and specific conductance profiles in 2007 and 2008.
Model simulations were made for the ice-free periods of 2007 and 2008. The initial
conditions used in the model for temperature and specific conductance were obtained
from field measurements using an YSI Model 63 probe (Figure 5.10). Initial values were
acquired as close to the ice-out date as possible on 1 April 2007 and 22 April 2008.
Estimates of ice-out dates in Tanners Lake are March 26-27, 2007 and April 1821, 2008
respectively. These ice out dates were determined from similar sized lakes located near
Tanners Lake (Kohlman, Gervais, and Harriet; [137]).
The two initial conductivity profiles are approximately similar but the two initial
temperature profiles are different. The temperature of the surface waters in 2008 were
much warmer than in 2007, but the deeper layers were colder in 2008 than in 2007.
In 2008 the saline layer persisted throughout the summer and diluted gradually by
effective diffusion into the overlying water. By fall the density of the bottom layer was
reduced due to heating and gradual mixing with hypolimnetic water, allowing for com-
plete mixing (Figure 5.11). In 2007 the chemocline eroded quickly after ice-out resulting
in an almost completely mixed water column (Figure 5.3).
Stratification stability
Density gradients caused by temperature differences and those caused by salinity were
120
!"
#"
$"
%"
&"
'!"
'#"
'$"
'%"
!" (!!" '!!!" '(!!" #!!!"
!"#$%&'()&
*#"+,-,+&+./01+$2/+"&'µ*3+()&
!" #" $" %" &" '!"
4"(#"52$15"&'.6)&
$)')!*"
$)##)!&"
Figure 5.10: Measured specific conductance (dashed line) and temperature (solid line)profiles used as initial conditions for simulations of the open water periods 2007 and2008.
calculated separately to evaluate the contribution of the salinity to lake stratification
(Figure 5.12).
In April, after ice-out, the density stratification in the lake was mostly caused by
salinity. On April 1 2007 all of the density stratification in the lake was from the salinity.
The largest salinity induced density gradient was located at 13 m and was equal to 0.17
Kg/m4. On April 22 2008 temperature stratification was present up to a depth of 4
m and the strongest density gradient (equall to 0.15 Kg/m4) caused by temperature
stratification was at a depth of 4m. Salinity stratification began at a depth of 8 m.
The strongest salinity induced density gradient (also equal to 0.15 Kg/m4) was at 10 m
depth .
121Depth (m)
4/01
/07
6/01
/07
8/01
/07
10/0
1/07
0 2 4 6 8 10 12 14
Specific Conductance (!S/cm)
600
700
800
900
1000
1100
1200
1300
1400
1500
1600
Depth (m)
4/01
/08
6/01
/08
8/01
/08
10/0
1/08
0 2 4 6 8 10 12 14
Specific Conductance (!S/cm)
600
700
800
900
1000
1100
1200
1300
1400
1500
1600
Depth (m)
4/01
/07
6/01
/07
8/01
/07
10/0
1/07
0 2 4 6 8 10 12 14
Temperature ( !C )
0510152025
Depth (m)
4/01
/08
6/01
/08
8/01
/08
10/0
1/08
0 2 4 6 8 10 12 14
Temperature ( !C )
0510152025
Fig
ure
5.11
:Is
ople
ths
ofsi
mul
ated
spec
ific
cond
ucta
nce
(top
)an
dis
othe
rms
(bot
tom
)in
ade
pth
vsti
me
plot
duri
ngth
eic
e-fr
eepe
riod
sof
2007
(lef
t)an
d20
08(r
ight
).
122
In May the density gradients were dominated by temperature. In 2007 a slight chem-
ical stratification was present in the bottom 11 meters, but almost all salinity induced
density gradients had disappeared. Temperature-induced density gradient reached 0.7
Kg/m4. In 2008 a more pronounces salinity layer was present in May, but the density
gradients caused by the salinity only reached 0.06 kg/m4 while temperature stratifica-
tion caused a maximum density gradient of 0.5 kg/m4.
In July the temperature stratification in both 2007 and 2008 caused density gradients
to reach up to 1.4 kg/m4. Salinity stratification was non-existent in July of 2007, but
it was still present in July of 2008 starting at about 8 meters.
In October of 2008 salinity stratification had been reduced to a maximum value of
0.03 kg/m4 at 7 m. Temperature stratification was reduced to about 0.4 kg/m4 for both
2007 and 2008.
Hypolimnetic effective diffusivity
In order to get the variable results between 2007 and 2008 the Lake Number had to
be included in the calculation of the hypolimnetic effective diffusivity. With out the
inclusion of this parameter either to much mixing occurred in the summer months when
temperature stratification was strong or to little mixing occurred in the early spring
and late fall months when temperature stratification was reduced.
Without the Lake Number the hypolimnetic Kz values would be constant throughout
the year year if no localized density stratification was present at that particular depth.
The Lake number changes with strength of the overall lake stratification as well as
with wind speed. In summer when thermal stratification was strong the Lake number
increased causing the maximum hypolimnetic eddy diffusion (Kz) to decrease (Figure
13). In fall and spring when density gradients were absent or weak mixing was increased
in the hypolimnion. When wind speeds are high and more wind energy was applied at
the lake surface Kz values increased
5.4.4 Dissolved Oxygen Modeling Results
Simulations were run using the 2008 temperature and salinity profiles to determine how
dissolved oxygen (DO) profiles in Tanners Lake would respond to the presence of a
benthic saline layer. Under the first scenario with no vertical salinity gradient (Figure
123
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Figure 5.12: Profiles of density gradients caused by salinity (solid line) and temperature(dotted line).
124
!"
!#!$"
!#%"
!#%$"
!#&"
!#&$"
&'&('!(" )'&('!(" %!'&$'!(" &'&&'!*" )'&%'!*"%!'%+'!*"
!"#$%
&'()*+#
Figure 5.13: Simulated effective hypolimnetic diffusion coefficients near the lake bed(depth of 14m) plotted vs time.
5.14)the lake is dimictic, i.e. it turns over in fall and spring and the entire water column
is oxygenated on both occasions. In midsummer the lake bottom goes anoxic for about
100 days from July 10 to Oct 20.
Under the second scenario, using identical weather conditions, but introducing a
saline layer at the bottom of the lake produced a very different result. The benthic
saline layer reduced vertical mixing especially near the lake bed. In spring the benthic
saline layer prevented the complete convective mixing of the entire water column. In
fall, when the saline layer was diluted, vertical lake mixing was delayed, but eventually
the saline layer was eroded and the surface waters mixed with the benthic waters late
in November. At that time, DO was transport from the overlying water to the lake
sediment. Overall DO did not reach the lake bottom during the entire open-water
period from April to November (Figure 13 bottom)
Vertical dissolved oxygen profiles were very similar in late summer for the two simu-
lated scenarios, with and without a benthic saline layer, when temperature stratification
was at a maximum.
125D
etpt
h (m
)
6/1/08 8/1/08 10/1/08
0
2
4
6
8
10
12
14
Dissolved O
xygen (mg/L)
0
1
2
3
4
5
6
7
8
9
(a)
Dep
th (m
)
6/1/08 8/1/08 10/1/08
0
2
4
6
8
10
12
14
Dissolved O
xygen (mg/L)
0
1
2
3
4
5
6
7
8
9
(b)
Figure 5.14: Isopleths of simulated dissolved oxygen concentrations in a depth vs. timeplot without a saline layer (top) and with a saline layer (bottom) for the 2008 testscenario.
126
5.5 Discussion
5.5.1 Interpretation of Measurements (2007-2009) and Simulation Re-
sults (2007-2008)
Equations developed for the MINLAKE temperature model [133][120]were used to sim-
ulate temperature and salinity profiles in a stratified lake during the open-water season.
A conversion of salinity (specific conductance) to density and an effective hypolimnetic
diffusion coefficient linked to a Lake Number were introduced to accurately simulate
temperature and salinity profiles in Tanners Lake, a lake in the Twin Cities metropoli-
tan area of Minnesota. The dynamic lake model used daily weather parameters and
initial temperature and salinity profiles measured after ice-out as inputs. Daily sim-
ulated data and a few observed profiles for 2007 and 2008 and continuously recorded
profiles for 2008/2009 were compared. The interpretation of the three years of data and
two years of simulations focused on the saline layer.
In 2007 the saline layer eroded away a few weeks after ice-out resulting in an almost
completely mixed water column throughout the summer. In 2008 and 2009 this did
not occur; instead the saline benthic layer persisted throughout the summer. The main
cause for this significant and consequential difference appears to be a 9-day cooling
period between April 4 and April 12, 2007 right after ice-out where air temperatures
and dew point temperature were below 0 oC 5.3. The prolonged stratification instability
allowed for the effective hypolimnetic diffusion caused by wind mixing to erode away
the saline layer before temperature stratification was able to reduce the mixing between
the hypolimnion and epilimnion.
In 2008 and 2009 a steady warming of the surface waters followed ice-out. This warm-
ing quickly created a thermocline, which reduced the mixing between the hypolimnion
and the surface waters effectively limiting the erosion of the saline layer.
Convective mixing appeared to be a minimal component in the erosion of the saline
layer. Convective mixing alone was not strong enough to mix the surface waters with
the salinity layer in 2007, 2008 or 2009. In 2007 the density increase due to the heating
of the water to TMD (just below 4 oC) from 3.5 oC was only 0.002 kg/m3. At this same
time the density increase due to the change in salinity between the surface waters and
the hypolimnion was 0.42 kg/m3. In 2008 when the hypolimnetic water temperatures
127
were much cooler the difference in density caused by heating the water from 3 oC to TMD
amounted to 0.007 kg/m3 compared to the density difference of .47 kg/m3 between the
surface waters and the hypolimnion caused by salinity. The large differences between
the added density from salinity and the added density from heating the surface waters
to TMD eliminated the complete convective mixing of the water column. This means
that the major driving force for the erosion of the saline layer during the spring and fall
was wind energy.
The density stratification right after ice-out was dominated by salinity stratification.
Throughout the summer, however, when the temperature of the surface water heated
up, the density difference across the thermocline far outweighed the density gradients
caused by the chemocline. Consequently, it is the formation of the thermocline that
prevents the mixing of the saline layer with the surface waters during the summer. If
only the chemocline was present the density stratification caused by the salinity gradient
would not be sufficient to withstand wind mixing from top to bottom.
The data recorded continuously in 2009 at 2-minute intervals clearly showed the
accumulation of a saline water layer at the bottom of Tanners Lake. This layer grew
during the winter months, when melting events occurred, until ice-out (Figure 5.5).
The accumulation of salt water at the bottom of the lake suggests that the snowmelt
runoff plunged upon entering the lake to form a density current that flow to the lake
bottom. This flow pattern was documented using only temperature probes in Ryan
Lake in Minnesota [54].
Right after ice-out a final salinity increase was recorded in the deepest part of Tan-
ners Lake (Figures 5.5 and 5.66). At least two different processes could account for this:
(1) mixing between the sediment layer and the benthic water could have uprooted salt
stored in the sediments [138, 44, 71] or (2) arrival of a delayed snowmelt runoff traveling
through extended pathways.
Shortly after this final input of saline water, the erosion of the saline benthic layer
began. This erosion was not enough to completely mix the lake before a thermocline
formed in the lake reducing the vertical transport of mass, momentum and energy from
the lake surface to the lake bottom.
128
5.5.2 Effects of Benthic Saline Layer Formation on Lake Water Quality
The intermittent or persistent presence of a benthic saline layer at the bottom of an
urban lake can have a number of consequences for lake water quality. The saline layer
prevents natural convection and mixing of the surface waters with the benthic water.
This prevents oxygen from reaching the botom of the lake lengthening the anoxic periods
of the lake sediments [61]. This effect was clearly shown in the simulated DO profiles
(Figure 5.14 bottom). The saline layer reduced mixing from convection as well as
wind mixing of the hypolimnion, preventing oxygen from reaching the sediments in the
spring right after ice out. When the salt layer was removed oxygen was able to travel
throughout the water column due to convective and wind mixing (Figure 5.14 top).
DO remained in the hypolimnion until July when the oxygen demand of the sediments
finally reduced DO levels to those observed when a saline layer was present (Figure 5.14
bottom). The saline layer increased the anoxic period in the lower depths of the lake
by 3 months.
Biochemical (mostly microbial) DO uptake at the sediment water interface removes
DO from the water column, and diffusive transport from above usually replenishes it.
These processes were represented in the model. Lake bottom waters and lake sediments
become anaerobic when insufficient DO was supplied by convection or wind mixing from
the water above. Starting with zero DO at the lake bottom due to the presence of a
saline layer that prevents lake overturn, will cause continuing anoxia in summer on the
lake bed.
Under winter conditions, which were not modeled, there is no oxygen source in the
lake water (no surface aeration due to the ice cover, and no photosynthesis due to a
snow cover on the ice). Benthic DO continues, however, and in order to maintain aerobic
conditions near the lake, fall turnover and oxygen replenishment near the lake bed are
crucial.
A long anoxic period in the hypolimnion can facilitate the release of phosphorus and
metals from the sediments. Enhanced internal phosphorus release from the anaerobic
sediment [139, 140] increases cultural eutrophication. Increased chloride concentrations
have also been observed to increase the bioavailability of metals such as cadmium, lead,
chromium mercury among others [40, 37, 39, 4, 34]. By increasing the contact time
of the saline layer containing high concentrations of chloride with the sediments, the
129
release of metals from these sediments is increased.
Finally, the increased contact time of benthic organisms with elevated chloride con-
centrations can affect the biodiversity of the lake [59, 110]. Macro-invertebrates and
bottom feeding organisms would have to adjust to the increased length of the anoxic
period at the lake bed as well as increased chloride concentrations. All of these con-
sequences of the saline benthic layer formation are detrimental to water quality and
aquatic life in the lake.
5.6 Summary and Conclusions
Two years (2007, 2008) of intermittently measured temperature and specific conduc-
tance profiles and one year (2009) of continuously monitored data were used to show
the formation of a benthic saline layer in winter, and its effect on summer stratification
and mixing dynamic in Tanners Lake, Oakdale, Minnesota.
Erosion of the saline layer in the spring occurred in only one of the three years studied
(2007). In the other two years (2008 and 2009), the saline layer persisted throughout
the summer, and was destroyed only by fall turnover and mixing between the epilimnion
and hypolimnion when thermo stratification was at a minimum.
Simulations showed that from ice-out in April 2008 until November 2009 the saline
layer was able to prevent dissolved oxygen from reaching the lake sediments. Without
the saline layer the lake sediments would have been anoxic only from the beginning
of July until the end of October 2008. With the addition of a saline layer the anoxic
period experienced by the lake sediments persisted throughout the spring and summer.
Simulations also showed that in the fall turnover of the lake was delayed, when the
saline layer was present, until the end of November.
The results of this study provide information on the formation, the mixing and the
consequences of a benthic saline layer in a northern temperate urban lake that receives
snowmelt runoff from roads on which salt (NaCl) has been applied to increase driving
safety. Specific results are:
(1) The formation of the benthic saline layer has been documented in detail. The
record consists of specific conductance profiles recorded at 2-minute intervals from 28
Nov 2008 until 31 July 2009 in Tanners Lake in Oakdale, Minnesota. The formation of
130
the saline benthic layer is episodic, and follows the air temperature pattern.
(2) Natural convective mixing in spring or fall (spring and fall turnover) is not
intensive enough to remove the saline layer after ice out. Mixing of the hypolimnion by
wind energy applied at the water surface is needed to completely erode the saline layer.
(3) The formation of monomixis (one complete lake turnover per year) or meromixis
(no complete lake turnover per year) in a northern temperate lake due to road salt
application in the watershed appears to be contingent on both the strength (salt con-
centration) of the saline layer and the timing of the seasonal thermocline formation after
ice out.
(4) Formation of a seasonal thermocline effectively reduces the transport of wind
energy from the epilimnion to the hypolimnion, and hinders the erosion of the saline
layer. Lakes number was used in the model simulations to capture this effect.
Overall the presence of a saline benthic layer due to runoff containing road salt
(NaCl) was shown to disrupt the natural mixing mechanics of a dimictic lake. This
disruption has significant consequences for a lakes water quality and ecology.
Aknowledgements
We acknowledge the Minnesota Local Road Research Board (LRRB) and the University
of Minnesota Doctoral Dissertation Fellowship Program for providing support to com-
plete this research. We also thank Ben Erickson and Chris Ellis from the St. Anthony
Falls Laboratory for their assistance in designing and implementing the Buoy system.
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Appendix A
Data Sets
146
Brownie LakeC = Measured Conductivity (υS/cm)T = Temperature (oC)SC = calculated specific conductance (υS/cm)Depth
(m) C T SC C T SC C T SC C T SC C T SC C T SC C T SC0 343 1.4 625 245.2 0 469 515 13.9 654 713 21.7 761 541 26.1 530 475 15.8 576 471 6.2 735
-0.5 250.7 0 480 514 14 651 705 21.3 759 537 25.9 528 475 15.8 576 471 6.2 735-1 380 3.9 637 265.8 0.2 505 514 14 651 701 21.1 757 535 25.7 528 474 15.7 576 471 6.1 737
-1.5 372.2 0.4 702 513 13.8 653 693 20.7 755 533 25.5 528 472 15.7 574 470 6.1 736-2 397 4.3 657 491.6 0.5 924 514 13.5 659 691 20.5 756 542 25.1 541 468 15.6 570 470 6.1 736
-2.5 447 4.5 734 638 1.4 1162 658 12.3 869 720 19.6 803 574 24.5 580 469 15.5 573 470 6.1 736-3 593 4.7 969 782 2.7 1362 967 9.6 1370 968 15.7 1177 604 23.4 623 470 15.5 574 469 6.1 734
-3.5 656 4.7 1071 861 3.9 1442 1145 7.5 1720 1293 10.8 1774 647 22.7 677 470 15.4 576 468 6 735-4 743 4.7 1214 946 4 1580 1200 6.3 1867 1316 9.4 1875 679 22.1 719 470 15.4 576 467 5.9 735
-4.5 830 4.7 1356 1048 4.1 1744 1241 5.6 1972 1336 7.3 2018 755 20.9 819 472 15.4 578 467 5.9 735-5 907 4.8 1477 1130 4.2 1875 1312 5.2 2110 1379 6.3 2145 923 18.2 1061 484 15.3 594 467 5.9 735
-5.5 970 4.8 1579 1200 4.3 1985 1346 5 2178 1428 6 2241 1271 14.1 1605 766 14.6 956 467 5.9 735-6 1080 4.9 1753 1300 4.3 2150 1424 5 2304 1482 5.7 2347 1500 10.7 2064 1546 12.1 2051 513 6 805
-6.5 1290 5.3 2068 1415 4.4 2333 1560 5.2 2509 1565 5.7 2479 1590 8.3 2335 1666 10.3 2316 1535 7.4 2312-7 1493 5.9 2350 1512 4.7 2469 1652 5.5 2632 1683 5.8 2658 1664 7.5 2499 1762 8.4 2580 1782 8.3 2617
-7.5 1646 6.7 2530 1650 5.2 2654 1727 5.6 2744 1773 6 2783 1738 6.9 2656 1832 7.5 2752 1872 8.1 2764-8 1805 7.2 2735 1783 5.8 2816 1796 5.8 2836 1855 6.2 2894 1817 6.8 2785 1900 7 2895 1947 8 2883
-8.5 1892 7.4 2850 1884 6.3 2931 1902 6.2 2968 1935 6.5 2992 1889 6.8 2896 1954 6.8 2995 2004 7.8 2984-9 1990 7.6 2981 1985 6.6 3061 1984 6.4 3077 2017 6.7 3101 1984 6.9 3032 2028 6.8 3109 2063 7.7 3081
-9.5 2050 7.8 3053 2065 6.9 3156 2044 6.6 3152 2081 6.9 3181 2056 7.1 3124 2099 6.9 3208 2124 7.7 3172-10 2118 8 3136 2132 7.1 3240 2123 6.8 3254 2152 7 3279 2130 7.4 3209 2156 7.1 3276 2162 7.8 3220
-10.5 2155 8.1 3182 2161 7.2 3274 2161 7 3293 2190 7.3 3309 2182 7.5 3278 2201 7.3 3325 2200 8 3258-11 2190 8.1 3234 2198 7.3 3321 2198 7.2 3330 2221 7.4 3346 2206 7.6 3304 2224 7.5 3341 2218 8.1 3275
-11.5 2202 8.2 3242 2223 7.4 3349 2227 7.3 3364 2239 7.6 3354 2229 7.8 3320 2236 7.6 3349 2230 8.2 3284-12 2225 8.3 3267 2243 7.4 3379 2244 7.4 3380 2250 7.7 3360 2230 7.9 3312 2253 7.6 3374 2247 8.3 3299
-12.5 2249 8.4 3293 2260 7.5 3395 2259 7.5 3393 2260 7.7 3375 2253 8 3336 2263 7.7 3380 2264 8.4 3315-13 2264 8.5 3306 2293 7.6 3434 2281 7.5 3426 2278 7.8 3393 2263 8 3351 2283 7.8 3400 2281 8.5 3331
-13.5 2273 8.6 3310 2281 7.7 3407 2285 7.6 3422 2270 7.8 3381 2269 8.1 3351 2296 7.9 3410 2309 8.6 3362-14 2300 8.7 3340 2285 7.6 3422 2191 7.7 3272 2238 8.1 3305 2306 8 3415 1922 8.8 2783
-14.5 2287 7.6 3425 1979 8.2 2914
11/6/069/24/061/14/06 2/25/06 5/6/06 6/13/06 8/8/06
C T SC C T SC C T SC C T SC C T SC C T SC C T SC C T400 0.9 741 380 9 547 640 21.1 692 505 18.1 582 376 6.4 583 282 0.1 538 195 0.2 370 435 10.9432 1.7 778 378 8.5 552 640 21.1 692 505 18.1 582 376 6.4 583 287 0.5 539 233 0.1 444 436 10.9449 2.9 777 373 8.5 545 621 19.8 689 505 18.1 582 375 6.3 583 321 1.7 578 422 2.1 750 457 10.4459 3.4 781 370 8.1 546 612 19.3 687 500 17.7 581 374 6.3 582 394 2.7 686 464 3 800 472 8.4471 4 786 414 8 613 612 18.4 700 495 17.3 580 374 6.3 582 402 3.1 691 533 3.4 907 666 7472 4 788 654 6.1 1023 647 15.9 783 494 17.2 580 374 6.2 584 438 3.4 746 649 3.4 1105 807 6.4544 4 908 829 5.8 1309 804 12.2 1064 494 17.2 580 374 6.2 584 511 3.5 867 720 3.4 1226 922 5.1614 4.5 1009 893 5.1 1441 926 9.4 1319 494 17.1 582 374 6.2 584 586 3.6 991 825 3.4 1404 986 4.5684 4.6 1121 940 5.1 1516 1009 7.4 1520 501 17 591 373 6.2 582 698 3.7 1177 891 3.4 1517 1048 4.1773 4.7 1263 983 5.1 1586 1038 6.8 1591 539 16.8 639 373 6.2 582 770 3.7 1298 956 3.4 1627 1120 4845 4.6 1384 1012 5.2 1627 1071 6.5 1656 1128 14.3 1418 373 6.2 582 853 3.7 1438 1036 3.5 1758 1226 4906 4.7 1480 1007 5.5 1605 1152 6.2 1797 1304 12.4 1717 373 6.2 582 950 3.8 1596 1127 3.7 1900 1276 4.1
1070 4.9 1737 1143 5.8 1805 1233 6.3 1918 1408 9.7 1989 375 6.2 585 1074 4 1793 1174 3.8 1973 1383 4.31280 5.4 2046 1293 6.8 1982 1409 6.5 2179 1518 8.1 2242 1300 7.2 1970 1318 4.2 2187 1306 4 2181 1442 4.51595 5.8 2519 1500 7 2286 1566 6.8 2400 1626 7.2 2464 1616 8.1 2386 1502 5.1 2423 1514 4.8 2465 1536 4.71740 6.1 2723 1667 7.4 2511 1749 7.1 2658 1749 6.9 2673 1774 7.7 2649 1630 5.6 2590 1658 5.4 2650 1641 5.21872 6.5 2895 1775 7.6 2659 1860 7.4 2802 1844 6.8 2827 1854 7.4 2793 1820 6.4 2823 1819 5.9 2864 1845 5.81940 6.8 2974 1908 7.8 2841 1954 7.7 2918 1919 6.8 2942 1918 7.2 2906 1924 6.7 2958 1910 6.3 2971 1893 6.32052 7 3127 1986 8 2941 2034 8.2 2995 2004 6.9 3063 2009 7.1 3053 2030 7 3094 1992 6.6 3071 1986 6.62119 7.1 3220 2058 8.1 3039 2105 8.6 3065 2089 7 3183 2054 7.1 3121 2087 7.1 3171 2050 6.9 3133 2071 6.92158 7.2 3270 2120 8.3 3113 2138 8.8 3096 2131 7.1 3238 2130 7.2 3227 2138 7.2 3239 2122 7 3234 2124 7.12186 7.2 3312 2148 8.4 3145 2181 9.2 3124 2175 7.2 3295 2162 7.3 3266 2161 7.2 3274 2160 7.2 3273 2174 7.32210 7.3 3339 2178 8.5 3180 2210 9.4 3148 2189 7.3 3307 2178 7.3 3290 2188 7.3 3305 2184 7.3 3299 2198 7.42237 7.5 3360 2212 8.6 3221 2225 9.5 3161 2206 7.4 3323 2194 7.4 3305 2205 7.4 3322 2202 7.4 3317 2219 7.52258 7.4 3401 2227 8.5 3252 2235 9.7 3158 2220 7.5 3335 2200 7.4 3314 2219 7.4 3343 2216 7.4 3338 2239 7.62275 7.5 3417 2249 8.8 3257 2235 7.5 3357 2225 7.5 3342 2233 7.5 3354 2234 7.4 3365 2248 7.62300 7.6 3445 2271 8.8 3289 2241 7.5 3366 2235 7.5 3357 2255 7.6 3377 2241 7.5 3366 2251 7.72013 7.7 3006 2296 8.8 3325 2241 7.5 3366 2249 7.6 3368 2280 7.6 3415 2265 7.5 3402 2255 7.7
2200 8.8 3186 2253 7.6 3374 2269 7.7 3389 2295 7.7 3428 2207 7.7 3296 2262 7.72161 7.7 3227 1890 7.8 2815 1932 7.8
2/21/07 4/1/07 5/17/07 9/17/07 11/15/07 2/7/08 3/14/08 4/22/08
SC C T SC C T SC595 771 17.1 908 988 23.4 1019597 771 17.1 908 992 23.4 1023634 771 17.1 908 992 23.5 1021691 766 17 904 992 23.5 1021
1015 856 16.3 1027 989 23.4 10201252 1058 14.9 1311 1005 23 10451487 1074 11.3 1455 1060 22 11241621 1127 9 1623 1161 19.6 12951744 1159 6.4 1798 1274 15.8 15461870 1192 5.2 1917 1371 12.2 18152047 1230 4.8 2003 1430 9.3 20422124 1285 4.7 2099 1436 7.8 21392287 1658 4.7 2708 1478 6.6 22792370 1430 4.8 2328 1537 6.1 24052509 1537 5.1 2479 1667 6.1 26092639 1682 5.5 2680 1745 6.1 27312913 1809 5.9 2848 1839 6.2 28692945 1886 6.2 2943 1945 6.5 30083062 1985 6.5 3070 2011 6.6 31013165 2042 6.7 3139 2084 6.8 31943227 2084 6.9 3185 2132 7 32493284 2161 7.1 3284 2172 7.1 33003311 2180 7.2 3303 2197 7.3 33193333 2188 7.3 3305 2206 7.4 33233354 2199 7.3 3322 2216 7.4 33383367 2211 7.4 3331 2235 7.4 33673362 2215 7.4 3337 2245 7.5 33723368 2216 7.5 3329 2248 7.5 33773378 2215 7.5 3327 1979 7.6 29642877
4/22/08 5/30/08 8/15/08
Bryant LakeC = Measured Conductivity (υS/cm)T = Temperature (oC)SC = calculated specific conductance (υS/cm)Depth
(m) C T SC C T SC C T SC C T SC C T SC C T SC C T SC C T SC0 274 0.8 510 280 0.8 521 419 14 530 510 23 530 524 27.4 501 441 16.4 528 320 6.5 495 310 1 572
-0.5 289 2.3 510 298 1.1 548 419 14 530 510 23 530 526 27.3 504 441 16.3 529 322 6.3 501 329 1.7 593-1 292 2.7 509 310 3 535 418 13.9 530 509 22.9 530 526 27.2 505 441 16.3 529 324 6.2 506 345 2.9 597
-1.5 293 3 505 313 3.2 536 418 13.9 530 508 22.8 530 525 27.1 505 441 16.3 529 324 6.1 507 348 3.3 594-2 294 3.1 505 313 3.3 535 418 13.9 530 507 22.7 530 524 27 505 440 16.2 529 330 6.1 516 348 3.3 594
-2.5 294 3.1 505 313 3.4 533 418 13.8 532 501 22 531 523 27 504 440 16.2 529 331 6 520 349 3.4 594-3 294 3.1 505 314 3.5 533 418 13.8 532 497 21.6 532 523 27 504 439 16.2 528 331 6 520 349 3.4 594
-3.5 296 3.2 507 315 3.5 534 417 13.8 530 497 21.4 534 523 26.7 507 440 16.1 530 331 6 520 349 3.5 592-4 296 3.2 507 315 3.7 531 417 13.7 532 497 21.3 535 522 26.3 509 440 16.2 529 332 6 521 349 3.5 592
-4.5 299 3.3 511 319 3.7 538 417 13.8 530 495 21.1 535 532 25 532 439 16.2 528 333 5.9 524 351 3.6 594-5 303 3.4 516 322 3.8 541 416 13.7 530 492 20.6 537 540 23.8 553 439 16.1 529 335 5.9 527 356 3.9 596
-5.5 305 3.4 519 326 3.8 548 414 13.2 534 465 16.5 555 537 22.3 566 438 16.1 528 335 5.9 527 357 4 596-6 307 3.4 523 330 3.8 555 412 13 535 445 15 550 511 19.8 567 438 16 529 334 5.8 527 360 4.1 599
-6.5 310 3.4 528 335 3.9 561 413 12.8 538 440 14 557 501 16.4 599 436 15.9 528 334 5.8 527 360 4.1 599-7 314 3.4 535 347 3.9 581 406 10.5 562 437 13.1 566 492 15.3 604 436 15.8 529 335 5.8 529 363 4.1 604
-7.5 317 3.4 540 347 3.9 581 397 9.3 567 427 11.1 581 479 13.1 620 436 15.8 529 334 5.7 529 364 4.1 606-8 322 3.5 546 354 3.9 593 394 9 567 433 10.7 596 485 11.7 650 436 15.8 529 334 5.7 529 365 4.2 606
-8.5 327 3.5 555 361 3.8 607 387 8 573 442 9.8 623 494 10.8 678 441 15.5 539 335 5.6 532 368 4.2 611-9 334 3.5 567 370 3.8 622 454 9 654 495 9.8 697 491 14.2 619 335 5.6 532 374 4.2 621
-9.5 341 3.6 577 379 3.8 637 457 8.3 671 497 9.3 710 536 11 732 334 5.5 532 380 4.2 630-10 344 3.6 582 405 3.8 681 469 7.6 702 502 8.7 729 532 10 746 333 5.4 532 388 4.2 644
-10.5 360 3.7 607 427 3.9 715 478 7.3 722 515 7.9 765 537 9.5 763 333 5.4 532 400 4.2 664-11 378 3.7 637 453 4 756 481 7 733 522 7.8 777 537 9.2 769 333 5.4 532 409 4.3 676
-11.5 378 3.9 633 458 4.3 757 502 6.8 769 540 8.9 780 334 5.4 534 428 4.3 708-12 587 8.6 855 335 5.4 535 440 4.3 728
-12.5 335 5.5 534 440 4.4 725-13 426 6 669 465 4.5 764
11/8/06 2/21/079/24/061/21/06 2/26/06 5/5/06 6/14/06 8/8/06
C T SC C T SC C T SC C T SC C T SC C T SC C T SC C T SC366 7.4 551 519 18.9 587 584 25.1 583 487 18.5 556 362 5.8 572 253 0 484 288 0.7 537 386 7.4 581363 7.3 548 518 18.8 588 584 25.1 583 487 18.3 558 362 5.8 572 257 0.3 487 322 0.7 601 386 7.4 581363 7.2 550 518 18.7 589 584 25.1 583 487 18.3 558 361 5.8 570 280 1 517 361 1.4 657 385 7.3 582361 7.1 549 516 18.6 588 583 25 583 487 18.3 558 361 5.8 570 339 1.8 609 365 2 651 384 7.2 582361 7 550 515 18.6 587 582 25 582 487 18.3 558 361 5.8 570 352 1.8 632 368 2.2 652 384 7.1 583360 6.8 552 508 18 586 582 25 582 486 18.2 559 361 5.8 570 354 1.8 636 368 2.3 650 384 7.1 583357 6.6 550 505 17.7 587 577 24.5 583 486 18.1 560 361 5.8 570 355 1.9 635 368 2.3 650 384 7.1 583357 6.6 550 505 17.6 588 575 24.4 582 485 18.1 559 361 5.8 570 355 1.9 635 368 2.4 647 384 7.1 583359 6.5 555 504 17.6 587 573 24.2 582 485 18 560 361 5.8 570 357 2 637 369 2.5 647 384 7.1 583357 6.6 550 503 17.5 587 575 24.1 585 485 18 560 361 5.8 570 358 2.2 634 370 2.6 647 384 7 585357 6.6 550 499 17.1 588 573 24.1 583 485 18 560 361 5.8 570 358 2.4 630 374 2.7 651 384 7 585357 6.6 550 488 16 589 570 23.6 586 484 17.9 560 361 5.8 570 364 2.4 640 377 2.8 655 384 7 585357 6.5 552 476 15.2 586 557 21.2 601 483 17.9 559 361 5.8 570 366 2.6 640 380 2.9 658 384 7 585357 6.5 552 459 13.5 588 535 18.5 611 483 17.8 560 361 5.8 570 366 2.6 640 381 3 657 385 7 587357 6.6 550 444 12.3 586 497 15.5 607 482 17.7 560 361 5.8 570 368 2.7 641 383 3 661 385 7 587357 6.5 552 424 10.6 585 479 14.2 603 482 17.5 563 361 5.8 570 371 2.8 644 387 3.1 665 432 5.2 695358 6.5 554 406 9.3 580 461 12.4 607 482 17.4 564 361 5.8 570 373 2.8 648 389 3.1 669 435 4.9 706359 6.5 555 397 8.2 585 440 10.5 609 490 16.2 589 361 5.8 570 376 2.9 651 392 3.1 674 442 4.6 724362 6.2 565 392 7.8 584 426 9.5 605 510 14.2 643 361 5.8 570 378 3 652 394 3.2 675 465 4.4 767363 6.4 563 387 7.4 583 418 9 602 482 11.2 655 361 5.8 570 380 3 655 396 3.2 679 494 4.2 820387 6.1 606 384 7.2 582 413 8.5 603 473 10.3 658 361 5.8 570 383 3 661 402 3.2 689 521 3.8 876412 5.6 655 383 7.1 582 410 7.9 609 465 9.5 661 361 5.8 570 387 3.1 665 410 3.3 700 580 3.8 975446 5.1 719 381 6.9 582 408 7.7 609 463 9 667 361 5.7 572 391 3.2 670 418 3.3 714 595 3.8 1000497 4.7 812 380 6.7 584 410 7.4 618 461 8.7 669 361 5.7 572 398 3.2 682 429 3.4 730 607 3.8 1020554 4.7 905 382 6.6 589 416 7.2 630 462 8.5 675 361 5.7 572 407 3.3 695 439 3.4 747 622 3.8 1045592 4.6 970 383 6.6 591 419 7.2 635 462 8.4 676 361 5.7 572 417 3.3 712 453 3.5 769 635 3.9 1064622 4.7 1016 403 6.6 621 483 7.1 734 516 8.1 762 408 6 640 457 3.3 780 474 3.6 802 640 4 1069
4/1/07 5/17/07 7/13/07 9/17/07 11/15/07 2/7/08 3/14/08 4/22/08
C T SC C T SC521 16.8 618 606 24.6 611521 16.8 618 606 24.6 611521 16.8 618 606 24.6 611520 16.8 617 605 24.6 610520 16.8 617 605 24.6 610520 16.8 617 606 24.6 611519 16.7 617 606 24.5 612519 16.7 617 606 24.5 612518 16.6 617 606 24.2 615517 16.5 617 605 24.1 616515 16.3 618 603 24 615514 16.2 618 601 23.7 616504 15 623 596 22.2 630484 13 628 591 20.7 644476 12 633 576 17.6 671468 11.3 634 557 15.7 677463 10.5 640 542 13.9 688460 9.7 650 537 12.5 705466 9.2 667 533 11.1 726463 8.7 672 529 10.3 736462 8.6 673 529 10 741474 8.1 700 533 9.5 757524 7.3 792 542 9 781552 6.9 844 544 8.7 790556 6.8 852 548 8.5 800560 6.7 861 560 8.4 820595 6.5 920 580 8.3 852
8/15/085/30/08
Cedar LakeC = Measured Conductivity (υS/cm)T = Temperature (oC)SC = calculated specific conductance (υS/cm)Depth
(m) C T SC C T SC C T SC C T SC C T SC C T SC C T SC C T SC0 307 1.1 564 249 0 477 442 13.6 565 550 21.7 587 506 26.5 492 423 15.9 512 347 6.3 540 317 0 607
-0.5 266 0 509 550 21.6 588 506 26.5 492 429 15.8 520 347 6.2 541 335 0.2 636-1 325 3.1 558 300 0.4 566 447 13.6 571 548 21.6 586 506 26.5 492 429 15.8 520 362 6.1 567 360 0.6 674
-1.5 326 3.3 557 332 0.9 615 547 21.5 586 504 26.4 491 429 15.8 520 363 6.1 568 364 3 628-2 326 3.3 557 338 1.1 622 448 13.5 574 546 21.5 585 504 26.3 492 429 15.8 520 363 6.1 568 365 3.1 627
-2.5 326 3.2 559 339 1.4 617 546 21.4 586 507 26.3 495 428 15.8 519 363 6.1 568 365 3.1 627-3 326 3.3 557 341 1.8 612 448 13.5 574 545 21.4 585 508 26.2 497 427 15.7 519 363 6.1 568 365 3.1 627
-3.5 326 3.3 557 342 2.1 608 449 13.5 575 544 21.3 585 504 26.1 494 427 15.7 519 363 6.1 568 365 3.1 627-4 327 3.4 556 344 2.1 611 449 13.4 577 528 19.5 590 510 26 500 427 15.7 519 363 6.1 568 365 3.2 625
-4.5 328 3.4 558 345 2.3 609 450 13.5 577 519 18.4 594 548 24.3 555 427 15.5 522 363 6 570 366 3.2 627-5 331 3.5 561 349 2.6 610 450 13.4 578 486 15 601 556 21.5 596 428 15.5 523 363 6 570 366 3.2 627
-5.5 331 3.5 562 350 2.8 608 432 10.8 593 474 13.6 606 540 18.9 611 428 15.4 524 363 6 570 366 3.2 627-6 332 3.6 562 356 2.9 616 414 9 596 457 12.1 606 508 16.3 609 428 15.4 524 363 6 570 366 3.2 627
-6.5 334 3.6 564 363 3 626 399 7.6 598 446 10.6 615 490 13.7 625 430 15.2 529 363 6 570 366 3.3 625-7 335 3.8 563 364 3 628 398 7.3 601 440 9.6 623 470 12 625 461 14.3 579 363 6 570 367 3.3 627
-7.5 336 3.8 565 369 3 636 395 6.9 604 426 8.6 620 458 11.1 624 478 11.4 646 368 6 578 368 3.3 628-8 338 3.8 568 375 3.1 645 395 6.6 609 418 7.5 628 441 9.4 628 456 9.7 644 370 6 581 369 3.4 628
-8.5 340 3.8 572 382 3 659 395 6.2 616 412 7.2 624 434 8.7 630 445 8.6 648 369 6 579 370 3.4 630-9 342 3.8 575 385 3.1 662 394 6 618 404 6.6 623 428 7.8 637 447 7.9 664 369 6 579 371 3.5 630
-9.5 343 3.9 575 390 3 673 393 5.8 621 407 6.3 633 421 7.3 636 447 7.5 671 368 5.9 579 374 3.6 633-10 346 3.9 579 391 3 674 402 5.6 639 406 6.1 635 419 7 639 444 7.3 671 368 5.9 579 374 3.6 633
-10.5 347 4 579 393 3 678 404 6 634 422 6.8 647 445 7 678 368 5.9 579 374 3.6 633-11 350 4.1 583 394 3.1 677 407 5.9 641 424 6.7 652 448 6.8 687 412 6.1 645 374 3.7 631
-11.5 355 4.4 585 428 5.9 674 433 6.5 670 465 6.7 715 414 6.1 648 374 3.7 631-12 355 4.5 583 446 6.5 690 375 3.7 632
-12.5 385 3.8 647-13 392 3.8 659
-13.5-14
-14.515
-15.5-16
11/6/06 2/21/079/24/061/14/06 2/25/06 5/6/06 6/13/06 8/8/06
C T SC C T SC C T SC C T SC C T SC C T SC C T SC C T SC C T SC388 8.6 565 525 18.7 597 489 18.6 557 362 7 552 318 0.2 604 316 1 583 355 7.2 538 490 17 578 555 24.3 563378 7.6 566 525 18.6 598 489 18.6 557 361 6.9 552 325 0.4 613 325 1 600 355 7.1 539 490 17 578 555 24.3 563377 7.4 568 525 18.9 594 489 18.6 557 361 6.9 552 329 1.3 601 338 1.6 611 355 7.1 539 490 16.9 580 558 24.3 566372 7 567 525 18.9 594 489 18.6 557 361 6.9 552 334 1.4 608 344 2.2 609 355 7.1 539 490 16.9 580 558 24.3 566371 6.9 567 524 18.8 594 489 18.6 557 361 6.8 553 335 2.1 595 346 2.4 609 355 7 541 490 16.9 580 558 24.3 566370 6.8 567 523 18.8 593 489 18.6 557 361 6.8 553 335 2.1 595 346 2.5 607 355 6.8 544 490 16.9 580 558 24.3 566370 6.7 569 522 18.7 593 489 18.6 557 361 6.8 553 336 2.1 597 347 2.6 606 354 6.7 544 490 16.8 581 559 24.3 567369 6.7 567 517 18.5 590 489 18.6 557 361 6.8 553 336 2.2 595 347 2.6 606 354 6.6 546 489 16.8 580 559 24.3 567369 6.6 569 512 18 591 489 18.6 557 361 6.8 553 336 2.3 593 347 2.6 606 356 6.5 551 488 16.6 581 558 24.2 567368 6.6 567 508 17.6 592 487 18.4 557 361 6.8 553 337 2.4 593 347 2.7 604 358 6.4 555 483 16.2 581 559 23.4 577368 6.6 567 489 16 591 487 18.3 558 361 6.8 553 337 2.4 593 348 2.8 604 378 5.2 608 454 13 589 561 22.3 592368 6.5 569 466 13.9 591 486 18.3 557 361 6.8 553 338 2.6 591 349 3 602 384 4.5 631 439 11.4 593 538 18.3 617369 6.4 572 440 11 601 487 18.3 558 361 6.8 553 339 2.7 591 350 3.1 602 386 4.3 638 427 10.4 592 513 15.5 627372 6.3 579 420 9.3 600 486 18.2 559 361 6.8 553 343 2.8 596 352 3.2 603 389 4.1 647 419 9.2 600 488 13.4 627380 5.8 600 408 8.2 601 485 17.9 561 361 6.8 553 343 2.8 596 354 3.2 607 389 4 650 415 8.7 603 466 11.4 630385 5.8 608 402 7.5 604 487 17.1 574 362 6.8 555 345 2.9 597 357 3.2 612 390 3.9 653 411 8.1 607 451 10.3 627386 5.6 613 397 7.2 601 493 13.7 629 361 6.8 553 349 3 602 359 3.3 613 392 3.9 657 409 7.6 613 443 9.3 633397 4.8 646 394 6.9 602 463 10.5 640 361 6.8 553 350 3.1 602 360 3.4 613 393 3.8 660 409 7 623 437 8.3 642414 4.4 683 393 6.7 604 450 9.5 639 362 6.8 555 356 3.1 612 362 3.4 616 396 3.7 668 408 6.8 625 434 7.7 648426 3.9 714 390 6.6 601 437 8.7 635 362 6.8 555 353 3.2 605 364 3.5 618 398 3.6 673 409 6.7 629 432 7.5 649429 3.8 721 389 6.4 603 434 8 643 362 6.7 557 355 3.3 606 367 3.5 623 406 3.6 687 410 6.3 638 431 6.8 661435 3.8 731 389 6.4 603 428 7.5 643 362 6.7 557 356 3.3 608 368 3.5 624 412 3.5 699 414 5.8 654 429 6.5 663433 3.7 730 389 6.4 603 424 7.2 642 362 6.7 557 357 3.3 610 370 3.5 628 419 3.5 711 416 5.6 661 428 6.3 666436 3.7 735 388 6.3 604 422 7.1 641 362 6.7 557 360 3.4 613 372 3.5 631 425 3.5 721 416 5.4 665 429 6.2 669437 3.7 737 388 6.3 604 421 6.8 645 362 6.7 557 352 3.4 599 374 3.5 635 429 3.5 728 417 5.2 671 429 6 673436 3.7 735 389 6.3 605 422 6.6 651 362 6.7 557 364 3.4 620 377 3.6 638 429 3.4 730 418 5.1 674 430 5.8 679440 3.7 742 389 6.3 605 422 6.5 653 362 6.7 557 367 3.4 625 381 3.6 644 441 3.4 751 420 4.9 682 432 5.7 684442 3.7 745 389 6.3 605 425 6.3 661 362 6.7 557 371 3.5 630 384 3.6 649 455 3.4 775 421 4.8 685 433 5.7 686443 3.7 747 389 6.3 605 426 6.2 665 362 6.7 557 377 3.5 640 388 3.7 654 457 3.4 778 422 4.8 687 435 5.6 691443 3.6 749 389 6.3 605 428 6.2 668 361 6.7 555 381 3.6 644 395 3.7 666 464 3.4 790 423 4.7 691 435 5.5 693444 3.6 751 389 6.3 605 430 6.1 673 361 6.7 555 395 3.8 664 409 3.9 685 465 3.4 792 423 4.7 691 436 5.5 695444 3.6 751 436 6.3 678 431 6.1 674 437 6.7 672 454 3.7 765 409 4 683 455 3.6 770 425 4.6 696 463 5.4 740455 3.6 770 457 6 717 424 4 708 441 4.5 725
4/1/07 5/17/07 9/17/07 11/15/07 2/7/08 3/13/08 4/22/08 5/30/08 8/15/08
Lake GervaisC = Measured Conductivity (υS/cm)T = Temperature (oC)SC = calculated specific conductance (υS/cm)Depth
(m) C T SC C T SC C T SC C T SC C T SC C T SC C T SC C T SC0 700 26.4 682 539 16.4 645 451 8.8 653 390 0.2 741 405 1.1 745 432 5.9 680 625 17.1 736 747 24.1 742
-0.5 700 26.5 681 537 16.4 643 443 8.2 652 406 0.3 769 411 1.3 751 431 5.8 681 625 17.1 736 746 24.1 742-1 701 26.5 681 537 16.4 643 441 8 653 414 0.6 775 422 2.3 745 432 5.8 682 625 17.1 736 745 23.9 742
-1.5 700 26.5 681 537 16.5 641 440 8 652 422 1.2 774 426 2.7 742 432 5.8 682 623 17.1 734 747 23.8 742-2 701 26.5 681 537 16.5 641 440 7.9 653 416 2.4 732 427 2.9 739 431 5.8 681 622 16.9 736 747 23.8 742
-2.5 701 26.4 683 538 16.5 642 439 7.9 652 417 3 719 427 2.9 739 432 5.7 684 621 16.9 735 746 23.8 742-3 701 26.4 683 537 16.5 641 439 8 650 419 3.3 716 427 2.9 739 431 5.8 681 621 16.9 735 746 23.7 742
-3.5 700 26.4 682 537 16.5 641 438 8 649 420 3.4 715 428 2.9 741 431 5.8 681 620 16.9 733 747 23.7 742-4 699 26.2 683 538 16.5 642 438 8 649 421 3.4 717 428 2.9 741 431 5.8 681 620 16.8 735 747 23.7 742
-4.5 694 26.1 680 538 16.5 642 438 8 649 422 3.3 721 428 3 738 431 5.7 683 618 16.7 734 747 23.6 742-5 687 25.7 678 538 16.4 644 438 8.1 647 423 3.4 720 428 3.1 736 431 5.6 685 606 15.7 737 740 22.9 742
-5.5 699 24.3 708 537 16.3 644 438 8.2 645 425 3.5 721 429 3.2 735 431 5.6 685 591 14.9 732 750 20.7 742-6 680 20.6 742 534 16.2 642 438 8.2 645 426 3.4 725 432 3.3 738 431 5.6 685 569 13.1 736 748 18.5 742
-6.5 654 17.3 767 531 16.1 640 438 8.3 643 429 3.4 730 435 3.4 741 447 5 723 542 11.2 736 623 16.6 742-7 633 14.4 794 531 16.1 640 437 8.4 640 431 3.5 731 438 3.4 746 470 4.6 770 522 9.8 736 599 14.8 744
-7.5 616 12.4 811 532 16 642 436 8.4 638 435 3.5 738 441 3.4 751 473 4.4 780 510 8.7 741 579 13.3 746-8 609 10.8 836 655 13.3 843 435 8.4 637 441 3.5 748 446 3.4 759 480 4.3 794 503 8.3 739 561 11.9 748
-8.5 606 10.3 843 632 11.6 849 435 8.4 637 443 3.5 752 449 3.4 764 498 4.1 829 501 8.1 740 550 11.1 749-9 600 9.8 845 621 11 848 434 8.6 632 444 3.8 746 451 3.6 763 500 8 740 543 10.2 757
-9.5 594 9.5 844 613 10.2 855 434 8.8 628 449 3.9 752 454 3.6 768 498 7.9 740 526 9.5 747-10 593 9 854 608 9.8 857 434 8.9 627 447 4 746 457 3.6 773 495 7.7 739 521 8.8 754
-10.5 589 8.5 860 606 9.4 863 434 9 625 450 4.1 749 457 3.6 773 494 7.5 742 518 8.6 754-11 589 8.4 862 625 9.1 898 434 9 625 456 4.2 757 460 3.6 778 493 7.4 743 517 8.2 761
-11.5 590 8.2 869 629 9.2 901 434 9 625 457 4.2 758 467 3.7 787 493 7.3 745 517 8.1 763-12 587 8.1 867 433 9.1 622 460 4.4 758 472 3.8 793 492 7.3 743 515 8 763
-12.5 587 8 869 434 9.2 622 468 4.5 769 476 3.8 800 492 7.3 743 516 7.8 768-13 589 7.8 877 434 9.2 622 469 4.6 768 486 4 811 495 7.2 750 535 7.6 801
-13.5 597 7.8 889 480 9.2 687 477 4.6 782 486 4.1 809 600 4.2 995-14 497 9.1 714 584 4.3 966
5/17/07 7/13/074/1/078/9/06 9/25/06 11/8/06 1/24/07 2/21/07
C T SC C T SC C T SC C T SC C T SC C T SC C T SC660 20.2 727 398 6.7 612 360 1.1 662 390 1.9 698 457 7.6 684 668 17.5 780 822 26.7 796662 20.3 727 398 6.7 612 366 1.3 669 390 1.9 698 455 7.5 683 668 17.5 780 803 25.8 791661 20.3 726 397 6.6 612 367 1.5 666 390 1.9 698 454 7.3 686 664 17.1 782 799 25.3 794662 20.4 726 397 6.6 612 378 1.8 679 393 2.2 696 452 7.2 685 664 17 784 794 25.1 792663 20.4 727 397 6.5 614 378 1.9 676 394 2.3 696 452 7.2 685 662 16.9 783 791 25.1 789662 20.4 726 396 6 622 378 2 674 394 2.3 696 446 6.7 686 661 16.8 784 790 24.7 795663 20.4 727 396 6.5 612 378 2.1 672 394 2.3 696 445 6.5 688 660 16.6 786 787 24.5 795663 20.4 727 396 6.5 612 378 2.1 672 394 2.3 696 441 6.1 690 660 16.5 788 788 24.4 797662 20.4 726 396 6.5 612 378 2.2 670 395 2.3 697 440 6 691 659 16.4 789 784 24.1 798662 20.4 726 396 6.5 612 379 2.4 667 396 2.4 697 440 5.9 693 656 16.2 789 782 24 797662 20.4 726 396 6.5 612 379 2.5 665 396 2.5 694 442 5.9 696 646 15.4 791 781 23.9 798662 20.4 726 396 6.5 612 379 2.6 662 398 2.6 696 448 5.4 716 634 14.1 801 774 23.3 800660 20.3 725 396 6.5 612 383 2.9 663 398 2.8 691 486 4.6 796 611 12.8 797 748 20.7 815658 20 727 396 6.5 612 390 3 673 403 3 695 487 4.3 805 599 11.6 805 711 18.5 812659 19.5 736 396 6.4 614 391 3.2 670 406 3.1 698 508 4.2 843 581 10.4 806 694 17 819646 16.3 775 396 6.4 614 392 3.5 665 410 3.2 703 529 3.9 886 580 9.8 817 684 14.2 862615 14.5 769 395 6.4 613 394 3.6 666 413 3.3 705 555 3.7 936 579 9.4 825 669 13.1 866603 13.4 775 395 6.4 613 399 3.9 668 422 3.4 718 606 3.4 1032 579 8.9 836 656 12.3 866689 12.1 914 395 6.4 613 405 3.9 678 428 3.4 729 649 3.1 1116 579 8.6 843 642 11.2 872677 11.5 912 395 6.4 613 407 3.9 682 433 3.3 740 660 3 1138 580 8.3 852 637 10.6 879563 10.6 777 395 6.4 613 409 4.1 681 439 3.3 750 674 2.9 1166 584 7.9 867 636 10 891555 9.9 780 395 6.4 613 411 4.3 680 443 3.4 754 685 2.9 1185 605 7.3 914 637 9.5 905549 9.4 782 395 6.4 613 416 4.6 682 451 3.5 765 698 2.8 1212 623 6.8 955 637 9.2 912548 9.3 783 395 6.4 613 420 4.8 684 462 3.6 781 705 2.9 1220 635 6.5 982 636 9.1 913547 9.2 783 395 6.4 613 425 4.8 692 485 3.6 820 720 2.9 1246 643 6.2 1003 635 8.7 922547 9.2 783 395 6.5 611 433 4.9 703 507 3.6 857 729 3 1257 653 6 1025 636 8.7 924547 9.1 786 482 6.6 743 450 5.2 724 541 3.6 915 730 3 1259 658 5.8 1039 643 8.7 934558 8.9 806 550 3.8 924 650 5.8 1026
9/12/07 11/16/07 2/8/08 3/14/08 4/22/08 5/30/08 8/15/08
Lake McCarronC = Measured Conductivity (υS/cm)T = Temperature (oC)SC = calculated specific conductance (υS/cm)Depth
(m) C T SC C T SC C T SC C T SC C T SC C T SC0 357 2.8 619 328 0.6 614 500 16 604 587 24.5 593 589 26.6 572 481 16.7 572
-0.5 366 1.1 673 498 15.7 606 586 24.4 593 590 26.7 571 481 16.8 570-1 371 3.7 626 384 2.8 667 498 15.6 607 584 24.2 593 590 26.7 571 477 16.6 568
-1.5 371 3.8 624 388 3.4 660 497 15.6 606 581 23.8 595 590 26.8 570 476 16.5 568-2 372 3.8 625 388 3.4 660 496 15.5 606 576 23.5 593 590 26.7 571 476 16.5 568
-2.5 373 3.8 627 388 3.5 658 485 14.9 601 565 22.8 590 590 26.8 570 475 16.5 567-3 374 3.8 628 389 3.5 660 479 14.2 603 560 22.2 592 589 26.8 569 475 16.5 567
-3.5 374 3.8 628 389 3.5 660 477 13.9 605 556 21.9 591 588 26.8 568 474 16.5 566-4 374 3.8 629 389 3.5 660 475 13.8 604 552 21.5 592 588 26.8 568 474 16.5 566
-4.5 376 3.8 632 390 3.6 660 474 13.5 607 539 20.7 587 589 26.8 569 475 16.5 567-5 376 3.8 632 391 3.7 659 471 13.2 608 511 18.1 589 595 24.5 601 475 16.5 567
-5.5 378 3.8 634 392 3.7 661 465 12.9 605 486 14.8 604 583 21.6 623 475 16.5 567-6 378 3.8 635 392 3.6 663 460 11.5 620 480 13.7 612 563 19.1 635 475 16.4 568
-6.5 379 3.8 637 394 3.7 664 439 7.8 654 479 11.8 640 537 16.3 644 476 16.4 570-7 381 3.8 640 396 3.7 668 431 5.7 683 473 10.6 652 522 13.9 662 474 16.3 568
-7.5 382 3.8 642 398 3.7 671 423 5.1 682 467 9.7 660 514 11.6 691 535 14.7 666-8 382 3.8 643 399 3.7 673 422 4.9 685 463 7.6 693 506 10 709 537 16.5 641
-8.5 383 3.8 644 401 3.7 676 428 4.5 703 460 6.8 705 494 9.2 708 526 12 700-9 385 3.8 647 403 3.7 679 428 4.3 708 457 6.2 713 487 7.6 729 511 9.7 722
-9.5 385 3.8 647 406 3.7 684 430 4.2 713 456 5.7 722 485 7.2 735 507 8.5 740-10 386 3.8 649 409 3.6 692 434 4.1 722 458 5.2 737 490 6.3 762 508 7.5 763
-10.5 389 3.8 654 412 3.7 695 443 4 740 466 5 754 492 6 772 511 6.5 790-11 390 3.8 656 418 3.7 705 462 3.9 774 480 4.8 782 494 5.8 780 513 6 805
-11.5 394 3.8 662 426 3.7 718 474 3.9 794 485 4.7 792 503 5.4 804 511 5.8 807-12 396 3.9 664 435 3.7 733 487 3.9 816 498 4.6 816 509 5.2 819 513 5.7 813
-12.5 400 4 668 449 3.7 757 510 3.8 857 509 4.5 837 514 5.1 829 518 5.5 825-13 407 4 680 474 3.7 799 527 3.8 886 515 4.5 846 518 5.1 836 525 5.4 839
-13.5 418 4.1 696 512 3.7 863 531 3.8 892 522 4.5 858 520 5.2 836 535 5.4 855-14 430 4.1 715 575 3.9 963 532 3.8 894 527 4.5 866 526 5.2 846 539 5.4 862
-14.5 481 4.2 798 570 3.9 955 533 3.8 896 561 4.6 919 567 5.3 909 622 5.4 994-15 563 4 940 535 3.8 899
-15.5 558 3.8 938-16 580 3.9 972
9/25/061/14/06 2/26/06 5/6/06 6/14/06 8/9/06
C T SC C T SC C T SC C T SC C T SC C T SC434 9.7 613 376 0.9 697 419 6.3 652 583 17.6 679 656 24.1 667 571 20.5 625434 9.7 613 386 1.7 696 415 6.3 646 583 17.6 679 656 24.1 667 571 20.5 625431 9.3 616 405 3.3 692 415 6.2 648 578 17.3 678 655 24 668 571 20.5 625429 9.2 614 406 3.3 693 414 6.1 648 578 17.3 678 653 23.9 667 571 20.5 625428 9.1 615 407 3.4 693 414 6.2 646 577 17.3 676 652 23.8 667 571 20.5 625427 9.2 612 407 3.4 693 413 6.2 644 577 17.2 678 652 23.8 667 571 20.5 625425 9 612 408 3.5 692 413 6.2 644 577 17.2 678 652 23.8 667 571 20.5 625424 9 611 408 3.5 692 414 6.1 648 575 17.1 677 651 23.8 666 571 20.5 625423 8.9 611 408 3.5 692 414 6.1 648 564 16.1 680 651 23.7 668 571 20.5 625422 8.8 611 407 3.5 691 414 6.1 648 543 14.7 676 650 23.6 668 571 20.5 625421 8.8 610 408 3.5 692 414 6.2 646 522 13 677 648 23.5 667 570 20.5 624420 8.7 610 408 3.6 690 414 6.1 648 497 10.8 682 588 17.7 683 570 20.4 625418 8.7 607 410 3.7 691 413 6.1 646 466 8.3 684 537 13.5 688 570 19.8 633417 8.7 606 410 3.7 691 413 6.1 646 447 7.2 677 502 11.4 678 573 18.1 660416 8.7 604 411 3.7 693 414 6 650 435 6.4 675 493 10.4 684 545 14.1 688416 8.8 602 413 3.8 694 415 5.8 655 427 5.8 674 470 9.1 675 515 11.9 687416 8.7 604 414 3.8 696 415 5.8 655 428 5.6 680 457 8 677 497 10.2 693416 8.7 604 415 3.8 697 415 5.8 655 424 5.4 678 454 7.3 686 480 8.9 693415 8.7 603 416 3.8 699 416 5.8 657 424 5.4 678 445 6.8 682 466 8.2 686415 8.9 599 417 3.8 701 417 5.6 662 423 5.3 678 441 6.1 690 461 7.5 692415 8.8 601 418 3.8 702 419 5.5 668 423 5.3 678 438 5.7 694 452 6.6 697415 8.9 599 420 3.8 706 420 5.4 671 425 5.3 681 437 5.5 696 453 6.1 709415 8.9 599 421 3.8 707 428 4.6 701 425 5.2 683 437 5.3 701 541 5.7 857415 9.1 596 424 3.7 715 451 4.5 741 426 5.3 683 444 5.2 714 453 5.5 722416 9.1 597 427 3.7 720 479 4.6 785 429 5.3 688 447 5.1 721 457 5.2 735416 9.2 596 432 3.7 728 498 4.7 813 433 5.3 694 452 5.1 729 459 5.1 740417 9.2 597 445 3.7 750 520 4.7 849 442 5.3 709 458 5 741 463 5 749419 9.4 597 459 3.7 774 552 4.8 899 458 5.6 728 461 5 746 468 4.9 760553 9 796 498 3.8 837 566 4.8 922 474 5.6 753 468 4.7 764 472 4.9 766601 9.4 856 546 3.8 918 584 4.9 948 490 5.6 778 472 4.7 771 474 4.9 769
610 3.8 1025 596 3.9 998 519 5.6 825 473 4.7 773 478 4.8 778613 3.9 1027 567 5.1 915 538 5.4 860 481 4.7 786 479 4.8 780
524 4.7 856 605 4.8 985
11/8/06 2/21/07 4/1/07 5/17/07 7/13/07 9/12/07
C T SC C T SC C T SC C T SC C T SC C T SC413 6.8 633 330 0 632 343 1.7 618 404 8.4 592 539 17.2 633 642 26.7 622412 6.8 632 373 0.3 706 343 1.7 618 403 8.3 592 539 17.1 635 642 26.7 622412 6.8 632 386 1.8 693 343 1.7 618 403 8.3 592 528 17 623 641 26.4 624412 6.8 632 390 2.2 691 401 2.7 699 402 8.2 592 536 16.9 634 637 26.2 623412 6.7 633 390 2.3 689 402 2.8 698 402 8.1 594 535 16.9 633 632 25.8 622412 6.7 633 391 2.4 688 402 2.8 698 400 8 592 534 16.8 633 633 25.6 626412 6.7 633 391 2.4 688 402 2.8 698 400 8 592 534 16.7 635 631 25.3 627412 6.7 633 391 2.4 688 402 2.8 698 400 7.9 594 534 16.6 636 630 25 630412 6.7 633 391 2.4 688 402 2.8 698 396 7.7 591 533 16.6 635 627 24.6 632412 6.5 637 391 2.4 688 402 2.8 698 400 6.8 613 533 16.6 635 626 24.4 633412 6.5 637 391 2.4 688 402 2.8 698 435 5.8 687 527 13.6 674 622 23.5 640412 6.5 637 391 2.5 686 402 2.8 698 435 5.1 702 484 11.5 652 603 20.6 658412 6.5 637 392 2.5 687 402 2.8 698 435 4.8 708 459 10.4 636 567 16.2 682412 6.5 637 394 2.6 689 404 2.8 701 433 4.6 709 454 9.5 645 554 15.1 683412 6.5 637 395 2.6 690 405 2.8 703 431 4.2 715 452 8.7 656 543 13.6 694412 6.5 637 397 2.6 694 407 2.8 707 433 4.1 721 449 8.1 663 529 12.7 691412 6.5 637 398 2.6 696 408 2.9 706 433 3.7 730 450 7.4 678 523 11.7 701412 6.5 637 398 2.6 696 412 2.9 713 435 3.7 733 453 6.8 694 508 9.9 714412 6.5 637 400 2.6 699 141 2.9 244 444 3.3 758 454 6.2 708 505 8 748412 6.5 637 401 2.7 699 416 2.9 720 447 3.3 763 456 5.4 729 505 6.8 774412 6.5 637 404 2.7 704 421 2.9 729 452 3.3 772 462 4.6 757 512 5.9 806412 6.5 637 407 2.7 709 424 2.9 734 456 3.2 781 471 4.3 779 514 5.4 822412 6.5 637 409 2.7 712 428 2.9 741 457 3.2 783 478 3.8 803 514 5.1 829412 6.5 637 412 2.7 718 435 2.9 753 464 3.1 798 491 3.6 830 515 4.8 839412 6.5 637 412 2.8 715 443 2.9 767 472 3.1 811 496 3.6 839 515 4.8 839412 6.5 637 420 2.9 727 457 2.9 791 496 3.1 853 502 3.5 852 516 4.5 848412 6.5 637 422 3 728 474 2.9 820 522 3.1 897 505 3.5 857 516 4.4 851412 6.5 637 432 3 745 492 2.9 851 534 3.1 918 508 3.4 865 520 4.3 860412 6.5 637 463 3 799 523 2.9 905 564 3.2 966 508 3.4 865 520 4.3 860412 6.5 637 487 3.1 837 592 3.1 1018 581 3.3 992 511 3.4 870 521 4.2 864412 6.4 639 551 3.3 941 625 3.3 1067 592 3.2 1014 514 3.4 875 523 4.2 868412 6.4 639 593 3.5 1006 656 3.5 1113 489 3.5 830 596 3.5 1011 525 4.1 874511 6.1 800 610 3.6 1032 649 3.6 1098 515 4.1 857
8/15/0811/15/07 2/8/08 3/14/08 4/22/08 5//30/2008
Parkers LakeC = Measured Conductivity (υS/cm)T = Temperature (oC)SC = calculated specific conductance (υS/cm)
depth(m) C T SC C T SC C T SC C T SC C T SC C T SC C T SC0 602 15.1 742 610 22.2 644 641 27.6 611 16.1 602 449 6.4 696 419 0.6 785 440 7.3 665
-0.5 601 15.1 741 610 22.1 646 640 27.6 610 16 601 447 6.3 695 434 1.5 787 438 7.2 664-1 601 15 743 625 22.1 662 648 27.5 618 16 604 446 6.3 694 448 2.8 778 438 7.1 666
-1.5 599 14.9 742 623 22.1 660 642 27.5 613 16 602 445 6.2 694 461 3.6 780 435 6.9 665-2 596 14.7 742 623 22.1 660 640 27.5 611 16 602 444 6.1 695 462 3.6 781 434 6.8 665
-2.5 594 14.6 741 611 21.3 657 640 27.4 612 15.9 603 443 6.1 693 463 3.7 781 434 6.7 667-3 594 14.6 741 606 21 656 636 27.1 611 15.9 603 443 6 695 464 3.8 780 432 6.7 664
-3.5 592 14.5 741 610 20.6 666 631 26.8 610 15.9 603 443 6 695 467 4.1 777 432 6.6 666-4 589 14.1 744 616 19.8 684 631 26.5 613 15.9 603 443 6 695 475 4.2 788 432 6.6 666
-4.5 587 14 743 614 18.4 703 660 24.7 664 15.9 603 443 6.1 693 478 4.3 791 431 6.6 665-5 581 13.5 745 597 17 705 684 22.6 717 15.9 602 443 6.1 693 486 4.3 804 431 6.4 668
-5.5 580 12.7 758 581 15.1 716 690 20.4 756 15.9 602 443 6.1 693 490 4.2 813 585 5.4 935-6 614 9.8 865 638 12.8 832 696 17.7 809 15.9 602 442 6.1 692 502 4.2 833 626 4.5 1029
-6.5 711 7.3 1074 785 10.9 1074 770 15 952 15.4 630 442 6.1 692 514 4.2 853 648 4.4 1068-7 773 5.9 1217 873 9.1 1254 888 12.4 1169 15.2 641 441 6.1 690 541 4.3 895 667 4.3 1103
-7.5 855 5 1383 906 7.7 1353 965 10.4 1338 13 1276 441 6.1 690 576 4.3 953 714 4.3 1181-8 916 4.6 1501 954 6.3 1484 1004 9.1 1442 10.9 1410 441 6.1 690 640 4.3 1058 764 4.3 1264
-8.5 955 4.5 1570 970 5.8 1532 1012 8 1499 9.3 1489 440 6.1 689 705 4.4 1162 868 4.4 1431-9 976 4.4 1609 988 5.4 1579 1021 7.4 1538 8.4 1530 439 6 689 781 4.4 1288 911 4.3 1507
-9.5 988 4.4 1629 993 5.2 1597 1020 7 1554 8.1 1541 438 6 687 864 4.5 1420 1024 4.3 1694-10 984 4.5 1617 996 5 1612 1023 6.5 1582 7.8 1555 438 6 687 870 4.6 1425 1117 4.3 1847
-10.5 995 4.9 1615 1021 6.4 1584 7.6 1564 437 6.1 684 922 4.6 1511 1213 4.3 2006-11 990 4.9 1607 1022 6.3 1590 7.4 1575 737 6.2 1150 933 4.7 1524 1254 4.4 2067
-11.25 976 5 1579 974 6.3 1515 7.3 1522 1266 4.8 2061
5/7/06 6/14/06 8/8/06 9/24/06 11/8/06 2/22/07 4/1/07
C T SC C T SC C T SC C T SC C T SC C T SC C T SC C T SC694 18.9 786 730 24.7 734 652 18.5 744 471 5.1 760 476 0.1 908 198 0.2 376 751 8.9 751 750 16.9 887692 18.5 790 730 24.6 736 652 18.4 746 471 5.1 760 477 0.4 900 261 0.2 496 754 8.7 754 750 16.9 887692 18.4 792 728 24.7 732 650 18.3 745 470 5.1 758 488 1.3 892 457 0.3 865 760 8.4 760 750 16.9 887692 18.3 794 726 24.6 732 648 18.2 745 470 5.1 758 497 1.8 892 531 2.6 928 764 8.1 764 750 16.9 887691 18.3 792 719 24.1 732 647 18.1 745 470 5 761 501 1.9 897 537 3 926 774 7.7 774 750 16.9 887690 18.2 793 714 23.8 731 642 17.5 749 470 5 761 503 2 897 537 3 926 794 7.6 794 750 16.9 887689 18.1 794 712 23.7 730 643 17.4 752 470 5 761 506 2.1 899 535 3 923 544 7.6 815 749 16.9 886681 17.8 790 708 23.6 727 635 17.1 748 470 5 761 507 2.1 901 531 2.9 919 607 6.7 933 750 16.9 887678 17.5 791 706 23.4 728 633 17.1 745 470 5 761 510 2.2 903 547 2.7 953 678 4.8 1104 749 16.9 886678 17.4 793 707 21.2 762 633 17 747 470 5 761 513 2.3 906 570 2.7 993 714 4.1 1188 745 16.3 893667 15.3 819 682 18.9 772 633 16.9 749 470 5 761 517 2.4 910 590 2.8 1024 720 3.9 1206 708 14.4 888652 14.4 818 661 15.8 802 633 16.9 749 470 5 761 521 2.4 917 613 2.8 1064 774 3.7 1305 676 11.6 909659 10.7 907 647 14.5 809 633 16.8 751 470 5 761 530 2.4 933 643 2.8 1116 789 3.6 1334 658 10.3 915572 9 824 638 12.5 838 634 16.5 757 470 5 761 559 2.5 980 672 2.8 1167 797 3.4 1357 728 8.1 1075558 8.1 824 600 11.2 815 654 14.4 820 470 5 761 570 2.6 996 713 2.8 1238 884 3.4 1505 844 7.2 1279548 7.5 823 585 9.9 822 627 12.1 832 470 5 761 600 2.6 1049 719 2.9 1244 920 3.4 1566 1002 5.4 1602544 7.1 827 570 8.8 825 616 10.8 845 470 5 761 640 2.6 1119 745 2.9 1289 956 3.4 1627 1062 4.8 1729532 6.6 820 567 8.1 837 609 10.2 849 469 4.9 761 664 2.7 1157 782 2.9 1353 992 3.4 1689 1106 4.5 1818531 6.3 826 564 7.6 845 599 9.2 858 469 4.9 761 696 2.8 1208 843 2.9 1459 1036 3.5 1758 1119 4.4 1845532 6 835 563 7.4 848 593 8.7 861 468 4.8 762 729 3 1257 935 3 1613 1126 3.6 1904 1129 4.3 1867533 5.7 844 564 7.2 855 595 8.3 874 468 4.8 762 772 3 1331 976 3 1683 1204 3.6 2036 1149 4.2 1906536 5.7 849 563 7.1 855 598 8.1 883 468 4.8 762 880 3 1518 1100 3.1 1891 1270 3.6 2148 1161 4.2 1926538 5.6 855 672 7.2 1018 601 8 890 468 4.8 762 829 3.2 1420 1066 3.1 1833 1307 3.7 2203 1150 4.1 1914770 5.5 1227 688 7.1 1045 688 7.9 1022 527 5.5 840 1100 3.7 1854
5/17/07 7/13/07 9/17/07 11/16/07 2/8/08 3/14/08 4/22/08 5/30/08
C T SC752 24.7 756751 24.7 755749 24.6 755744 24.5 751744 24.4 753743 24.3 753742 24.3 752741 24.2 752732 23.9 748714 23.3 738766 21.3 824776 18.3 890806 15.1 994869 11.9 1159985 9.9 1384
1046 8.9 15101124 7.6 16831154 7 17591165 6.5 18021174 6.3 18261178 6.1 18431182 5.8 18661145 5.8 1808
8/15/08
Ryan LakeC = Measured Conductivity (υS/cm)T = Temperature (oC)SC = calculated specific conductance (υS/cm)Depth
(m) C T SC C T SC C T SC C T SC C T SC C T SC C T SC0 289 2.1 513 307.2 0.5 577 386.5 16.8 458 432 22.5 454 469 28.3 441 16.3 468 380 8 563
-0.5 309.1 1.1 569 386.7 16.7 460 431 22.5 453 469 28.4 440 16.2 469 381 7.9 566-1 295 2.7 514 314.7 2.1 559 385.6 16.6 459 429 22 455 460 27.4 440 16.2 468 379 7.7 566
-1.5 296 2.8 513 314.2 2.7 547 376.7 15.7 458 420 21.1 454 451 26.6 438 16.1 469 379 7.7 566-2 296 2.9 512 314.7 2.8 546 374.1 15.1 461 416 20.6 454 452 26.2 442 16 468 378 7.6 566
-2.5 296 2.9 513 315.4 2.8 548 362.5 14.5 453 411 19.8 456 456 24.7 459 15.2 466 369 6.8 566-3 298 2.8 517 316.7 2.8 550 355.9 13.2 459 403 18.3 462 454 22.5 477 14.7 468 366 6.6 564
-3.5 298 2.8 517 315.5 2.9 546 342.4 12 456 386 15 477 429 18.4 491 14.6 467 364 6.5 563-4 300 2.8 520 316.4 3 546 324 8.6 472 369 12.6 484 416 16.1 501 14.4 468 363 6.4 563
-4.5 303 2.8 526 318.4 3 549 314.9 7.1 478 353 10.6 487 386 12.1 512 14.1 475 361 6.4 560-5 305 2.9 528 322.2 3 556 314.9 6.9 481 340 8.4 498 370 9.7 523 13.2 501 360 6.3 560
-5.5 309 2.9 535 325.4 3 561 320.4 5.3 514 340 7.2 515 374 8.1 552 11.4 550 359 6.2 560-6 311 3 536 331.4 2.9 573 326.6 4.8 532 349 5.8 551 392 6.6 604 8.2 607 358 6.1 560
-6.5 313 3 539 337.9 3 583 332.8 4.5 547 368 5.1 594 414 5.8 654 7.1 653 357 6.1 559-7 319 3.1 549 348.3 3 601 347.1 4.3 574 394 4.6 646 441 5.3 707 6.5 701 357 6.1 559
-7.5 322 3.1 554 362.7 3 626 367 4 613 422 4.5 694 473 5 765 6.1 745 357 6.1 559-8 336 3.1 577 391.3 3 675 419.2 3.8 704 471 4.2 781 507 4.8 825 5.9 785 356 6 559
-8.5 368 3.2 631 434.8 3 750 488 3.6 825 504 4.1 839 533 4.7 871 5.7 833 355 6 557-9 408 3.2 698 483 3 833 539 3.5 915 531 4.1 884 546 4.6 895 5.5 861 355 6.3 552
-9.5 456 3.2 781 540 3.1 928 557 3.5 945 544 4 908 554 4.6 908 5.6 869 356 6.4 552-10 511 3.3 873 571 3.2 978 565 3.5 959 553 4.1 920 562 4.6 921 5.6 892 357 6.6 550
-10.5 599 3.5 1016 640 3.4 1089 574 3.6 971 560 4.1 932 582 4.7 951 5.6 907 544 6.7 836-11 600 3.6 1015 604 4.2 1002 5.6 1042
11/08//20069/25/061/14/06 2/25/06 5/6/06 6/14/06 8/8/06
C T SC C T SC C T SC C T SC C T SC C T SC C T SC C T SC343 0.5 645 338 8.5 494 482 18.7 548 499 24.1 508 457 19.6 510 323 4.9 524 317 0.1 604 216 0.2 410356 1.9 637 338 8.5 494 482 17.7 560 499 24.1 508 457 19.5 511 323 4.9 524 322 0.5 605 293 0.8 545367 2.3 648 337 8.3 495 480 18.5 548 499 24.1 508 443 18 511 323 4.8 526 330 1.3 603 337 1.6 609367 2.4 646 337 8.3 495 478 18.3 548 493 23.5 508 436 17.5 509 323 4.8 526 333 1.9 596 340 2 606368 2.4 647 337 8.2 496 474 18 547 491 23.3 507 430 17 508 323 4.8 526 335 2 597 341 2.2 604367 2.4 646 338 8.2 498 472 17.8 547 490 22.7 513 428 16.7 509 323 4.7 528 336 2.1 597 343 2.3 606367 2.4 646 338 8.1 499 456 15.5 557 503 20.8 547 428 16.4 512 323 4.7 528 336 2.2 595 344 2.6 601367 2.4 646 341 7.8 508 411 10.6 567 488 17.8 566 427 16.1 514 323 4.7 528 337 2.3 595 344 2.7 599367 2.4 646 347 7.5 521 396 9.1 569 468 15.4 573 431 15.6 525 323 4.7 528 337 2.4 593 345 2.8 599367 2.4 646 356 6.7 547 378 7.7 565 424 11.1 577 444 14.8 551 324 4.7 529 338 2.7 589 348 2.8 604367 2.4 646 360 5.9 567 366 6.8 561 405 9.1 582 441 12.7 576 324 4.7 529 338 2.8 587 354 2.9 613366 2.4 644 370 4.8 602 360 6.2 562 382 7.3 577 424 9.9 596 324 4.7 529 344 2.9 595 361 3 623366 2.3 646 375 4.5 616 359 5.8 567 376 6.8 576 413 8.3 606 324 4.7 529 346 3 597 370 3 638367 2.3 648 380 4.2 630 362 5.6 575 373 5.9 587 402 7.1 611 324 4.7 529 350 3.1 602 378 3 652366 2.3 646 388 4.1 646 363 5.5 578 375 5.7 594 404 6.6 623 324 4.7 529 357 3.1 614 389 3 671368 2.3 650 400 3.9 670 362 5.5 577 381 5.5 607 404 6.1 632 324 4.7 529 362 3.2 620 402 3 693405 2.4 713 426 3.9 714 362 5.5 577 390 5.4 623 417 5.8 658 324 4.7 529 373 3.4 635 433 3 747445 2.5 780 460 3.9 771 361 5.4 577 402 5.3 645 428 5.6 680 324 4.7 529 384 3.6 649 492 3 849494 2.7 861 482 4 805 362 5.4 579 422 5.2 679 438 5.5 698 324 4.7 529 404 3.7 681 553 3 954546 3.2 936 517 4.3 855 372 5.2 598 437 5.2 703 444 5.4 710 324 4.7 529 457 3.8 768 633 3 1092586 3.4 998 556 4.4 917 391 5.2 629 440 5.2 708 447 5.4 714 324 4.7 529 567 3.8 953 715 3 1233646 3.6 1093 582 4.7 951 424 4.9 688 511 5.2 822 588 5.4 940 354 4.8 576 597 3.5 1013 727 3.2 1246
593 4.8 966 432 4.6 708
2/22/07 4/1/07 5/17/07 7/13/07 9/17/07 11/15/07 2/8/08 3/14/08
C T SC C T SC C T SC345 13.1 446 443 17 523 485 25.7 479345 13 448 443 17 523 482 25.4 478345 12.7 451 443 17 523 477 24.8 479343 12.6 449 442 17 522 475 24.4 481330 11 450 442 16.9 523 476 24.3 482313 7.7 467 442 16.9 523 478 23.9 488313 7 477 414 15.1 511 484 22.6 507313 6.7 481 337 13.2 435 458 19 517313 6.6 483 354 10.7 487 424 15 524314 6.3 488 345 9.3 493 409 12.5 537319 6.1 499 337 8.4 493 390 10.3 542350 4.8 570 330 7 503 409 8.9 591378 4.5 621 367 6 576 449 7.3 678406 3.6 687 425 5.2 683 499 6.6 769430 3.4 732 462 4.6 757 544 5.8 859462 3.3 789 500 4.2 830 573 5.3 919494 3.3 844 535 3.9 896 616 4.9 1000600 3.3 1025 570 3.9 955 635 5 1028644 3.3 1100 617 3.7 1040 648 4.7 1058654 3.3 1117 629 3.7 1060 654 4.8 1065690 3.3 1178 635 3.6 1074 664 4.5 1091733 3.3 1252 639 3.7 1077 670 4.7 1094754 3.4 1284 647 3.7 1091
8/15/084/22/08 5/30/08
Sweeney LakeC = Measured Conductivity (υS/cm)T = Temperature (oC)SC = calculated specific conductance (υS/cm)Depth
(m) C T SC C T SC C T SC C T SC C T SC C T SC C T SC0 923 29.2 854 724 18.1 834 641 8.9 926 660 2.3 1165 670 8.4 981 1015 19.5 1134 1113 25.5 1102
-0.5 920 29 855 724 18 836 640 8.8 927 702 2.7 1223 671 8.3 985 1014 19.4 1135 1112 25.5 1101-1 918 28 868 724 18 836 638 8.7 926 705 2.7 1228 669 8.1 988 1010 19.2 1136 1109 25.3 1103
-1.5 915 28.4 859 720 17.8 835 634 8.3 931 706 2.6 1234 668 8 989 1003 18.9 1135 1107 25.2 1103-2 916 28.3 862 718 17.6 836 633 8.3 929 705 2.6 1232 668 7.9 992 998 18.7 1135 1101 24.7 1107
-2.5 914 28.2 861 717 17.5 837 632 8.3 928 705 2.6 1232 670 7.8 998 996 18.7 1132 1100 24.5 1111-3 910 27.9 862 716 17.4 838 630 8.2 928 706 2.5 1238 694 7.6 1039 994 18.6 1132 1093 24.4 1106
-3.5 900 27.3 862 715 17.4 836 628 8.2 925 706 2.5 1238 742 7.4 1118 990 18 1143 1092 24.3 1107-4 900 27.1 865 715 17.4 836 628 8.2 925 706 2.5 1238 780 6.5 1206 954 16 1152 1089 23.7 1117
-4.5 900 27 867 714 17.4 835 628 8.2 925 706 2.5 1238 807 5.7 1278 923 14 1169 1064 21.4 1143-5 900 27 867 714 17.4 835 628 8.3 922 707 2.5 1240 835 4.8 1360 863 10.9 1181 997 16.5 1190
-5.5 900 27 867 714 17.4 835 628 8.3 922 718 2.6 1255 854 4.3 1412 833 9.2 1193 944 13.5 1210-6 900 26.9 868 714 17.5 833 624 8.4 914 727 2.6 1271 879 3.7 1482 815 8.3 1197 914 12 1216
-6.5 899 26.8 869 714 17.4 835 621 8.5 907 727 2.7 1266 907 3.7 1529 810 8 1199 892 11 1218-7 899 26.8 869 713 17.5 832 723 2.9 1251 948 3.7 1598 809 7.7 1208 887 10.4 1230
-7.5 959 26.6 931 714 17.5 833 710 2.9 1229 939 3.7 1583 880 10.3 1224-8 722 17.6 841
7/13/075/17/078/8/06 9/24/06 11/8/06 2/22/07 4/2/07
C T SC C T SC C T SC C T SC C T SC C T SC C T SC827 20.8 899 540 5.9 850 451 0.1 860 605 0.4 1141 1087 12.5 1428 994 17.3 1165 1105 25.1 1103822 20.3 903 540 5.9 850 520 1.7 937 681 0.9 1262 1046 10.7 1439 994 17.3 1165 1164 25.1 1162819 20.1 904 540 5.9 850 572 1.9 1024 768 1.9 1374 1040 10.5 1438 994 17.3 1165 1095 24.8 1099817 19.9 905 540 5.9 850 700 2.2 1240 774 2 1380 1036 10.4 1437 993 17.3 1164 1089 24.5 1100815 19.8 905 540 5.9 850 702 2.3 1239 774 2 1380 1018 9.7 1438 993 17.3 1164 1087 24.3 1102810 19.5 905 540 5.9 850 702 2.3 1239 777 2 1386 1008 9.3 1440 990 17.1 1166 1086 24.1 1105810 19.5 905 540 5.9 850 703 2.3 1241 785 2 1400 991 8.3 1455 985 16.9 1165 1084 24.1 1103809 19.5 904 540 5.9 850 705 2.3 1245 793 2 1414 968 7.4 1458 972 15.4 1190 1083 23.9 1106800 18.9 905 540 5.9 850 707 2.3 1248 810 2 1445 962 7.1 1462 950 12.8 1239 1084 23.7 1112796 18.6 907 540 5.9 850 710 2.3 1253 823 2 1468 959 6.7 1474 963 10 1350 1128 22.9 1175795 18.5 908 540 5.9 850 712 2.3 1257 845 2 1507 959 6.3 1492 978 8.4 1432 1142 20.7 1244799 18.4 914 541 5.9 852 721 2.3 1273 858 2 1530 959 5.9 1510 988 8 1463 1142 15.7 1389803 18.3 921 541 5.9 852 726 2.3 1282 902 2 1609 962 5.7 1524 990 7.5 1487 1137 13.5 1457812 18 937 545 5.9 858 740 2.3 1306 935 2.1 1662 981 5.2 1578 987 7.1 1500 1111 11.7 1489940 16.4 1125 553 6.1 865 751 2.3 1326 998 2.1 1774 1002 4.8 1631 986 7.1 1498 1098 10.8 1507995 15.4 1218 553 6.1 865 770 2.4 1355 1014 2.1 1802 1006 4.6 1648 988 6.9 1510 1083 10.2 1510989 14.9 1225 563 6.8 863 765 2.7 1333 981 2.2 1738 1005 4.6 1647 971 6.8 1488 1068 10.3 1485
9/17/07 11/16/07 2/8/08 3/14/08 4/22/08 5/30/08 8/15/08
Tanners LakeC = Measured Conductivity (υS/cm)T = Temperature (oC)SC = calculated specific conductance (υS/cm)Depth
(m) C T SC C T SC C T SC C T SC C T SC C T SC C T SC0 680 25.8 670 521 15.9 631 502 7.7 750 425 1.5 771 441 1.6 797 466 5.8 736 629 17.2 739
-0.5 681 25.9 669 521 15.9 631 501 7.6 750 440 2 785 450 2 803 465 5.7 736 627 17 740-1 681 25.9 669 531 15.9 643 500 7.4 753 450 3.1 774 465 2.3 821 464 5.6 737 630 16.9 745
-1.5 680 25.9 669 535 15.9 648 498 7.3 752 453 3.3 774 476 3.1 818 464 5.6 737 631 16.9 746-2 680 25.9 669 537 15.8 651 498 7.2 755 455 3.3 777 477 3.2 817 464 5.6 737 633 16.9 749
-2.5 680 25.9 669 537 15.8 651 496 7.2 751 455 3.3 777 477 3.2 817 464 5.6 737 635 16.8 753-3 679 25.9 668 537 15.8 651 496 7.2 751 456 3.3 779 478 3.2 819 464 5.6 737 637 16.8 755
-3.5 673 25.7 664 537 15.8 651 495 7.2 750 456 3.3 779 478 3.2 819 464 5.6 737 639 16.8 758-4 640 24.9 641 537 15.8 651 494 7.1 751 457 3.3 780 478 3.2 819 464 5.6 737 639 16.8 758
-4.5 647 23.2 670 537 15.7 653 492 7 750 458 3.2 785 479 3.2 821 464 5.6 737 626 15.7 761-5 653 21.8 696 534 15.6 651 491 6.9 750 459 3.2 786 479 3.2 821 466 5.5 743 593 13.3 764
-5.5 623 18.2 716 533 15.5 651 490 6.9 749 461 3.2 790 479 3.2 821 469 5.3 752 575 11.9 767-6 598 15.5 731 528 15.3 648 489 6.9 747 463 3.1 796 480 3.2 822 478 5.1 771 555 10.4 770
-6.5 570 13.8 725 526 15 650 489 6.9 747 465 3 802 482 3.3 823 484 4.8 788 533 9 768-7 569 11.1 775 592 12.8 772 488 6.9 746 467 3 805 484 3.3 827 495 4.5 814 523 8.2 770
-7.5 580 9.7 819 606 10.3 843 487 6.9 744 469 2.9 812 488 3.3 833 508 3.9 851 507 7 773-8 617 7.6 924 636 8.8 921 486 6.9 743 473 2.9 818 493 3.2 845 524 3.8 881 499 6.5 772
-8.5 665 7.1 1010 703 7.6 1053 485 6.9 741 478 3 824 496 3.2 850 536 3.6 907 497 6.1 778-9 738 6.2 1151 763 6.8 1170 485 6.9 741 485 3 836 504 3.1 866 555 3.6 939 493 5.8 778
-9.5 773 5.8 1221 785 6.4 1218 485 6.9 741 494 3 852 519 3.1 892 580 3.5 984 493 5.7 781-10 791 5.5 1260 804 6.1 1258 485 7 739 506 3 873 530 3.1 911 621 3.5 1054 491 5.6 780
-10.5 818 5.2 1315 815 5.9 1283 485 7.1 737 513 3 885 539 3.1 927 679 3.5 1152 490 5.5 781-11 851 5.1 1373 844 5.7 1337 485 7.3 733 537 3 926 550 3.1 945 704 3.5 1195 492 5.4 786
-11.5 878 5 1421 858 5.6 1363 485 7.4 731 551 3 950 555 3.2 951 730 3.4 1243 495 5.3 794-12 899 4.9 1459 896 5.4 1432 485 7.6 726 575 3 992 575 3.1 988 764 3.5 1296 498 5.2 801
-12.5 913 4.9 1482 912 5.4 1458 486 7.7 726 610 3 1052 612 3.1 1052 819 3.5 1390 500 5.2 804-13 927 4.9 1505 915 5.4 1463 532 7.9 790 652 3.1 1121 673 3.2 1153 931 3.5 1580 502 5.2 807
-13.5 931 4.9 1511 916 5.4 1464 888 8.1 1311 756 3.2 1295 796 3.3 1359 967 3.5 1641 503 5.2 809-14 935 4.9 1518 916 5.4 1464 908 8.1 1341 913 3.3 1559 983 3.4 1673 978 3.6 1654 503 5.2 809
-14.5 878 5 1421 866 5.5 1380 847 8.2 1247 873 3.5 1481 954 3.5 1619 992 3.6 1678 704 5.1 1136
5/17/074/1/078/8/06 9/25/06 11/8/06 1/24/07 2/21/07
C T SC C T SC C T SC C T SC C T SC C T SC C T SC C T SC762 23.7 781 661 19.9 732 454 7.5 682 407 0.1 776 440 2.1 782 434 7.9 645 621 16.6 740 741 25.4 735762 23.7 781 663 19.9 735 454 7.4 684 410 0.3 776 440 2.1 782 434 7.9 645 621 16.6 740 737 25.1 736761 23.7 780 663 19.9 735 454 7.4 684 421 1.4 767 440 2.1 782 435 7.8 648 620 16.5 740 731 24.7 735761 23.7 780 663 19.9 735 454 7.4 684 425 1.8 763 444 2.2 787 435 7.8 648 619 16.5 739 728 24.5 735761 23.7 780 662 19.9 733 454 7.4 684 425 1.9 761 446 2.5 782 434 7.7 648 619 16.4 741 726 24.4 734761 23.7 780 662 19.9 733 454 7.4 684 425 2 758 446 2.5 782 434 7.6 650 618 16.4 739 725 24.3 735761 23.7 780 662 19.9 733 454 7.4 684 425 2 758 446 2.5 782 434 7.6 650 618 16.4 739 724 24.2 735761 23.7 780 663 19.9 735 454 7.4 684 426 2 760 446 2.5 782 434 7.5 652 618 16.3 741 724 24 738760 23.7 779 662 20 732 454 7.4 684 425 2 758 446 2.5 782 459 5.7 727 617 16.3 740 722 23.8 739750 22.7 784 662 20 732 454 7.3 686 425 2 758 446 2.5 782 477 5.3 765 583 14.3 733 714 23.1 741690 18.6 786 662 19.9 733 454 7.3 686 425 2.1 755 446 2.5 782 488 4.6 800 565 12.7 738 702 21.6 751666 16 804 666 19.4 746 454 7.3 686 426 2.2 755 446 2.6 780 495 4.2 821 536 10.8 735 652 17.5 761630 13.2 813 678 18 783 454 7.3 686 428 2.3 756 448 2.6 783 496 4 828 524 9.7 740 616 14.7 767591 10.9 809 656 14.7 817 454 7.3 686 432 2.3 763 451 2.6 788 500 3.7 843 513 8.6 747 593 12.7 775572 9.6 810 635 12.6 832 454 7.3 686 438 2.3 773 454 2.6 793 502 3.7 846 513 7.7 766 585 10.7 805558 8.8 808 600 10.5 830 454 7.3 686 443 2.4 779 459 2.7 800 512 3.4 872 525 6.8 805 596 9.3 851549 7.7 820 582 9.4 829 454 7.3 686 444 2.4 781 466 2.7 812 528 3.4 899 544 6.4 844 619 8.4 906540 7.1 821 569 8.6 829 454 7.3 686 450 2.4 792 475 2.7 827 541 3 933 569 6.1 890 643 7.6 963532 6.8 815 561 7.7 838 454 7.3 686 459 2.6 802 488 2.7 850 559 2.9 967 603 5.3 967 656 6.8 1006527 6.1 825 554 7.1 842 454 7.3 686 473 2.6 827 504 2.8 875 571 2.9 988 650 4.8 1058 662 6.5 1024523 6 821 551 6.9 842 454 7.3 686 485 2.7 845 532 2.8 924 666 2.9 1152 660 4.6 1081 667 6.2 1041521 5.9 820 549 6.7 844 454 7.3 686 499 2.7 869 565 2.8 981 700 2.9 1211 685 4.3 1133 669 6.1 1047520 5.6 826 547 6.5 846 454 7.3 686 519 2.7 904 605 2.9 1047 722 3 1245 690 4.2 1145 678 5.9 1067520 5.5 829 546 6.3 849 454 7.3 686 534 2.7 930 644 2.9 1114 755 3 1302 698 4.1 1162 682 5.8 1077525 5.4 839 546 6.2 852 454 7.3 686 588 2.7 1024 681 2.9 1178 818 3.1 1406 705 4.1 1173 687 5.6 1091529 5.4 846 546 6.2 852 454 7.3 686 633 2.8 1099 730 3 1259 847 3.1 1456 726 3.9 1216 691 5.6 1098529 5.4 846 546 6.1 854 454 7.3 686 672 2.9 1163 787 3 1357 865 3.1 1487 751 3.8 1262 692 5.6 1099534 5.3 856 546 6 857 454 7.3 686 778 2.9 1346 860 3.1 1478 878 3.1 1509 751 3.7 1266 692 5.5 1103531 5.3 851 546 6 857 454 7.3 686 745 3 1285 908 3.1 1561 924 3.2 1583 751 3.7 1266 692 5.5 1103581 5.3 931 621 5.9 978 537 7.1 816 808 3.2 1384 992 3.1 1705 830 3.4 1413 747 3.7 1259 703 5.6 1117
7/13/07 9/12/07 11/16/07 2/8/08 3/13/08 4/22/08 5/30/08 8/15/08
Lake Area Vs Depth profilesTanners Lake Lake McCarronmeters hectare meters hectare
0.00 30.61 0 27.03783.05 21.63 3.048 20.14474.57 18.28 4.572 17.410956.10 15.18 6.096 14.924259.14 7.51 9.144 11.54655
12.19 1.38 12.192 7.6261513.72 0.06 15.24 3.34125
17.3736 0.081Sweeney Lakemeters hectare Lake Gervais
0.00 25.08 meters hectare1.52 17.91 0 93.153.05 14.69 1.524 70.66444.57 11.44 3.048 61.77876.10 5.66 4.572 53.196757.62 0.46 6.096 42.4035
7.62 25.25589.144 10.0683
Parkers Lake 10.668 4.70205meters hectare 12.192 1.38915
0 40.7025 13.716 0.29971.524 32.08005 14.9352 0.02433.048 16.07854.572 10.2627 Cedar Lake6.096 6.9255 meters hectare7.62 4.45095 0 72.07785
9.144 2.16675 3.048 50.8396510.668 0.5589 4.572 44.85375
11.2776 0.02835 6.096 36.50679.144 15.8274
12.192 5.5485Ryan Lake 15.24 0.0729meters hectare
0.00 6.99 Bryant Lake1.52 4.39 meters hectare3.05 3.83 0 66.0154.57 3.27 1.524 51.4356.10 2.46 3.048 43.92637.62 1.43 4.572 34.177959.14 0.60 6.096 24.04485
10.06 0.02 9.144 5.9251512.192 1.555213.716 0.08505
ANION CHROMATOGRAPHY RESULTSSAMPLES TAKEN 11/15/07CUSTOMER: ERIC NOVOTNY - CIVIL ENGINEERING - AREA LAKESDATE: 03 - 06 - 2008ANALYST: RICK KNURRSYSTEM: DIONEX ICS-2000 Chromatograph - AS20 (4mm) - AMMS III (4mm) SuppressorCONDITIONS: NaOH gradient - 1ml/min - Suppression w/ 25 mN Sulfuric Acid - 50 ul loop
All concentrations are in ppm (ug/g)
SAMPLE DESCRIPTION Fluoride Chloride Nitrite-N Bromide Nitrate-N Sulfate Phosphate-P
Detection Limits <0.005 <0.005 <0.002 <0.005 <0.001 <0.010 <0.002BROWNIE 1 M 0.101 134.4 <0.002 0.032 0.687 4.691 0.005BROWNIE 13 M <0.005 703.7 <0.002 0.256 0.006 0.212 0.004
BRYANT 1 M 0.167 83.68 <0.002 0.034 0.953 8.701 0.052BRYANT 12 M 0.168 84.01 <0.002 0.034 0.922 8.744 0.045
CEDAR 1 M 0.100 96.44 0.002 0.028 0.585 9.915 0.013CEDAR 13.5 M 0.100 95.99 0.002 0.028 0.451 9.881 0.008
GERVAIS 1 M 0.104 109.4 0.002 0.031 0.761 12.95 0.046GERVAIS 12 M 0.104 108.6 <0.002 0.033 0.758 12.88 0.047
MCCARRON 1 M 0.075 102.3 0.022 0.057 0.302 30.05 0.011MCCARRON 15 M 0.076 102.8 0.001 0.053 0.858 30.19 <0.002
PARKERS 1 M 0.202 146.2 0.001 0.044 0.369 13.53 0.019PARKERS 10 M 0.202 146.0 <0.002 0.043 0.315 13.53 0.009
RYAN 1 M 0.089 82.29 0.001 0.019 1.683 5.731 0.083RYAN 10 M 0.091 83.01 0.005 0.019 1.697 5.787 0.107
SWEENY 1 M 0.109 125.6 0.001 0.112 0.522 36.00 <0.002SWEENY 7 M 0.110 127.7 0.001 0.116 0.507 36.71 <0.002
TANNERS 1 M 0.093 132.0 0.015 0.025 0.648 15.35 0.095TANNERS 12.5 M 0.092 131.5 0.004 0.026 0.493 15.38 0.080
CATION CHROMATOGRAPHY RESULTSSAMPLES TAKEN 11/15/07CUSTOMER: ERIC NOVOTNY - CIVIL ENGINEERING - AREA LAKESDATE: 03 - 06 - 2008ANALYST: RICK KNURRSYSTEM: DIONEX ICS-2000 Chromatograph - CS16 (4mm) - CSRS Ultra II (4mm) Suppressor CONDITIONS: 25 mM Methane sulfonic acid eluent - 1ml/min - AutoSuppression - 100 ul loop
All concentrations are in ppm (ug/g)
SAMPLE DESCRIPTION Lithium Sodium Ammonium Potassium Magnesium Calcium Strontium
Detection Limits <0.0001 <0.002 <0.005 <0.002 <0.005 <0.005 <0.005BROWNIE 1 M 0.0070 84.55 0.117 2.345 3.946 19.14 0.023BROWNIE 13 M 0.0223 419.8 55.38 12.46 12.87 60.22 0.128
BRYANT 1 M 0.0043 48.18 0.377 2.974 15.31 41.16 0.048BRYANT 12 M 0.0041 47.22 0.127 2.992 15.44 41.40 0.054
CEDAR 1 M 0.0163 58.88 0.133 3.102 8.911 36.25 0.044CEDAR 13.5 M 0.0164 58.78 0.116 3.829 8.716 37.14 0.044
GERVAIS 1 M 0.0041 58.53 0.128 2.767 11.86 41.80 0.043GERVAIS 12 M 0.0044 59.44 0.116 2.872 12.09 42.49 0.038
MCCARRON 1 M 0.0036 53.64 1.389 3.273 15.62 46.23 0.051MCCARRON 15 M 0.0039 53.05 0.958 3.304 15.52 45.84 0.058
PARKERS 1 M 0.0094 91.33 0.117 2.400 14.83 36.30 0.057PARKERS 10 M 0.0097 92.04 0.107 2.371 14.94 36.44 0.046
RYAN 1 M 0.0026 51.47 0.135 3.116 6.282 42.59 0.027RYAN 10 M 0.0023 51.46 0.123 3.100 6.246 42.78 0.024
SWEENY 1 M 0.1281 55.56 0.129 3.454 24.72 75.13 0.073SWEENY 7 M 0.1342 56.49 0.112 3.483 25.41 77.92 0.067
TANNERS 1 M 0.0027 68.88 0.114 3.173 13.95 44.46 0.049TANNERS 12.5 M 0.0028 69.23 0.117 3.143 13.94 44.23 0.045
ANION CHROMATOGRAPHY RESULTSSAMPLES TAKEN 2/22/2007CUSTOMER: ERIC NOVOTNY - CIVIL ENGINEERINGDATE: 03 - 22 - 2007ANALYST: RICK KNURRSYSTEM: DIONEX ICS-2000 Chromatograph - AS20 (4mm) - Atlas Anion ES (4mm) CONDITIONS: KOH gradient - 1ml/min - External Water Mode - 50 ul loop
All concentrations are in ppm (ug/g)
SAMPLE DESCRIPTION Fluoride Chloride Nitrite-N Bromide Nitrate-N Sulfate Phosphate-P
Detection Limits <0.005 <0.005 <0.002 <0.005 <0.001 <0.010 <0.002PARKERS 1 M 0.221 144.7 0.004 0.041 0.08 14.10 0.008PARKERS 10 M 0.239 307.4 0.014 0.061 0.19 19.48 0.038MCCARRONS 1 M 0.065 105.3 0.008 0.055 0.05 38.60 0.006MCCARRONS 14 M 0.067 140.9 0.006 0.072 0.02 36.35 0.004SWEENY 1 M 0.119 189.8 0.006 0.153 0.17 55.51 0.004SWEENY 6.5 M 0.117 194.2 0.008 0.157 0.17 56.73 0.005TANNERS 1 M 0.081 140.8 0.007 0.034 0.34 15.17 0.039TANNERS 12 M 0.089 195.7 0.008 0.045 0.43 15.68 0.045GERVAIS 1 M 0.104 132.0 0.021 0.042 0.09 13.50 0.028GERVAIS 12.5 M 0.103 135.1 0.010 0.047 0.03 15.96 0.074BROWNIE 1 M 0.090 185.8 0.009 0.042 0.30 5.680 0.012BROWNIE 12.5 M 0.112 614.8 0.005 0.192 0.01 1.717 0.005BRYANT 1 M 0.167 79.48 0.021 0.039 0.22 7.798 0.003BRYANT 12 M 0.177 101.4 0.004 0.045 0.04 10.07 0.002RYAN 1 M 0.087 99.39 0.014 0.019 0.31 5.574 0.066RYAN 10 M 0.089 186.0 0.037 0.041 0.10 4.047 0.312CEDAR 1 M 0.093 104.8 0.051 0.036 0.27 10.73 0.025CEDAR 12 M 0.094 103.5 0.014 0.038 0.09 10.78 0.033
Sediment core samples (depth in cm)MCCARRONS 0 - 4 0.092 118.6 <0.010 0.117 0.162 77.76 0.014MCCARRONS 28 - 32 0.104 69.60 <0.010 0.096 0.077 17.09 0.007MCCARRONS 60 - 64 0.087 57.58 <0.010 0.172 0.076 3.553 0.009MCCARRONS 92 - 96 0.057 41.92 <0.010 0.166 0.067 1.899 <0.010MCCARRONS 116 - 120 0.063 34.15 <0.010 0.179 0.104 3.044 <0.010
Sediment core samples (depth in cm)TANNERS 0 - 4 0.167 409.4 0.014 0.106 0.220 35.91 0.044TANNERS 28 - 32 0.151 217.3 <0.010 0.127 0.069 4.637 0.012TANNERS 60 - 64 0.103 146.1 <0.010 0.116 0.112 1.525 0.008TANNERS 92 - 96 0.079 88.02 <0.010 0.115 0.077 0.929 <0.010TANNERS 116 - 120 0.078 77.73 <0.010 0.108 0.063 3.380 <0.010
CATION CHROMATOGRAPHY RESULTSSAMPLES TAKEN 2/22/2007CUSTOMER: ERIC NOVOTNY - CIVIL ENGINEERINGDATE: 03 - 22 - 2007ANALYST: RICK KNURRSYSTEM: DIONEX ICS-2000 Chromatograph - CS16 (4mm) - Atlas Cation ES (4mm) CONDITIONS: 25 mM Methane sulfonic acid - 1ml/min - External Water Mode - 25 ul loop
All concentrations are in ppm (ug/g)
SAMPLE DESCRIPTION Lithium Sodium Ammonium Potassium Magnesium Calcium
Detection Limits <0.0001 <0.002 <0.005 <0.002 <0.005 <0.005PARKERS 1 M 0.0079 96.56 0.263 2.629 17.33 33.87PARKERS 10 M 0.0074 203.8 0.829 2.853 20.67 50.90MCCARRONS 1 M 0.0020 53.11 0.999 3.403 16.73 47.62MCCARRONS 14 M 0.0031 75.93 2.061 3.490 18.65 58.27SWEENY 1 M 0.1550 86.88 0.731 4.194 37.58 108.8SWEENY 6.5 M 0.1464 123.5 0.748 4.312 37.38 107.3TANNERS 1 M <0.0005 85.77 0.526 3.542 16.91 51.52TANNERS 12 M <0.0005 104.8 0.400 3.434 16.42 51.41GERVAIS 1 M <0.0005 73.14 0.786 3.122 15.34 48.50GERVAIS 12.5 M <0.0005 71.06 1.975 3.243 18.51 57.60BROWNIE 1 M 0.0041 113.3 0.793 2.883 4.690 20.61BROWNIE 12.5 M 0.0143 366.9 36.22 9.988 10.61 48.71BRYANT 1 M 0.0033 48.82 0.676 3.234 18.07 43.39BRYANT 12 M 0.0039 55.70 2.148 3.226 17.57 45.44RYAN 1 M <0.0005 63.35 4.120 4.038 7.661 50.60RYAN 10 M <0.0005 122.7 7.184 4.409 7.775 50.69CEDAR 1 M 0.0142 66.58 1.839 3.772 10.01 40.90CEDAR 12 M 0.0142 60.41 1.267 3.416 9.490 38.92
Sediment core samples (depth in cm)MCCARRONS 0 - 4 <0.0005 69.81 39.84 6.393 26.45 103.2MCCARRONS 28 - 32 <0.0005 36.07 42.79 5.724 17.88 62.05MCCARRONS 60 - 64 <0.0005 31.79 52.79 5.582 27.20 84.51MCCARRONS 92 - 96 <0.0005 19.53 51.85 4.652 19.83 62.76MCCARRONS 116 - 120 <0.0005 13.54 49.74 4.105 13.38 47.15
Sediment core samples (depth in cm)TANNERS 0 - 4 <0.0005 247.4 18.66 6.690 20.35 73.96TANNERS 28 - 32 <0.0005 128.8 38.33 6.918 17.21 66.66TANNERS 60 - 64 <0.0005 71.44 37.76 5.122 14.21 62.01TANNERS 92 - 96 <0.0005 47.59 43.13 5.323 14.26 72.27TANNERS 116 - 120 <0.0005 36.07 42.67 5.190 13.54 63.68
Waster water treatmentplant effluent data
Date LocationsChloride (mg/L)
Sodium (mg/L)
6/20/07 BLUE_LAKE 401 2857/3/07 BLUE_LAKE 418 2927/25/07 BLUE_LAKE 396 2748/1/07 BLUE_LAKE 400 2878/8/07 BLUE_LAKE 386 2908/22/07 BLUE_LAKE 308 2499/5/07 BLUE_LAKE 366 2839/19/07 BLUE_LAKE 403 29610/3/07 BLUE_LAKE 368 27210/17/07 BLUE_LAKE 381 26310/31/07 BLUE_LAKE 370 27511/14/07 BLUE_LAKE 365 27611/28/07 BLUE_LAKE 397 27612/12/07 BLUE_LAKE 414 30112/26/07 BLUE_LAKE 426 3181/9/08 BLUE_LAKE 410 2841/23/08 BLUE_LAKE 369 2862/6/08 BLUE_LAKE 389 2852/20/08 BLUE_LAKE 364 3193/5/08 BLUE_LAKE 395 2963/19/08 BLUE_LAKE 412 2874/2/08 BLUE_LAKE 393 2714/16/08 BLUE_LAKE 360 2424/30/08 BLUE_LAKE 344 2235/14/08 BLUE_LAKE 374 2435/28/08 BLUE_LAKE 408 2616/11/08 BLUE_LAKE 2496/25/08 BLUE_LAKE 384 2437/9/08 BLUE_LAKE 390 2487/23/08 BLUE_LAKE 392 62.68/6/08 BLUE_LAKE 385 2918/20/08 BLUE_LAKE 382 2429/3/08 BLUE_LAKE 435 2779/17/08 BLUE_LAKE 418 27810/1/08 BLUE_LAKE 377 28410/15/08 BLUE_LAKE 416 30810/29/08 BLUE_LAKE 410 30911/12/08 BLUE_LAKE 430 3026/20/07 COTTAGE_GR 353 2567/3/07 COTTAGE_GR 340 2517/25/07 COTTAGE_GR 342 2518/1/07 COTTAGE_GR 337 2618/8/07 COTTAGE_GR 347 2638/22/07 COTTAGE_GR 307 237
9/5/07 COTTAGE_GR 315 2379/19/07 COTTAGE_GR 365 26610/3/07 COTTAGE_GR 343 25710/17/07 COTTAGE_GR 343 26210/31/07 COTTAGE_GR 348 26311/14/07 COTTAGE_GR 330 26311/28/07 COTTAGE_GR 368 26312/12/07 COTTAGE_GR 389 28112/26/07 COTTAGE_GR 376 2761/9/08 COTTAGE_GR 376 2551/23/08 COTTAGE_GR 335 2472/6/08 COTTAGE_GR 351 2722/20/08 COTTAGE_GR 327 2653/5/08 COTTAGE_GR 322 2503/19/08 COTTAGE_GR 372 2654/2/08 COTTAGE_GR 372 2634/16/08 COTTAGE_GR 350 2474/30/08 COTTAGE_GR 336 2515/14/08 COTTAGE_GR 330 2385/28/08 COTTAGE_GR 336 2456/11/08 COTTAGE_GR 302 2166/25/08 COTTAGE_GR 356 2277/9/08 COTTAGE_GR 356 2187/23/08 COTTAGE_GR 337 54.68/6/08 COTTAGE_GR 334 2458/20/08 COTTAGE_GR 376 2459/3/08 COTTAGE_GR 342 2419/17/08 COTTAGE_GR 387 25910/1/08 COTTAGE_GR 388 26910/15/08 COTTAGE_GR 366 26210/29/08 COTTAGE_GR 336 24111/12/08 COTTAGE_GR 370 2676/20/07 METRO 246 1897/3/07 METRO 209 1667/11/07 METRO 248 1877/24/07 METRO 223 1737/25/07 METRO 232 1807/26/07 METRO 238 1877/27/07 METRO 234 1967/30/07 METRO 217 1877/31/07 METRO 218 1858/1/07 METRO 232 1958/2/07 METRO 239 2028/3/07 METRO 234 1968/6/07 METRO 206 1708/7/07 METRO 220 1718/8/07 METRO 228 1888/22/07 METRO 211 1809/5/07 METRO 200 180
9/19/07 METRO 223 19410/3/07 METRO 226 18310/17/07 METRO 225 17510/31/07 METRO 251 19411/14/07 METRO 232 19211/28/07 METRO 255 18712/12/07 METRO 268 20512/26/07 METRO 260 1961/9/08 METRO 266 2071/23/08 METRO 270 1702/6/08 METRO 268 2072/20/08 METRO 248 1983/5/08 METRO 272 1893/19/08 METRO 278 1944/2/08 METRO 297 2244/16/08 METRO 248 1844/30/08 METRO 248 1745/14/08 METRO 263 1725/28/08 METRO 232 1586/11/08 METRO 240 1756/25/08 METRO 244 1747/9/08 METRO 240 6337/23/08 METRO 242 1678/6/08 METRO 248 1838/20/08 METRO 258 1869/3/08 METRO 208 1629/17/08 METRO 270 18710/1/08 METRO 269 20010/15/08 METRO 230 18610/29/08 METRO 232 19611/12/08 METRO 244 1996/20/07 SENECA 298 4507/3/07 SENECA 274 3907/25/07 SENECA 274 4208/1/07 SENECA 273 4248/8/07 SENECA 296 4828/22/07 SENECA 235 3989/5/07 SENECA 249 3749/19/07 SENECA 291 46210/3/07 SENECA 263 39310/17/07 SENECA 265 48610/31/07 SENECA 257 39211/14/07 SENECA 278 34811/28/07 SENECA 278 44112/12/07 SENECA 294 39212/26/07 SENECA 312 4631/9/08 SENECA 292 3851/23/08 SENECA 276 4252/6/08 SENECA 294 452
2/20/08 SENECA 274 4133/5/08 SENECA 271 3363/19/08 SENECA 305 3614/2/08 SENECA 308 4434/16/08 SENECA 282 3904/30/08 SENECA 276 3425/14/08 SENECA 291 4215/28/08 SENECA 276 2806/11/08 SENECA 274 3316/25/08 SENECA 285 3187/9/08 SENECA 258 3787/23/08 SENECA 288 94.78/6/08 SENECA 291 4728/20/08 SENECA 293 4599/3/08 SENECA 293 3419/17/08 SENECA 296 46610/1/08 SENECA 305 45710/15/08 SENECA 294 49210/29/08 SENECA 240 48811/12/08 SENECA 284 547
Grab sample Sodium and chloride concentrations from the Metropolitan council
DateChloride, Filtered
Sodium, Filtered Date
Chloride, Filtered
Sodium, Filtered Date
Chloride, Filtered
Sodium, Filtered
2/8/08 43.5 2/4/08 14.4 2/6/08 40.71/10/08 38 35.8 1/7/08 15 12.3 1/9/08 43 32.811/30/07 36 28.4 11/26/07 15 11.8 11/29/07 35 26.111/2/07 24 19.6 10/29/07 13 9.63 10/31/07 21 16.510/5/07 18 12.3 10/1/07 18 15.2 10/3/07 42 32.79/27/07 35 29.7 9/24/07 18 14.2 9/26/07 45 33.29/20/07 35 30.3 9/17/07 16.8 9/18/07 56 43.39/7/07 28 24.7 9/4/07 22 17.1 9/5/07 38 30.38/23/07 16 13.9 8/20/07 21 16.4 8/22/07 52 41.78/9/07 40 42.9 8/6/07 16 14.2 8/8/07 55 47.27/27/07 35 39.5 7/23/07 19 14.6 7/25/07 43 40.77/13/07 27 34.2 7/9/07 12 7/10/07 33 31.26/29/07 22 26.3 6/25/07 11 9.42 6/27/07 29 23.46/14/07 22 23.7 6/11/07 8 7.64 6/13/07 22 20.16/8/07 23 22.3 6/4/07 11 8.77 6/6/07 23 195/18/07 24 25.3 5/14/07 15 9 5/16/07 25 21.15/4/07 24 25.4 4/30/07 12 7.8 5/2/07 22 17.34/20/07 21 18.9 4/16/07 16 9.02 4/18/07 23 174/6/07 20 12.8 4/2/07 13 7.4 4/4/07 20 11.93/23/07 13 6.96 3/19/07 11.9 3/21/07 11.23/9/07 56 50.1 3/5/07 25 21.1 3/6/07 79 56.22/16/07 52 50.9 2/12/07 36 25 2/14/07 60 492/7/07 50 44.5 1/29/07 19 15.7 2/1/07 60 44.31/5/07 45 42.4 1/4/07 24 17.5 1/2/07 55 4312/1/06 48 47 11/27/06 18.8 11/29/06 51 41.911/6/06 54 55.8 10/30/06 19 14.1 11/1/06 50 39.910/20/06 45 45.2 10/3/06 21 15.1 10/18/06 53 39.310/4/06 50 51.1 9/18/06 24 17.4 10/3/06 51 39.79/29/06 48 45.9 9/6/06 15.8 9/19/06 60 43.69/22/06 47 46.8 7/31/06 16.5 9/15/06 57 43.99/5/06 45.6 7/17/06 19 14.5 9/15/06 58 447/31/06 38.9 7/5/06 16 12 9/8/06 52 38.97/21/06 34 32.5 6/12/06 15 9.78 9/8/06 51 38.97/12/06 32 27.8 5/31/06 19 10.6 9/1/06 51 40.87/7/06 28 24.6 5/16/06 14 8.41 9/1/06 51 416/28/06 26 19 5/2/06 18 9.45 8/25/06 57 42.16/20/06 20 12.8 4/17/06 16 8.63 8/25/06 55 42.46/14/06 22 17.6 4/4/06 7.2 8/18/06 52 39.76/9/06 28 24.4 3/15/06 8/18/06 52 40.96/2/06 26 24.5 2/27/06 18 12.3 8/11/06 51 41.15/25/06 25 22.1 2/13/06 21 12.4 8/11/06 51 40.7
Minnesota River at Jordan (Minnesota river mile 39.6)
Mississippi River at anoka (Upper Mississippi River mile
871.6)
Mississippi River at Hastings (Upper Mississippi River mile
815.6)
5/19/06 20 22.3 1/30/06 33 19.4 8/4/06 49 39.95/12/06 22 20.4 1/19/06 18 11.4 8/4/06 49 39.45/5/06 22 13.7 1/5/06 20 10.8 7/28/06 51 39.84/27/06 22 20.3 12/20/05 21 12.4 7/28/06 51 404/19/06 21 18.6 12/6/05 22 12 7/19/06 44 36.54/14/06 20 14.5 11/17/05 22 13.8 7/5/06 32 254/7/06 21 11.5 11/3/05 21 11.5 6/14/06 27 22.23/31/06 23 15.6 10/17/05 17 8.9 5/30/06 22 17.73/24/06 26 21.3 10/3/05 20 10.8 5/17/06 20 16.23/17/06 9/13/05 18 11.5 5/3/06 23 17.13/10/06 29 23.7 8/29/05 20 14.3 4/19/06 20 15.63/3/06 33 26.3 8/16/05 14 10.8 4/5/06 20 12.62/16/06 30 23.1 8/2/05 16 11.6 3/15/062/3/06 27 16.2 7/20/05 17 11.8 3/1/06 34 25.41/20/06 31 25.3 7/7/05 9.07 2/21/06 36 27.81/6/06 32 23 6/14/05 12 6.55 2/1/06 34 23.8
12/16/05 33 26.9 6/1/05 14 8.62 1/18/06 30 21.312/2/05 33 22.2 5/16/05 18 10.1 1/4/06 34 22.411/18/05 33 27.5 5/4/05 9.32 12/14/05 31 19.811/4/05 30 24.4 4/20/05 16 7.01 11/30/05 37 22.210/27/05 28 21.1 4/4/05 12 6.32 11/16/05 32 23.210/20/05 25 18.8 3/21/05 20 12 11/2/05 27 18.710/6/05 19 10.8 3/7/05 22 14.3 10/19/05 21 13.79/21/05 27 22.9 2/14/05 18 12.6 10/5/05 21 13.19/16/05 29 27 2/3/05 16 12.2 9/14/05 35 27.19/9/05 28 28.8 1/5/05 14 11 8/31/05 33 26.49/2/05 31 31.5 12/14/04 13 9.38 8/17/05 35 27.98/25/05 23 19.4 12/1/04 15 9.29 8/3/05 30 25.38/17/05 36 35.7 11/15/04 15 9.88 7/20/05 26 22.48/12/05 33 33.5 11/1/04 14 8.56 7/6/05 21 158/4/05 26 28.9 10/20/04 12 9.03 6/15/05 17 11.47/29/05 27 29.7 10/5/04 12 8.89 6/1/05 20 12.77/22/05 24 29.1 9/13/04 14 9.8 5/18/05 22 12.57/15/05 24 26.3 8/30/04 19 13.5 5/4/05 23 14.67/8/05 24 21.2 8/16/04 18 11.6 4/20/05 20 11.16/29/05 25 20.2 8/2/04 17 11.4 4/6/05 17 9.686/23/05 25 18.4 7/19/04 17 9.86 3/23/05 51 36.16/17/05 25 17.2 7/6/04 18 10.5 3/9/05 43 29.66/9/05 26 15.7 6/14/04 14 6.65 2/16/05 45 31.46/3/05 27 18.2 6/1/04 16 8.53 2/8/05 58 41.25/26/05 24 16 5/17/04 13 8.98 1/20/05 42 31.25/20/05 23 13.3 5/3/04 12 8.72 1/6/05 46 34.75/12/05 27 16.9 4/13/04 11 8.28 12/15/04 32 22.75/6/05 30 21.7 3/29/04 15 10.3 12/6/04 31 22.74/29/05 26 18.3 3/15/04 23 16.5 11/17/04 26 19.74/22/05 25 15.8 3/1/04 20 14.7 11/3/04 25 17.34/15/05 25 13.1 2/17/04 17 13.4 10/20/04 28 19.54/8/05 23 14.9 2/3/04 14 11.2 10/4/04 22 14.93/31/05 21 13.1 1/20/04 15 11.9 9/15/04 34 23.4
3/25/05 33 27.9 1/5/04 16 11.4 9/1/04 42 29.53/17/05 48 38.5 12/15/03 18 13.4 8/18/04 36 24.13/11/05 31 25.5 12/1/03 18 13.2 8/4/04 36 25.13/3/05 37 28.9 11/3/03 19 14 7/21/04 28 16.72/17/05 45 30.5 9/29/03 17 12.6 7/9/04 31 19.22/8/05 47 39.8 9/16/03 18 12 6/16/04 19 10.91/25/05 47 39.6 9/2/03 18 12.6 6/3/04 23 13.31/11/05 44 39.4 8/4/03 15 9.75 5/19/04 40 27.212/22/04 41 32.5 6/30/03 9 4.89 5/5/04 31 2212/8/04 35 27.4 6/3/03 18 8.7 4/14/04 25 18.311/22/04 36 31.6 5/27/03 17 8.48 3/31/04 29 20.211/9/04 30 22.6 5/5/03 19 8.39 3/17/04 47 32.510/21/04 29 20.9 2/18/03 16 10.4 3/3/04 70 48.810/8/04 26 17.3 2/4/03 18 13.3 2/19/04 63 46.29/16/04 33 28.5 12/2/02 18 10.4 2/5/04 59 449/2/04 33 26.9 11/18/02 19 11.2 1/26/04 55 40.18/19/04 28 20.8 11/4/02 16 9.33 1/8/04 49 35.18/12/04 10/15/02 17 12/17/03 61 46.98/5/04 27 19 9/30/02 17 9.58 12/3/03 64 43.97/22/04 26 16.4 9/16/02 16 8.69 11/19/03 50 36.77/8/04 24 15.3 9/3/02 15 7.83 11/5/03 48 36.86/17/04 18 9.82 8/19/02 13 10/15/03 51 37.76/10/04 24 8/5/02 12 7.05 10/1/03 46 33.36/4/04 16 8.72 7/1/02 10 5.34 9/17/03 42 30.25/27/04 26 14.9 6/10/02 18 10.5 9/4/03 47 35.25/20/04 48 35.7 6/3/02 16 9.88 8/20/03 35 24.45/13/04 52 39.4 4/29/02 13 8.06 8/6/03 28 20.75/7/04 48 40.6 2/19/02 14 11.6 7/16/03 18 12.14/30/04 48 43.9 2/4/02 11 10.8 7/2/03 17 10.44/22/04 44 39.8 1/22/02 10 9.84 6/18/03 26 174/15/04 38 35.4 11/14/01 9 8.77 6/5/03 28 17.54/1/04 31 27.5 11/1/01 4 4.37 5/29/03 24 15.83/18/04 31 25.2 7/30/01 10 8.46 5/21/03 23 14.33/8/04 45 39 5/7/01 11 5.88 5/7/03 28 17.42/25/04 79 70 4/30/01 9 4.98 4/16/03 33 23.42/20/04 65 59.4 2/20/01 10 4/2/03 31 20.12/13/04 70 66.7 2/9/01 13 10.9 3/19/03 85 60.22/6/04 70 65.6 1/16/01 9.96 3/5/03 51 32.31/30/04 70 64.6 11/17/00 9 7.4 2/20/03 51 29.51/23/04 73 65.7 9/18/00 11 9.09 2/6/03 61 43.41/16/04 71 66.4 7/31/00 14 9.4 1/23/03 40 29.91/9/04 70 65.3 5/1/00 17 11.7 1/8/03 32 25.1
12/30/03 63 59.2 2/9/00 13 11.6 12/18/02 36 25.712/23/03 66 62.4 12/4/02 34 2212/11/03 69 67.7 11/20/02 28 19.612/5/03 70 65.1 11/12/02 28 19.511/25/03 63 62.6 10/16/02 22 13.211/21/03 59 59.5 10/2/02 31 20.711/13/03 60 59 9/18/02 23 14.4
11/7/03 63 61.6 9/5/02 22 13.510/30/03 60 53.2 8/21/02 21 14.710/17/03 58 52.8 8/7/02 18 1210/3/03 57 55.5 7/17/02 16 11.59/19/03 45 39.3 7/2/02 17 129/5/03 41 41.2 6/26/02 20 12.48/22/03 36 31.5 6/12/02 27 18.58/7/03 30 28.1 6/5/02 28 19.67/18/03 25 18.8 5/15/02 22 15.67/3/03 25 16.3 5/1/02 22 16.36/20/03 28 4/17/02 16 12.76/6/03 29 21.1 4/3/02 30 21.15/30/03 29 20.9 3/20/02 61 48.15/23/03 26 3/6/02 38 29.15/9/03 28 20.6 2/21/02 34 26.54/18/03 33 2/6/02 40 31.84/3/03 26 19.3 1/24/02 32 26.83/20/03 28 1/9/02 33 24.73/7/03 12/19/01 30 22.82/21/03 61 12/5/01 33 27.12/7/03 61 53.5 11/19/01 29 23.4
12/20/02 39 34.3 11/8/01 28 22.612/6/02 48 38.5 10/17/01 36 28.711/14/02 36 30.8 10/3/01 37 29.110/18/02 27 9/19/01 38 25.910/4/02 40 34.5 9/6/01 32 259/19/02 35 30.8 8/15/01 27 21.79/6/02 27 22.5 8/1/01 22 17.48/23/02 23 7/18/01 23 18.48/8/02 18 17.9 7/5/01 17 14.28/2/01 20 18.6 6/20/01 11 7.837/6/01 18 6/6/01 16 12.46/6/01 19 5/23/01 16 13.15/10/01 15 12.6 5/9/01 13 9.75/4/01 12 10.9 4/4/01 30 23.14/5/01 9 3/19/01 53 39.53/9/01 3/6/01 51 40.52/23/01 54 2/21/01 40 342/13/01 53.7 2/8/01 43 32.91/9/01 1/17/01 42 31.512/8/00 1/5/01 33 23.911/22/00 54 46.6 12/19/00 41 31.511/7/00 60 54.1 12/6/00 26 22.210/6/00 11/20/00 24 19.29/21/00 63 49.7 11/2/00 36 26.49/8/00 48 10/17/00 45 31.88/4/00 35 30.4 10/3/00 46 34.85/8/00 37 36.9 9/19/00 45 314/7/00 33 9/6/00 37 25.4
3/3/00 32 8/15/00 40 29.48/1/00 30 21.77/21/00 22 157/6/00 24 16.96/16/00 27 18.76/2/00 26 175/17/00 21 17.35/2/00 30 23.74/18/00 24 19.84/4/00 28 21.13/14/00 24 17.82/29/00 49 40.62/15/00 39 31.52/3/00 36 281/27/00 34 26.41/4/00 39 29.9
Chloride data (mg/L) from 10 streams located in the TCMA
DateBasset Creek Date
Battle Creek Date
Bluff Creek Date
Carver Creek Date
Credit River Date
Fish Creek Date
Minnehaha Creek Date
Nine Mile Date
Riley Creek Date
Shingle Creek
1/24/01 186 9/18/01 108 1/6/00 55 1/4/00 24 7/7/00 36 7/22/01 67 1/12/01 105 1/6/00 133 1/12/01 471/29/01 1031 4/12/02 177 2/2/00 49 2/2/00 24 7/12/00 30 9/18/01 106 1/30/01 192 2/25/00 122 1/29/01 44 3/7/01 8043/30/01 148 5/5/02 139 2/28/00 71 2/25/00 35 10/4/00 36 12/6/01 125 3/6/01 1166 2/26/00 182 1/30/01 148 4/3/01 161
4/3/01 140 6/3/02 101 5/9/00 61 2/28/00 38 11/8/00 60 4/12/02 121 3/20/01 169 4/12/00 132 3/30/01 55 5/2/01 884/6/01 108 6/7/02 94 6/4/00 51 3/6/00 47 11/29/00 53 5/9/02 170 3/30/01 181 4/19/00 60 4/2/01 69 6/26/01 1174/9/01 99 6/18/02 139 6/20/00 58 5/18/00 43 1/9/01 72 6/7/02 120 4/3/01 201 5/8/00 101 4/3/01 71 7/23/01 64
4/12/01 96 6/19/02 106 7/5/00 63 5/31/00 59 2/22/01 52 6/18/02 134 4/5/01 167 5/17/00 41 4/6/01 58 8/6/01 1054/16/01 105 6/21/02 95 7/9/00 38 6/4/00 68 3/6/01 113 6/21/02 59 4/9/01 148 5/18/00 103 4/11/01 51 9/27/01 804/21/01 83 7/3/02 83 10/6/00 58 8/1/00 26 3/14/01 147 7/10/02 56 4/12/01 137 5/30/00 68 5/24/01 66 10/17/01 1454/24/01 91 7/6/02 61 11/15/00 72 8/23/00 43 3/21/01 119 7/18/02 62 4/21/01 108 6/4/00 27 6/1/01 68 11/27/01 1035/25/01 76 7/10/02 43 1/3/01 59 10/6/00 23 3/27/01 69 7/24/02 59 4/23/01 91 6/15/00 37 6/11/01 50 12/19/01 1696/13/01 68 7/16/02 95 2/26/01 61 11/13/00 55 3/29/01 55 7/26/02 85 4/25/01 92 6/20/00 65 6/13/01 31 1/23/02 351
7/3/01 102 7/20/02 71 3/28/01 113 1/3/01 38 4/2/01 47 8/3/02 45 4/27/01 95 6/21/00 13 6/22/01 66 2/14/02 2987/17/01 75 7/24/02 59 4/4/01 71 3/9/01 25 4/4/01 39 8/13/02 79 5/1/01 112 7/6/00 67 7/5/01 61 3/8/02 5157/23/01 74 7/27/02 64 4/11/01 58 3/27/01 52 4/6/01 39 8/16/02 43 5/5/01 73 7/7/00 18 8/6/01 37 3/11/02 1690
8/1/01 86 8/3/02 41 4/12/01 61 4/2/01 65 4/9/01 34 8/20/02 42 5/9/01 64 7/9/00 19 8/18/01 29 3/11/02 20208/14/01 92 8/13/02 100 11/13/01 58 4/6/01 46 4/13/01 30 9/5/02 33 5/17/01 57 7/9/00 36 9/6/01 38 3/12/02 13908/29/01 90 8/13/02 100 12/3/01 91 4/6/01 54 4/16/01 30 10/2/02 82 5/20/01 50 7/13/00 36 9/7/01 17 4/16/02 131
9/4/01 104 8/20/02 39 12/19/01 59 4/9/01 52 4/19/01 37 11/8/02 97 5/23/01 51 7/25/00 13 9/20/01 34 5/8/02 629/7/01 49 8/27/02 76 1/16/02 58 4/9/01 52 4/23/01 30 12/18/02 117 5/29/01 59 7/26/00 43 9/22/01 22 6/13/02 82
9/19/01 92 8/29/02 47 2/6/02 55 4/13/01 43 4/26/01 30 2/27/03 116 6/4/01 55 8/8/00 10 10/2/01 40 7/22/02 1039/22/01 53 10/2/02 92 3/5/02 58 4/17/01 43 5/1/01 35 3/27/03 88 6/5/01 54 8/21/00 49 11/2/01 37 9/11/02 7410/1/01 93 11/8/02 105 3/13/02 235 4/17/01 43 5/6/01 42 4/16/03 96 6/11/01 52 9/5/00 48 12/11/01 45 10/9/02 5711/2/01 116 12/18/02 176 3/29/02 103 4/19/01 40 5/8/01 42 5/4/03 127 6/18/01 56 9/21/00 70 1/22/02 38 11/14/02 161
11/26/01 106 2/27/03 542 3/29/02 84 4/23/01 35 5/18/01 43 5/9/03 114 7/3/01 53 11/6/00 31 2/15/02 41 12/30/02 19111/26/01 199 3/27/03 167 4/4/02 120 4/26/01 33 5/20/01 41 6/12/03 113 7/22/01 48 11/8/00 59 3/11/02 54 1/13/03 22812/3/01 139 5/22/03 108 4/11/02 111 5/1/01 33 5/26/01 34 6/25/03 77 8/13/01 52 11/29/00 102 3/19/02 66 2/11/03 325
1/2/02 152 6/5/03 91 4/17/02 94 5/3/01 32 6/1/01 43 7/18/03 94 8/18/01 49 1/10/01 227 3/27/02 49 4/10/03 1562/1/02 178 6/12/03 137 4/28/02 125 5/8/01 32 6/11/01 47 8/15/03 115 8/29/01 51 3/6/01 339 3/29/02 64 5/8/03 1503/1/02 232 6/17/03 129 5/8/02 92 5/14/01 34 6/13/01 23 8/20/03 81 9/4/01 54 3/14/01 544 4/6/02 58 6/18/03 152
3/12/02 660 6/24/03 53 5/9/02 93 5/25/01 36 6/13/01 23 9/10/03 118 9/7/01 51 3/29/01 171 4/17/02 66 7/23/03 1333/13/02 522 7/16/03 105 5/22/02 73 5/25/01 37 6/15/01 26 9/11/03 21 9/22/01 50 4/2/01 168 4/26/02 65 8/5/03 169
4/9/02 161 7/18/03 117 6/5/02 95 6/13/01 31 6/20/01 29 9/18/03 46 10/2/01 63 4/4/01 148 5/8/02 61 9/23/03 1545/21/02 118 8/15/03 120 6/21/02 22 6/13/01 27 7/10/01 40 10/12/03 78 11/1/01 70 4/7/01 98 5/30/02 65 10/28/03 1735/21/02 118 8/20/03 102 6/22/02 39 6/15/01 33 7/25/01 44 10/30/03 111 11/24/01 61 4/13/01 97 6/4/02 49 11/13/03 1656/11/02 67 9/10/03 122 6/25/02 44 6/18/01 33 8/16/01 48 11/21/03 114 11/26/01 85 4/22/01 70 6/19/02 66 12/15/03 4526/17/02 115 9/11/03 69 7/10/02 43 6/28/01 33 9/6/01 43 12/10/03 127 12/3/01 115 4/24/01 71 6/24/02 63 1/20/04 3596/19/02 82 9/18/03 65 7/11/02 52 7/10/01 33 10/2/01 44 1/13/04 121 1/2/02 192 5/6/01 32 7/3/02 58 2/24/04 13206/21/02 64 10/11/03 125 8/3/02 24 7/25/01 31 10/22/01 42 3/12/04 126 2/1/02 166 5/7/01 84 7/5/02 72 4/14/04 2136/24/02 79 10/28/03 103 8/4/02 44 8/14/01 28 11/16/01 38 3/17/04 108 3/1/02 193 5/23/01 74 7/10/02 41 5/17/04 586/26/02 86 10/30/03 113 8/16/02 25 9/5/01 25 11/21/01 39 4/15/04 134 3/12/02 231 6/11/01 33 8/19/02 60 6/2/04 737/10/02 46 11/21/03 121 8/18/02 37 10/2/01 26 12/19/01 43 4/18/04 155 3/27/02 272 6/13/01 38 9/5/02 68 7/12/04 497/16/02 94 12/10/03 659 8/22/02 28 10/22/01 23 1/15/02 77 4/21/04 135 4/9/02 261 6/13/01 32 10/4/02 31 8/25/04 1477/20/02 88 1/13/04 512 9/6/02 16 11/13/01 22 2/6/02 56 5/20/04 135 4/10/02 218 6/20/01 45 10/24/02 61 9/28/04 1017/24/02 49 2/19/04 1285 9/18/02 60 12/19/01 40 3/6/02 52 5/20/04 99 4/27/02 238 7/11/01 101 11/25/02 40 11/16/04 1357/28/02 56 3/12/04 242 10/4/02 41 1/16/02 30 3/13/02 220 5/27/04 126 5/5/02 190 8/16/01 98 12/30/02 39 1/25/05 663
8/8/02 85 3/17/04 287 10/7/02 46 2/6/02 25 3/29/02 39 5/29/04 112 5/8/02 150 8/29/01 8 1/30/03 38 3/15/05 3378/16/02 56 3/25/04 142 10/10/02 50 3/5/02 43 4/4/02 47 6/5/04 119 5/11/02 135 9/6/01 80 3/5/03 38 5/11/05 1448/20/02 40 4/6/04 218 11/19/02 66 3/29/02 41 4/17/02 50 6/9/04 95 5/21/02 143 9/7/01 24 3/15/03 71 7/15/05 163
9/5/02 85 4/15/04 216 12/5/02 63 4/3/02 51 5/8/02 64 6/11/04 97 5/21/02 143 9/7/01 9 3/27/03 60 9/9/05 569/25/02 72 4/18/04 145 12/18/02 62 4/17/02 65 5/21/02 57 6/29/04 118 5/28/02 82 9/10/01 61 4/10/03 62 10/13/05 8910/2/02 83 4/20/04 163 1/7/03 58 5/9/02 72 6/4/02 40 7/11/04 89 6/4/02 74 9/22/01 14 4/15/03 71 11/7/05 15910/4/02 52 4/25/04 166 2/13/03 58 5/11/02 70 6/21/02 26 7/30/04 117 6/6/02 67 9/24/01 61 5/5/03 62 12/22/05 283
10/10/02 66 5/9/04 115 3/17/03 133 5/22/02 69 6/22/02 27 9/5/04 41 6/10/02 61 10/4/01 65 5/9/03 51 1/12/06 38711/12/02 100 5/12/04 143 4/2/03 88 6/21/02 32 6/24/02 29 10/24/04 112 6/17/02 72 10/10/01 43 5/10/03 46 2/23/06 27812/2/02 122 5/21/04 161 4/18/03 99 6/22/02 49 7/11/02 33 10/28/04 52 6/19/02 68 10/22/01 84 5/19/03 54 3/23/06 5041/10/03 135 5/26/04 127 5/1/03 80 6/25/02 41 7/29/02 32 10/29/04 91 6/21/02 49 11/16/01 92 6/6/03 52 4/6/06 1433/11/03 265 5/29/04 112 5/11/03 51 6/28/02 35 8/4/02 18 11/19/04 110 6/21/02 51 11/24/01 15 6/13/03 64 4/20/06 1553/17/03 187 6/5/04 88 5/12/03 60 7/10/02 29 8/6/02 22 11/23/04 129 6/24/02 45 12/5/01 88 6/25/03 27 5/1/06 87
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3/1/04 255 9/13/04 89 5/23/04 58 12/18/02 40 4/17/03 67 8/26/05 62 3/11/03 110 6/6/02 57 5/9/04 473/5/04 293 9/23/04 100 5/27/04 49 1/7/03 40 4/22/03 43 8/31/05 91 3/18/03 284 6/11/02 31 5/17/04 33
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