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TRANSCRIPT
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Water Resources 1I•~W
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KASKASKIA RIvER AREA ASSESSMENT
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DEPARTMENT OF
NATURAL ~ESOURCES
KASKASKIA RIVER AREA ASSESSMENT
VOLUME 2: WATER RESOURCES
Illinois Department ofNatural Resources Office of Scientific Research and Analysis
Illinois State Water Survey 2204 Griffith Drive
Champaign, Illinois 61820 (217) 244-5459
1999
300 Printed by the authority of the State of Illinois
Other CTAP Publications
Kaskaskia River Area Assessment Vol. I Geology Vol. 3 Living Resources Vol. 4 Socio-Economic Profile, Environmental Quality, Archaeological Resources
The Kaskaskia River Basin: An Inventory ofthe Region's Resources - 22-page color booklet
Descriptive inventories and area assessments are also available for the following regions:
Rock River Spoon River Cache River Driftless Area Mackinaw River Lower Rock River Illinois Headwaters Sinkhole Plain Illinois Big Rivers Sugar-Pecatonica Rivers Fox River Vermilion River Kankakee River Upper Sangamon River Kishwaukee River Du Page River Embarras River Thorn Creek Upper Des Plaines River Prairie Parklands Illinois River Bluffs
Also available:
Illinois Land Cover, An Atlas, plus CD-ROM Inventory ofEcologically Resource-Rich Areas in Illinois EcoWatch '98, Annual Report of the Illinois EcoWatch Network Illinois Geographic Information System, CD-ROM of digital geospatial data
All CTAP and Ecosystems Program documents are available from the DNR Clearinghouse at (217) 782-7498 or TOO (217) 782-9175, Selected publications are also available on the World Wide Web at http://dnr.state.il.us/ctap/ctaphome.htm, or http://dnr.state.il.us/c2000/manage/partner.htm, as well as on the EcoForum Bulletin Board at 1 (800) 528-5486 or (217) 782-8447.
For more information about CTAP, call (217) 524-0500 or e-mail [email protected]; for information on the Ecosystems Program call (217) 782-7940 or e-mail at [email protected].
The Illinois Department of Natural Resources does not discriminate based upon race, color, national origin, age, sex, religion or disability in its programs, services, activities and facilities. If you believe that you have been discriminated against or if you wish additional information, please contact the Department at (217) 785-0067 or the U.S. Department of the Interior Office of Equal Employment, Washington, D.C. 20240.
About This Report
The Kaskaskia River Area Assessment examines almost 5,800 square miles that extend from Campaign County southwest to Randolph County. Because significant natural community and species diversity has been found in the watershed, a portion of the assessment area has been designated a state "Resource Rich Area". I
This report is part ofa series of reports on areas of Illinois where a public-private partnership has been formed to protect natural resources. These assessments provide information on the natural and human resources of the areas as a basis for managing and improving their ecosystems. The determination of resource rich areas and development of ecosystem-based information and management programs in Illinois are the result of three processes - the Critical Trends Assessment Program, the Conservation Congress, and the Water Resources and Land Use Priorities Task Force.
Background
The Critical Trends Assessment Program (CTAP) documents changes in ecological conditions. In 1994, using existing information, the program provided a baseline of ecological conditions2 Three conclusions were drawn from the baseline investigation:
I. the emission and discharge of regulated pollutants over the past 20 years has declined, in some cases dramatically,
2. existing data suggest that the condition of natural ecosystems in Illinois is rapidly declining as a result of fragmentation and continued stress, and
3. data designed to monitor compliance with environmental regulations or the status of individual species are not sufficient to assess ecosystem health statewide.
Based on these findings, CTAP has begun to develop methods to systematically monitor ecological conditions and provide information for ecosystem-based management. Five components make up this effort:
1. identifY resource rich areas, 2. conduct regional assessments, 3. publish an atlas and inventory of Illinois landcover, 4. train volunteers to collect ecological indicator data, and 5. develop an educational science curriculum which incorporates data collection
See Inventory ofResource Rich Areas in Illinois: An Evaluation ofEcological Resources. 2 See The Changing Illinois Environment: Critical Trends, summary report and volumes 1-7.
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At the same time that CTAP was publishing its baseline findings, the Illinois Conservation Congress and the Water Resources and Land Use Priorities Task Force were presenting their respective findings. These groups agreed with the CTAP conclusion that the state's ecosystems were declining. Better stewardship was needed, and they determined that a voluntary, incentive-based, grassroots approach would be the most appropriate, one that recognized the inter-relatedness ofeconomic development and natural resource protection and enhancement.
From the three initiatives was born Conservation 2000, a six-year program to begin reversing ecosystem degradation, primarily through the Ecosystems Program, a cooperative process ofpublic-private partnerships that are intended to merge natural resource stewardship with economic and recreational development. To achieve this goal, the program provides financial incentives and technical assistance to private landowners. The Rock River and Cache River were designated as the first Ecosystem Partnership areas.
At the same time, CTAP identified 30 Resource Rich Areas (RRAs) throughout the state. In RRAs and areas where Ecosystem Partnerships have been formed, CTAP is providing an assessment ofthe area, drawing from ecological and socio-economic databases to give an overview of the region's resources - geologic, edaphic, hydrologic, biotic, and socioeconomic. Although several ofthe analyses are somewhat restricted by spatial and/or temporal limitations of the data, they help to identifY information gaps and additional opportunities and constraints to establishing long-term monitoring programs in the partnership areas.
The Kaskaskia River Area Assessment
The Kaskaskia River begins as a cropland ditch in Champaign County and runs south for approximately 270 miles before it empties into the Mississippi River in Randolph County in southwestern Illinois. The area discussed in this assessment report coincides with the boundaries ofthe entire Kaskaskia River basin as determined by the Illinois Environmental Protection Agency. This area includes parts of seventeen counties in Illinois, covering approximately 5,747 mile2 (3,677,787 acres). Ten subbasins through which the river passes, totaling 324,105 acres, were designated "Resource Rich Areas" because they contain significant natural community diversity.
This assessment is comprised of four volumes. In Volume 1, Geology discusses the geology, soils, and minerals in the assessment area. Volume 2, Water Resources, discusses the surface and groundwater resources and Volume 3, Living Resources, describes the natural vegetation communities and the fauna of the region. Volume 4 contains three parts: Part I, Socio-Economic Profile, discusses the demographics, infrastructure, and economy of the area, focusing on Bond, Clinton, Fayette, Marion, Montgomery, Moultrie, Shelby and Washington counties; Part II, Environmental Quality,
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&c.le 1:2700000 .~=== I!!!"=== ~'OO."
....==== I!!!"==="...'soa-....
Drainage baaln. fram 1:24000 acal. WIIter.had boundarlea •• delineated by the u.s.G.s. W.ter RellOuro•• DJvi.ian.
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Major drainage basins oflllinois and location of the Kaskaskia River Assessment Area
, ~L r;;r GREENE; ~
"'I'Jersey- ~ :."f'ville ffi i
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I Scale I; 1362240
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Subbasins in the Kaskaskia River Assessment Area. Subbasin boundaries depicted are those determined by the Illinois Environmental Protection Agency.
discusses air and water quality, and hazardous and toxic waste generation and management in the area; and Part III, Archaeological Resources, identifies and assesses the archaeological sites known in the area.
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Contributors
Project Coordinator Nani Bhowmik
Report Coordinator Becky Howard
Maps Kathleen Brown
Introduction
Physiography, Rivers and Streams, Lakes H. Vernon Knapp
Wetlands Michael Miller, Liane Suloway, Laura Keefer'
Land Use ; Laura Keefer
Climate and Trends in Climate James Angel
Streamflow and Trends in Streamflow H. Vernon Knapp, Michael Myers
Erosion and Sedimentation Misganaw Demissie, Renjie Xia, William Bogner
Water Use and Availability
Ground-Water Resources Kenneth Hlinka, Sean Sinclair
Surface Water Resources H. Vernon Knapp
Ground-Water Quality Kenneth Hlinka, Sean Sinclair, Thomas Holm
• Contributor Affiliations: Michael Miller, Illinois State Geological Survey; Liane Suloway, Illinois Natural History Survey; Laura Keefer, Illinois State Water Survey.
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Table of Contents
Introduction 1 Physiography 1
Land Elevation and Slope 4 Rivers and Streams 5 Lakes 7 Wetlands 7 Land Use 15
Climate and Trends in Climate 17 Overview : 17 Temperature 17 Precipitation 20
Precipitation Deficits and Excesses 23 Severe Weather 23
Tornadoes 23 Hail 24 Thunderstorms 24
Summary 24
Streamflow and Trends in Streamflow 27 Streamgaging Records : 27 Human Impacts on Streamflows in the Assessment Area 27 Annual Streamflow Variability 30
Statistical Trend Analysis 32 Daily and Seasonal Flow Variability 33
Flooding and High Flows 36 Statistical Trend Analysis 36 Seasonal Distribution of Flood Events .. , 38
Drought and Low Flows 39 Statistical Trend Analysis 41
Summary 41
Erosion and Sedimentation 43 Instream Sediment Load 43 Sedimentation 51
Water Use and Availability 55 Ground-Water Resources 55
Data Sources 56 Data Limitations 56
. Ground-Water Availability 57 1995 Ground-Water Use 58 Ground-Water Use Trends 59
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Surface Water Resources 60 Public Water Supply 60 Industrial and Cooling Water Supply 62 Trends in Surface Water Use 62 Potential for Development of Surface Water Supplies : 62
Ground-Water Quality 65 Data Sources 65 Data Limitations 66 Chemical Components Selected for Trend Analysis 67 Aquifer Unit Analysis 67 Discussion and Results 69
Iron(Fe) 70 Total Dissolved Solids (TOS) 71 Sulfate (S04) 72 Nitrate (N03) 72 Chloride (CI) 73 Hardness (as CaC03) 73
Summary 74
References 75
List of Figures
Introduction
Figure 1. Location of Major Streams in the Kaskaskia River Assessment Area 2 Figure 2. Physiographic Regions in the Kaskaskia River Assessment Area 3 Figure 3. Location of Major Lakes in the Kaskaskia River Assessment Area 8 Figure 4. Wetlands from the National Wetlands Inventory and Quadrangle Map
Boundaries for the Kaskaskia River Assessment Area 11 Figure 5. National Wetlands Inventory Information from the Vandalia 7.5-minute
Quadrangle Map Showing Wetlands, Deepwater Habitat, and NWI Codes. 12 Figure 6. Acreages of Selected Crops in the Kaskaskia River Assessment Area
Based on Dlinois Agricultural Statistics Data 15
Climate and Trends in Climate
Figure 7. Average Annual Temperature for Sparta and Pana, 1901-1998 18 Figure 8. Annual Number of Days with Maximum Temperatures Equal to
or Above 90° F at Sparta and Pana, 1901-1998 19 Figure 9. Annual Number of Days with Minimum Temperatures Equal to
or Below 32° F at Sparta and Pana, Winters 1901-1902 to 1997-1998 20 Figure 10. Annual Precipitation for Sparta and Pana, 1901-1998 21 Figure 1~. Annual Number of Days with Measurable Precipitation at Sparta and Pana,
1901-1998 :.22
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Figure 12. Annual Snowfall at Sparta and Pana, Winters 1901-1902 to 1997-1998 ...... 22 Figure 13. Annual Number of Days with Measurable Snowfall at Sparta and Pana,
Winters 1901-1902 to 1997-1998 23 Figure 14. Annual Number of Days with Thunderstorms at St. Louis, Missouri,
1945-1997 25
Streamflow and Trends in Streamflow
Figure 15. Location of Streamgages in the Kaskaskia River Assessment Area ; 29 Figure 16. Average Annual Strearnflows in the Kaskaskia River Assessment Area 31 Figure 17. Probabilities of Exceedence for Monthly Flows, Shoal Creek near Breese .. 33 Figure 18. Flow Duration Curves (Discharge Versus Probability) for the Kaskaskia
River: a) 1940-1969; b) 1970-1997 34 Figure 19. Flow Duration Curves (Discharge Versus Probability) for Tributary
Streams in the Kaskaskia River Assessment Area 35 Figure 20. Annual Peak Discharges for Gaging Stations in the Kaskaskia River
Assessment Area 37 Figure 21. Seven-Day Low Flows for Gaging Stations in the Kaskaskia River
Assessment Area 40 Figure 22. Location of Sediment Monitoring Stations in the Kaskaskia River
Assessment Area 44 Figure 23. Variabilities of Flow Discharge and Suspended Sediment Concentration
and Load for the Kaskaskia River at Cooks Mills 46 Figure 24. Variabilities of Flow Discharge and Suspended Sediment Concentration
and Load for the Kaskaskia River near Venedy Station 47 Figure 25. Variabilities of Instantaneous Flow Discharge and Suspended Sediment
Concentration and Load for the Kaskaskia River at Vandalia 48 Figure 26. Variabilities of Instantaneous Flow Discharge and Suspended Sediment
Concentration and Load for the Kaskaskia River near Cowden 49 Figure 27 Location of Potential Reservoirs in the Kaskaskia River Assessment Area.. 63
List of Tables
Introduction
Table I. Distribution of Land Slopes in the Physiographic Regions of the Kaskaskia River Assessment Area 4
Table 2. Major Rivers and Streams in the Kaskaskia River Assessment Area 6 Table 3. Examples of Channel Slope in the Kaskaskia River Assessment Area 6 Table 4. Largest Lakes and Water Supply Lakes in the Kaskaskia River
Assessment Area 7 Table 5. Wetlands in the Kaskaskia River Assessment Area 13
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Climate and Trends in Climate
Table 6. Temperature Summary for Sparta and Pana 18 Table 7. Average Annual Temperature during Consecutive 30-Year Periods
for Sparta and Pana 19 Table 8. Precipitation Summary for Sparta and Pana 21
Streamflow and Trends in Streamflow
Table 9. USGS Streamgages in and near the Kaskaskia River Assessment Area with Daily Continuous Discharge Records for Five Years or Longer.. 29
Table 10. Trend Correlations for Annual and Seasonal Flows 32 Table 11. Trend Correlations for Flood Volume and Peakflow 38
'1Table 12. Monthly Distribution of Top Twenty-Five Flood Events at Selected Stations 38
Table 13. Historical Droughts and Low Flows 39 Table 14. Trend Correlations for Low Flows 41
Erosion and Sedimentation
Table 15. Suspended Sediment Monitoring Stations in the Kaskaskia River Assessment Area 43
Table 16. Annual Sediment Load for the Kaskaskia River Basin 50 Table 17. Lake Sedimentation Rates in the Kaskaskia River Assessment Area 52
Water Use and Availability
Table 18. Ground-Water Use Trends in the Kaskaskia River Assessment Area 58 Table 19. Communities Using Surface-Source Public Water Supplies 60 Table 20. Surface Water Use Trends within the Kaskaskia River Basin, 1990-1995 61
Ground-Water Quality
Table 21. Chemical Constituents Selected for Trend Analysis, Unconsolidated Aquifer Systems 68
Table 22. Chemical Constituents Selected for Trend Analysis, Bedrock Aquifer Systems 69
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Introduction
The Kaskaskia River Assessment Area is defined by the watershed of the Kaskaskia River, which is located primarily in the southwestern portion of llIinois. Figure I provides the general location of the Kaskaskia River watershed and its major streams. The total drainage of the watershed is approximately 5,800 square miles, covering all or part of 22 llIinois counties: Bond, Champaign, Christian, Clinton, Coles, Douglas, Effingham, Fayette, Jefferson, Macon, Macoupin, Madison, Marion, Monroe, Montgomery, Moultrie, Perry, Piatt, Randolph, St. Clair, Shelby, and Washington. The Kaskaskia River watershed is the largest watershed contained entirely within llIinois.
The mean annual precipitation for the Kaskaskia River Assessment Area ranges from less than 39 inches in the northwest portion of the watershed to over 4 I inches in its southern portions. The average annual streamflow ranges from 9.5 inches along the western side of the watershed to I 1 inches along the eastern side, with an overall watershed average of about 10.3 inches.
Physiography
The Kaskaskia River Assessment Area is located within three physiographic regions as defined by Leighton et aI. (1948), these being the Bloomington Ridged Plain, the Springfield Plain, and the Mt. Vernon Hill Country (see Figure 2). The topography of all three regions was formed by glacial influence, but the age of glaciation differs by region. The following descriptions ofthese regions are paraphrased from material in Leighton et aI. (1948) and Knapp (1990).
The northeastern portion of the Kaskaskia watershed is located within the Bloomington Ridged Plain. This region is generally characterized by wide stretches of nearly flat to gently sloping till plains, crossed by low, broad end moraines. The till plains and moraines of this region are features that were formed under the influence of the most recent, Wisconsin Episode of glaciation, with the tills being a crushed mixture of bedrock and sediment deposited as the glaciers retreated from the landscape. Stream erosion has since only slightly modified the landscape, and most streams are generally poorly incised and provide relatively poor natural drainage. The Shelbyville Moraine marks the southern extreme of this region, and crosses the watershed in Shelby County.
The Springfield Plain is located in the central portion of the Kaskaskia River watershed and covers over 60% of the watershed. This area is also a relatively flat till plain crossed by low, broad end moraines. These features were formed under the influence of the relatively older lllinoian Episode of glaciation, which provides for more full development
1
+
Scale );)362240
N Basin Boundary
N Streams
Figure 1. Location of Major Streams in the Kaskaskia River Assessment Area
2
SCALE OF MILES o 10 20 30· 40
I Ii'
Figure 2. Physiographic Regions in the Kaskaskia River Assessment Area
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of the drainage systems. But despite the presence of well-defined valleys, the valleys are only slightly entrenched into the topography, the local relief is not great, and some of the upland areas are poorly drained.
The Mt. Vernon Hill Country covers the southern 20% of the assessment area, primarily in Randolph, Monroe, Washington, and Marion Counties. The physiography of the Mt. Vernon Hill Country is the most removed from its glacial influences. The upland areas in the region are hilly, featuring greater local relief, and the valleys and drainage systems are well defined. Sinkholes in Monroe County add an additional hilly character to that portion of the region.
Land Elevation and Slope
Elevations in the Kaskaskia River Assessment Area range from a high of 855 feet above mean sea level (ft-msl), near the headwaters of the river in Champaign County to 368 feet at the Kaskaskia Lock and Dam, at the river's confluence with the Mississippi River. There is a strong north to south downward slope in the land elevations across the watershed. Most of the land in the northern portion of the watershed has elevations in the range of 650 to 700 ft-msl, while elevations in the southern portion of the watershed typically range from 450 to 550 ft-ms!.
Table I provides an average distribution of overland slopes for the three physiographic regions in the Kaskaskia River Assessment Area. The overland slopes listed in this table were estimated from data in Runge et al. (1969). More than three-fourths of the land area in the Bloomington Ridged Plain is level or very gently sloping, having less than a 2% slope; and only 6% of the land in the region has moderate to steep slopes (in excess of 4%). The region typically contains some of the flattest plains in llIinois. The upland area in the Springfield Plain is also relatively flat (58% of the land in the region has less than a 2% slope), although the region also contains many gentle to moderate slopes in rolling topography. In contrast, much ofthe Mt. Vernon Hill Country is sloping to moderately steep. Most of the steeper areas occur along upland slopes.
Table 1. Distribution of Land Slopes in the Physiographic Regions of the Kaskaskia River Assessment Area
(Source: Runge et aI., 1969)
SID
0- 2 % 78.0 2 - 4 16.0 4 - 7 3.3 7 -12 1.3
12 -18 0.5 18 -30 0.8
>30 0.1
4
58.0 34.0 20.0 23.0
8.0 14.0 5.0 12.0 2.2 8.0 6.0 7.0 0.8 2.0
Rivers and Streams
The Kaskaskia River originates in Champaign County and flows southwest to its confluence with the Mississippi River in Randolph County. The total length of the river is 302 miles. The slope of the river is remarkably consistent over much of its length. Downstream of Shelbyville the river has a slope of approximately 1.0 foot per mile. The slope upstream of Shelbyville is only slightly higher, averaging 1.5 feet per mile until within 6 miles of he headwaters, where the channel elevation rises more than 125 feet.
The Kaskaskia navigation pool is located in the lower 36 miles of the Kaskaskia River, being formed by the water impounded by the Kaskaskia navigation lock and darn, which is located immediately upstream of the river's confluence with the Mississippi River.
The Kaskaskia lock and dam and navigation pool were constructed in the 1960s to provide for commercial barge traffic to transport coal mined in the area. Secondary benefits include industrial and agricultural development and recreational activities. The original channel of the Kaskaskia River was straightened to provide the navigation channel, which is maintained to be 225 feet wide and 9 feet deep.
There are about 8,680 miles of rivers and streams in the Kaskaskia River Assessment Area, as measured from 1:100,000 scale mapping. The major streams in the area (those with watersheds greater than 10 square miles) account for about 32% of this total, or approximately 2,748 river miles. The largest streams within the assessment area are listed in Table 2, and selected streams are located in Figure 1. The nine largest tributaries leading into the Kaskaskia River, listed from largest to smallest, are Shoal Creek, Silver Creek, Crooked Creek, West Okaw River, Richland Creek, Becks Creek, Hurricane Creek, Sugar Creek, and Lake Fork.
Table 3 provides examples of channel slopes for streams in the Kaskaskia River Assessment Area. Streams in the Springfield Plain and the Mt. Vernon Hill Country have similar channel slopes and profiles, which are typical of many areas in lllinois. The streams and ditches in the Bloomington Ridged Plain normally have gentle channel slopes as a result of the region's level topography.
Much of the upland area in the Bloomington Ridged Plain has relatively poor natural drainage and, for this reason, many of the headwater streams in that region have been channelized. It is estimated from data given in Mattingly and Herricks (1991) that roughly 30 to 40% of the stream reaches in this region have been channelized, and there has also been considerable channelization for drainage along Richland and Silver Creeks in Madison and St. Clair Counties. However, most other streams in the Kaskaskia River Assessment Area have relatively well-defined drainage, such that only 15% of the stream reaches in the area have been channelized (Mattingly and Herricks, 1991).
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Table 2. Major Rivers and Streams in the Kaskaskia River Assessment Area
Stream Name
Kaskaskia River Lake Fork West Okaw River Robinson Creek Richland Creek Beck Creek Big Creek Ramsey Creek Hickory Creek Hurricane Creek East Fork Kaskaskia River Crooked Creek Little Crooked Creek Shoal Creek Middle Fork Shoal Creek East Fork Shoal Creek Beaver Creek Sugar Creek Elkhorn Creek Mud Creek Silver Creek East Fork Silver Creek Richland Creek Plum Creek Horse Creek
General Location b
Douglas, Piatt Shelby, Moultrie, Piatt Shelby Shelby Fayette, Shelby, Christian Fayette, Effingham, Shelby
5,800 170 292 124 86
203 139
Fayette, Shelby, Montgomery 106 Fayette, Effingham 142 Fayette, Bond, Montgomery 193 Marion, Fayette, Clinton 128 Washington, Marion 465 Washington, Clinton, Fayette 115 Clinton, Bond, Montgomery 916 Montgomery 117 Bond, Montgomery 185 Clinton, Bond 146 Clinton, Madison, Bond 176 Washington 87 St. Clair, Randolph, Washington 136 St. Clair, Macoupin, Madison 478 Madison, Bond 98 St. Clair 248 Randolph 89 Randolph, Monroe 92
Table 3. Examples of Channel Slope in the Kaskaskia River Assessment Area
Physiographic Region Stream name Bloomington Ridged Plain
Kaskaskia River Lake Fork West Okaw River
Springfield Plain Richland Creek Silver Creek East Fork Shoal Creek Crooked Creek Hurricane Creek
Mt. Vernon Hill Country Horse Creek Mud Creek
(in ftImi)
Draina e area of stream 10 s . mi. 50 s . mi. 100 s mi.
3.3 1.5 1.2 4.0 0.7 1.3 3.8 3.1 2.0
6.7 4.0 2.0 10.0 2.5 1.5 5.6 4.6 3.2 5.2 2.3 1.6 9.0 4.7 2.8
11.3 3.3 6.3 3.0
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Lakes
The Kaskaskia River Assessment Area has 843 lakes, as identified by I: 100,000 scale topographic mapping. The location of these lakes are shown in Figure 3. In addition to these are hundreds of other small lakes and ponds, having surface areas generally less than 2 acres. Table 4 lists the largest lakes in the assessment area, being those with surface areas greater than 100 acres, along with some smaller lakes used for public water supply.
Table 4. Largest Lakes and Water Supply Lakes in the Kaskaskia River Assessment Area
Name Carlyle Lake Lake Shelbyville Baldwin Lake Lake Glen Shoals Lake Lou Yaeger Coffeen Lake Raccoon Lake Governor Bond Lake Vandalia Lake Highland Silver Lake Lake Centralia Lake Pana Lake Hillsboro Lake Nellie Salem Reservoir Nashville Reservoir Coulterville Reservoir Kinmundy Reservoir
Wetlands
Surface Coun area acres)
Clinton, Bond Shelby Randolph Montgomery Montgomery Montgomery Marion Bond Fayette Madison Marion Shelby Montgomery Fayette Marion Washington Randolph Marion
26,000 11,000
1,967 1,804 1,304 1,070
925 750 646 574 254 220 109 68 74 37 24 20
Prim uses Flood control, recreation, water supply Flood control, recreation Cooling Recreation Recreation, water supply Cooling Water supply Water supply Recreation Water supply, recreation Recreation Water supply Water supply Water supply Water supply Water supply Water supply Water supply
Wetlands are an important part of our landscape because they provide critical habitat for many plants and animals and serve an important role in mitigating the effects of storm flow in streams. They are also government-regulated landscape features under Section 404 of the Clean Water Act. In general, wetlands are a transition zone between dry uplands and open water; however, open-water areas in many upland depressional wetlands are dry at the surface for significant portions of the year.
The Kaskaskia River Assessment Area has only about 4.5% (165,699 acres) of its total area in wetlands (Table 5). Generalizations about wetlands in an area as large as the Kaskaskia River Assessment Area is difficult and possibly misleading. However, some generalizations about the distribution of wetlands in number as well as type are possible
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Scale I: 1362240
o~~""'"==~~==..".,~~"' ....
N Basin Boundary • Lakes
Figure 3. Location of Major Lakes in the Kaskaskia River Assessment Area
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Table S. Wetlands in the Kaskaskia River Assessment Area
Subbasin name
Subbasin
Acres 9,678
Percent of area
0.3AsaCreek Ash Creek 18,884 0.5 Beaver Creek 76,086 2.1 Beck Creek 53,961 1.5 Big Creek 31,199 0.8 Brush Creek 17,540 0.5 Bull Branch 2,321 0.1 Camp Creek 36,947 1.0 Cattle Creek 1,728 0.0 Chicken Creek 764 0.0 Coal Creek 7,225 0.2 Cress Creek 6,001 0.2 Crooked Creek (lower) 104,439 2.8 Crooked Creek (upper) 19,369 0.5 E. Fie Kaskaskia River 69,123 1.9 E. Fie Shoal Creek 116,988 3.2 E. Fk. Silver Creek 42,481 1.2 Elkhorn Creek 56,148 1.5 Flat Br. 26,229 0.7 Flat Branch 15,036 0.4 Flat Creek 31,041 0.8 Grand Point Creek 19,635 0.5 Hammond Mutual Ditch 18,713 0.5 Hazel Creek 21,259 0.6 Hickory Creek 45,752 1.2 Horse Creek 59,549 1.6 Hurricane Creek 127,360 3.5 Jonathon Creek 36,530 1.0 Jordan Creek 16,149 0.4 Kaskaskia River 1 78,309 2.1 Kaskaskia River 2 89,233 2.4 Kaskaskia River 3 45,482 1.2 Kaskaskia River 4 56,161 1.5 Kaskaskia River 5 25,625 0.7 Kaskaskia River 6 63,200 1.7 Kaskaskia River 7 51,026 1.4 Kaskaskia River 8 33,900 0.9 Kaskaskia River 9 72,747 2.0 Lake Branch 11,822 0.3 Lake Carlyle 85,030 2.3 Lake Fork (Kaskaskia River) 108,281 2.9 Lake Fork (Shoal Creek) 28,620 0.8 Lake Lou Yager 49,223 1.3 Lake Shelbyville 111,713 3.0
Acres 49.63
432.79 4,490.00 1,314.58 1,057.40
168.38 24.76
1,015.84 31.06 77.73
125.64 51.05
9,208.36 575.05
3,968.99 3,357.82 1,379.54 4,054.84
79.94 666.15
2,863.76 1,143.51
53.79 1,271.51 1,128.76 1,596.84 4,640.51
412.96 190.60 582.49
1,857.20 1,332.53 3,868.65 3,267.71 9,409.73
10,559.21 6,107.35 6,611.92
298.83 9,596.56
510.42 724.64 746.51
2,540.44
Wetlands Percent of Percent of subbasin total wetlands
0.5 0.0 2.3 0.3 5.9 2.7 2.4 0.8 3.4 0.6 1.0 0.1 1.1 0.0 2.7 0.6 1.8 0.0
10.2 0.0 1.7 0.1 0.9 0.0 8.8 5.6 3.0 0.3 5.7 2.4 2.9 2.0 3.2 0.8 7.2 2.4 0.3 0.0 4.4 0.4 9.2 1.7 5.8 0.7 0.3 0.0 6.0 0.8 2.5 0.7 2.7 1.0 3.6 2.8 1.1 0.2 1.2 0.1 0.7 0.4 2.1 1.1 2.9 0.8 6.9 2.3
12.8 2.0 14.9 5.7 20.7 6.4 18.0 3.7 9.1 4.0 2.5 0.2
11.3 5.8 0.5 0.3 2.5 0.4 1.5 0.5 2.3 1.5
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Subbasin name
Subbasin
Acres 48,173
Percent of area
1.3Little Crooked Creek Little Hickory Creek 8,524 0.2 Little Silver Creek 31,187 0.8 Locust Fork 11,196 0.3 Lone Grove Br. 11,936 0.3 Lost Creek 49,691 1.4 Marrowbone Creek 36,395 1.0 Mid. Fk. Shoal Creek 68,071 1.9 Middle Creek 12,865 0.3 Mitchell Creek 46,656 1.3 Mud Creek 78,291 2.1 N. Fk. Kaskaskia River 49,455 1.3 Nashville Creek 11,411 0.3 Ninemile Creek 27,858 0.8 Opossum Creek 21,407 0.6 Plum Creek 56,800 1.5 Prairie du Long Creek 50,512 1.4 Ramsey Creek 66,571 1.8 Richland Creek-North 36,398 1.0 Richland Cr.-South (lower) 28,667 0.8 Richland Cr.-South (upper) 60,999 1.7 Robinson Creek 78,227 2.1 S. Fk. Big Creek 22,883 0.6 S. Fk. Mud Creek 8,005 0.2 Sewer Creek (Crooked Creek) 21,813 0.6 Sewer Creek (Sugar Creek) 6,411 0.2 Shoal Creek (lower) 56,209 1.5 Shoal Creek (upper) 98,181 2.7 Silver Creek (lower) 88,974 2.4 Silver Creek (upper) 100,434 2.7 Suck Creek 8,838 0.2 Sugar Creek 90,977 2.5 Sugar Fk. 19,638 0.5 Town Creek 7,241 0.2 Two mile Slough 24,069 0.7 W. Fk. Richland Creek 16,969 0.5 W. Fk. Shoal Creek (lower) 32,555 0.9 W. Fk. Shoal Creek (upper) 19,592 0.5 W. Okaw Ditch #3 24,692 0.7 W. Okaw Ditch #4 24,283 0.7 W. Okaw River 48,316 1.3 Whitley Creek 33,324 0.9 WolfCreek 34,542
3,677,743 0.9
100.0Total
Table 5. Concluded
Acres 1,584.73
126.03 552.96 203.16 109.11
1,734.69 269.04
1,540.80 680.84 602.03
5,954.30 1,873.47
353.72 780.74 379.89
2,712.85 1,113.32 1,653.12
524.35 1,385.36 1,641.52
961.79 495.05 651.41 547.41
90.48 8,702.74 3,010.27 9,113.03 4,642.54
168.81 4,303.91
539.34 122.40 120.81 397.59 632.14
77.10 22.04
110.83 1,024.29
367.63 369.57
165,699.25
10
Wetlands Percent of subbasin
3.3 1.5 1.8 1.8 0.9 3.5 0.7 2.3 5.3 1.3 7.6 3.8 3.1 2.8 1.8 4.8 2.2 2.5 1.4 4.8 2.7 1.2 2.2 8.1 2.5 1.4
15.5 3.1
10.2 4.6 1.9 4.7 2.7 1.7 0.5 2.3 1.9 0.4 0.1 0.5 2.1 1.1 1.1
-
Percent of total wetlands
1.0 0.1 0.3 0.1 0.1 1.0 0.2 0.9 0.4 0.4 3.6 1.1 0.2 0.5 0.2 1.6 0.7 1.0 0.3 0.8 1.0 0.6 0.3 0.4 0.3 0.1 5.3 1.8 5.5 2.8 0.1 2.6 0.3 0.1 0.1 0.2 0.4 0.0 0.0 0.1 0.6 0.2 0.2
100.0
because the KRAA can be roughly subdivided into three general areas on the basis of geologic processes and materials. Barnhardt shows this in Volume 1, Modern Soils and the Landscape - Influences on Habitat and Agriculture, by combining information from Quaternary Geology (Volume 1, Figure 5) and Topography (Volume 1, Figure 7) maps. The area north of Lake Shelbyville is geologically younger, generally less dissected, with more productive soils which results in wide level areas between streams which have been significantly drained for agriculture. Inspection of Figure 4 shows an area of relatively few surviving wetlands. As one proceeds south from Lake Shelbyville the dissection of the landscape by streams is progressively more intense and as one gets south of Lake Carlyle the width of the floodplains generally increase towards the south or towards the lower reaches of subbasins. The combination of landscape and the difficulty of draining these low flat areas have resulted in large areas of Bottomland Forest located along the streams of in the lower half of the Kaskakia River Assessment Area. Table 5 shows that 120,928 acres (73%) of the total 165,699 wetland acres are classed as Bottom Land -Forested Wetlands and inspection of Figure 4 shows a concentration of wetlands along the river valleys. The remaining 27% of the wetlands acreage is divided among the other types of Palustrine Wetlands and Lacustrine and Riverine categories of wetlands. (For wetland categories, see the table describing wetland and deepwater habitat in Volume 3: Living Resources.) Inspection of Table 5, generally shows the subbasins in the southern half of the Kaskaskia River Assessment Area have larger percentages of wetlands then those in the north (see lower Silver Creek - 5.5%, lower Shoal Creek - 5.3%, and Kaskaskia River 6, 7, arid 9 - 5.7, 6.4, and 4.0% respectively, compared to Kaskaskia 10.4%, Lake Fork - 0.3%, and Jonathon Creek - 0.2%.
The hydrogeology of wetlands allows water to accumulate in them longer than in the surrounding landscape, with far-reaching consequences for the natural environment. Wetland sites become the locus of organisms that require or can tolerate moisture for extended periods of time, and the wetland itself becomes the breeding habitat and nursery for many organisms that require water for early development. Plants that can tolerate moist conditions (hydrophytes) can exist in these areas, whereas upland plants cannot successfully compete for existence. Given the above conditions, the remaining wetlands in our landscape are refuges for many plants and animals that were once widespread but are now restricted to existing wetland areas.
The configuration of wetlands enables them to retain excess rainwater, extending the time the water spends on the upland area. The effect of this retention on the basin is to delay the delivery of water to the main stream. This decreases the peak discharges of storm flow or floods, thus reducing flood damages and the resulting costs. It is important to realize that the destruction of wetland areas has the opposite effect, increasing peak flood flows and thereby increasing flood damages and costs.
The location of wetlands affects many day-to-day decisions because wetlands are considered "Waters of the United States" (Clean Water Act) and are protected by various legislation at the local, state, and federal levels (for example, the Rivers and Harbors Act of 1899, Section 10; the Clean Water Act; and the llIinois Interagency Wetlands Act of
11
I Scale I: 1362240
N
j
Figure 4. Wetlands from the National Wetlands Inventory and quadrangle map boundaries for the Kaskaskia River Assessment Area. The inset area is depicted in the following figure.
12
1989). Activities by government, private enterprise, and individual citizens are subject to regulations administered by the U.S. Army Corps of Engineers. Under a Memorandum of Agreement between federal regulatory agencies with jurisdiction over wetlands, the Natural Resources Conservation Service takes the lead in regulating wetland issues for agricultural land, and the U.S. Army Corps of Engineers takes the lead for all nonagricultural lands.
In contexts where wetland resources are an issue, the location and acreage of a wetland will be information required by any regulatory agency, whether local, state, or federal. Currently, there are two general sources of wetland location information for lllinois: the National Wetland Inventory (NWn, completed in 1980, and Illinois Land Cover, an Atlas (ILCA) by the lllinois Department of Natural Resources (1996). The State of lllinois used the NWI information to publish the Wetland Resources ojIllinois: An Analysis and Atlas (Suloway and Hubbell, 1994). While this atlas is not of suitable scale for landowners or government agencies to use for individual wetland locations, it can be used by agencies or groups that consider wetlands in an administrative or general government manner and focus on acreage and not individual wetland boundaries.
The NWI program involved identifying wetlands on aerial photographs of I :58,000 scale and publishing maps of this information using USGS I :24,OOO-scale topographic quadrangle maps as the base. NWI quadrangle maps for the Spoon River basin are shown in Figure 5. Individual quadrangles can be purchased from:
Center for Governmental Studies Wetland Map Sales Northern lllinois University De Kalb, ll., 60115 Telephone: (815) 753-1901
Digital data by quadrangle are available from the NWI Web site: www.nwi.fws.gov.
The ILeA inventory used Landsat Thematic Mapper satellite data as the primary source for interpretation. National Aerial Photography Program photographs verified the land cover classification and helped ensure consistency from area to area in lllinois. The ll.,CA and companion compact disc can be purchased from:
lllinois Department of Natural Resources 524 South Second Street Lincoln Tower Plaza Springfield, ll., 62701-1787 Telephone: (217) 524-0500 E-mail: [email protected] Web site: http://dnr.state.il.us/ctap/ctaphome.htm
13
F
, , , ,
, , ,,, , , , , , I, ,,, , ,
,,, , ,
,,,, ,, ,, , ,
~~A:/
B
~FRSS1A fEMA
,,,
, , ,,, , ,, , ,, ,
2UBHX
EM1CX
.BGX
• ~ Wetlands
• ... ......... " Deepwater habitat I N
Scale 1:24000 j• 111I..., • ._- .............
Kaskaskia River AA Figure 5. National Wetlands Inventory infonnation from the Vandalia 7.5-minute quadrangle map showing wetlands, deepwater habitat, and NWI codes.
14
Although the ll..CA and NWI programs were not meant for regulatory purposes, they are the only state or regional wetland map resources available and are the logical sources for beginning a wetland assessment. The presence or absence of wetlands as represented by the wetland maps is not certified by either the ll..CA or the NWI mapping program. Figure 5, taken from the Vandalia Quadrangle in the Kaskaskia River Assessment Area, exemplifies the information that can be expected from NWI maps.
In some areas with intense economic development and significant wetland acreage, the NWI maps have been redone or updated for use in designating or locating wetland areas. Whatever the source of wetland map information, the user should be aware that this information is a general indication of wetland locations, and the boundaries and exact locations should be field-verified by persons trained or certified in wetland delineation.
Given the limitations of most existing wetland maps, more complete information can be obtained by comparing mapped wetlands with other regional attributes such as shallow aquifers, subsurface geology, and placement in the landscape. When these comparisons show consistent regional patterns (for example, placement in the landscape or correlation with a particular geologic material), any parcels of land with similar landscape positions or geologic materials can be considered potential wetland sites even if maps do not show them as wet.
Land Use
Agriculture is a major land use in the 22 counties (Bond, Champaign, Christian, Clinton, Coles, Douglas, Effingham, Fayette, Jefferson, Macon, Macoupin, Madison, Marion, Monroe, Montgomery, Moutrie, Perry, Piatt, Randolph, Shelby, St. Clair, and Washington) within the Kaskaskia River Assessment Area. Agricultural crops covered 67% of the area in 1995, higher than the 56% in 1925. During this increase in crop acreage, lllinois Agricultural Statistics (lAS) data indicate that the acreage of major crops significantly changed from 1925-1995, as shown in Figure 6.
The dominant crops in 1925 were small grains (1,191,747 acres) and com (798,066 acres), whereas in 1995 the dominant crops were soybeans (1,944,778 acres) and com (820,987 acres). Com acreage has been steady from 1925 and 1995 (averaging 770,685 acres) with some variation during this period. The maximum acreage of com harvested during the period of record (1925-1995) occurred in 1994 with 987,898 acres, whereas the lowest harvested acres for com was in 1945 with 522,880 acres. Soybean acreage increased from 42,788 acres in 1925 to 1,189,551 acres in 1995. The increase in soybean acreage mirrors a decrease in small grain acreage during the same period. Small grains decreased from 1,191,747 acres in 1925 to 497,136 acres in 1995.
15
2,500,000
2,000.000
1,500,000 w '" '" ~
1.000,000
500,000
o
-.- CORN
--SOYBEANS •••••• -•• CORN·BEANS
- - • - •• SMALL GRAINS
.-_.' " ; "
.... , . -' . ..'" \ ... '. :' '. ,.
, . .... ''''./'. ~~fCJ "
"
:0J ,_ .....~ /'
~ ,~
-- . -
: .. ' . "
\// '\.: .' ..J
f """- ......../
<7"/. ~
N\ ,J \ \ /
" '/
1920 1930 1940 1950 1960 1970 1980 1990 2000
Figure 6. Acreages ofSelected Crops in the Kaskaskia River Assessment Area Based on Illinois Agricultural Statistics Data
An inverse relationship between soybeans and small grains in the Kaskaskia River Assessment Area from 1925-1995 can be seen in Figure 6, Soybean acreage increased steadily from 1925 to 1978 (1,189,551 acres) and remained steady through 1995. Small grain acreage decreased from 1925 to 1970 (380,665 acres) and was steady from 1970 through 1995, In 1995, soybeans and com were planted on almost equal areas, accounting for 79% of the crop acreage in the assessment area, whereas small grains and com dominated the crop acreage (97%) in 1925. Except for brief periods in the 1960s, com was never the dominant crop harvested in the Kaskaskia River Assessment Area.
16
Climate and Trends in Climate
This chapter reviews trends in climate in the Kaskaskia River Assessment Area since the tum of the century. Climate parameters examined are: annual average temperature, the number of days with highs above or equal to 90°F, the number of days with lows below or equal to 32°F, the number of days with lows below or equal to OaF, annual precipitation, the number of days with measurable precipitation, annual snowfall, and the number of days with measurable snowfall. Extreme weather events examined in this report are tornadoes, hail, and thunderstorms.
Overview
The Kaskaskia River Assessment Area in southeastern lllinois occupies portions of Monroe, Randolph, Perry, St. Clair, Washington, Clinton, Madison, Bond, Marion, Fayette, Montgomery, Effingham, Christian, Shelby, Macon, Moultrie, Coles, Douglas, Champaign, and Piatt Counties. The climate of this area is typically continental, as shown by its changeable weather and the wide range of temperature extremes. Summer maximum temperatures are generally in the 80s and 90s, with lows in the 60s, while daily high temperatures in winter are generally in the 30s or 40s, with lows in the 20s. Based on the latest 30-year average (1961-1990), the average first occurrence of 32°F in the fall is around October 20, and the average last occurrence of 32°F in the spring is around April 15.
Precipitation is normally heaviest during the growing season and lightest in midwinter. Thunderstorms and associated heavy showers are the major source of growing season precipitation, and they can produce gusty winds, hail, and tornadoes. The months with the most snowfall are December, January, February, and March. However, snowfalls have occurred as early as October and as late as May. Heavy snowfalls have rarely exceeded 10 inches.
The climate data used in the following discussions originate from two long-term sites: Sparta, lllinois, located in the southern half of the basin and Pana, lllinois, located in the northern half of the basin. For Sparta, a station move in 1993 caused the mean temperature to drop by at least 4°F. Therefore, data from DuQuoin lllinois, a nearby site, was used after 1992. Supportive data and analyses for nearby lllinois sites can be found in reports by the llIinois Department of Energy and Natural Resources (1994) and Changnon (1984).
Temperature
Average temperatures and the number of days exceeding critical thresholds are found in Table 6. The average annual temperature is 56.4OF for Sparta and 53.1OF for Pana. For Sparta, the warmest year since 1901 was 1931 (60.2°F), while the coldest year was 1904
17
(53.5°p). For Pana, the warmest year since 1901 was 1995 (57.7°F), while the coldest year was 1917 (47.3°P). The record high for Sparta was 114°P on July 24, 1934, and the record low was _20oP on December 19, 1907. For Pana, the record high was 115°F on July 14, 1954, and the record low was -25°F on January 7, 1912.
Table 6. Temperature Summary for Sparta and Pana (Averages are from 1961-1990 and extremes are from 1901-1998 Temperatures are inOF)
Month Average
hi h Average
low
Sparta # of days with high
>90°F
# of days with low
<32°F Average
hi h Average
low
Pana # of days with high
>90°F
# of days with low
<32°F January 39.7 21.9 o 24 34.4 17.8 o 28 February 45.1 25.9 o 20 39.4 22.0 o 23 March 56.7 35.9 o 13 52.1 32.6 o 16 April 68.6 45.8 0.1 2.6 65.2 43.1 o 4 May 77.9 54.6 1.8 0.1 74.5 52.8 0.4 0.2 June 86.3 63.4 9.8 o 83.1 61.6 4.7 o July 90.2 67.5 18 o 86.3 65.6 8.7 o August 88.2 65.1 15 o 83.8 63.3 5.3 o September 81.4 58.2 6.8 0.1 78.0 56.4 1.6 0.1 October 70.5 46.8 0.6 2.1 66.4 45.1 o 2.9 November 56.5 37.4 o 12 52.5 34.9 o 13 December 43.5 26.9 o 21 39.0 23.5 o 24
Although there is a great deal of year-to-year variability, mean annual temperatures at Sparta show warming from 190I to 1940, followed by a cooling trend through 1998 (Figure 7). Pana records show a similar pattern except for a warming period from 1986 to 1995.
61
60 I I
~ 59
I A ~.
1;V-g-sa rr
1\
'.'I
1\ ~A 1\,11{!!.57
I~ § 56 c It I. ~55
I~V,Vc54 \Rf\~i:153 52 51
1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000
" 1\ 1\
\7 II II rIA, \Jil\_ y V\ I IV I., 11 v
1\ r~ 111> " If ,~ T¥
Figure 7. Average Annual Temperaturefor Sparta (solid line) and Pana (line with markers), 1901-1998
18
-------------------------------------- -
The NWS has adopted 30-year averages, ending at the beginning of the latest new decade, to represent climate "normals." These averages were adopted to filter out some of the smaller scale features and yet retain the character of the longer-term trends. Consecutive, overlapping "normals" for the last seven 30-year periods at Sparta and Pana are presented in Table 7. The consecutive averages demonstrate the slight warming through the 19311960 period, followed by cooling through the 1961-1990 period for both sites.
Table 7. Average Annual Temperature during Consecutive 30-Year Periods
Avera in eriod 1901-1930 1911-1940 1921-1950 1931-1960 1941-1970 1951-1980 1961-1990
for Sparta and Pana
Sparta Pana Average temperature Average temperature
(oF) (oF)
56.5 57.3 57.7 57.7 57.1 56.7 56.5
53.6 54.3 54.5 54.6 53.9 53.3 53.2
Another way to detect climate change is to examine the frequency of extreme events. The annual number of days with temperatures equal to or above 90°F is shown in Figure 8 for both Sparta and Pana. The time series resembles that of annual temperature (Figure 7), even though the number of days with temperatures above 90°F represents only the high summer temperature extremes. Figure 8 data show an increase in the number of days through the mid-1930s, followed by a decline through the mid-1970s before returning to slightly higher numbers through 1998 for both stations.
100
~ : /I 1\ 70
j::t:
60
&.
'i 50
40! 30 '0 20
'"' 10 o
f\I • I' vI. /+\\
It /1
I~ I\ LA ... \J
R\ nAY •\H IlI'.t' ••
1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000
Figure 8. Annual Number ofDays with Maximum Temperatures Equal to or Above 90°F at Sparta (solid line) and Pana (line with markers), 1901-1998
19
140
I&. 130 III II 120 v
~ 110 .... ..c 100:to ~
S90
c 80
l\ " ~
I. It "Il'
, " ~ I IWM ~MI I. ,ijf '¥ If If
•
'v\. yv V\ M ~, " V\ W\J
Figure 9 shows the winter frequency of daily minimum temperatures equal to or below 32°F. The frequency of such temperatures shows no long-term trends for either sites. Due to the low numbers, the number of days when the daily minimum temperature is equal to or below Oop is not shown.
'0 70* 60
1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000
Figure 9. Annual Number ofDays with Minimum Temperatures Equal to or Below 32°F at Sparta (solid line) and Pana (line with markers),
Winters 1901-1902 to 1997-1998
Precipitation
Average annual precipitation is 41.67 inches for Sparta and 40.20 inches for Pana, with more rainfall in the spring, summer, and fall than in winter (Table 8). Late spring, summer, and early fall precipitation is primarily convective in nature, often associated with thunderstorms, with a duration of I to 2 hours. During the remainder of the year, the precipitation is of longer duration and associated with synoptic-scale weather systems (cold fronts, occluded fronts, and low-pressure systems).
The wettest year of record since 1901 at Sparta was 1993 (63.84 inches). The driest year was 1953 (23.32 inches). For Pana, the wettest year on record since 1901 was 1927 (57.28 inches) while the driest year was 1914 (23.11 inches).
The annual precipitation for Sparta and Pana are shown in Figure 10. A slight downward trend is evident through 1940 before increasing through 1998 for both sites.
20
-----_.---_.----
Table 8. Precipitation Summary for Sparta and Pana (Averages are from 1961-1990 and extremes are from 1901-1998. Precipitation is in inches.)
Month January February March April May June July August September October November December
Average nrecio. 1.90 2.59 4.29 3.83 4.44 3.36 4.16 3.42 3.33 3.07 3.72 3.56
60
55
~ 50-c45 .S! 'lii40
'f"" 35 0. 30
25
20
Snarta # of days
Snowfall with orecio. 5.5 8 5.0 8 2.4 10 0.5 11 0 10 0 9 0 8 0 8 0 8 0 7
0.9 8 3.2 8
Pana # of days
Snowfall with orecio. 7.3 9 6.1 8 4.3 10 0.6 11 0 11 0 10 0 9 0 8 0 8
0.1 8 1.7 9 5.8 9
I. -jjI.
]V
WIt r;JJJ
,U I' ' \1 ~
1 .-
Average orecio. 1.99 2.15 3.68 3.71 4.05 3.94 4.28 3.38 3.26 2.86 3.36 3.54
1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000
Figure 10. Annual Precipitation for Sparta (solid line) and Pana (line with markers), 1901-1998
The number of days per year with measurable precipitation (i.e., more than a trace) is shown in Figure 11. Except for abnormally low values in 1990 and 1991 for Sparta, there is no trend evident in the data. Precipitation at both sites is more frequent during summer months than during winter months.
21
t
• N t ~
IM;JA~"J ~ I. I~ IMII ' ./).
'-~J '+f 'l IV If p,rv.. ~ VV\
v Tr
150
c: 140 .2 1'l;j 30 :a. 120 .~ 110 Q.
.c: 100
i 90
~ 80 o '0 70 ... 60
50
1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000
Figure 11. Annual Number ofDays with Measurable Precipitation at Sparta (solid line) and Pana (line with markers), 1901·1998
Average winter snowfall is 17.1 inches at Sparta and 25.9 inches at Pana with great yearto-year variability. The most snowfall during anyone winter in Sparta was 60.7 inches during the 1911-1912 winter, whereas the least amount was only 0.2 inches during the 1931-1932 winter. For Pana, the most snowfall in one winter was 61.2 inches during the 1977-1978 winter, whereas the least amount was only 3.3 inches during the 1994-1995 winter. Snowfall from the 1901-1902 winter season through the 1997-1998 season is shown in Figure 12. Snowfall amounts decreased through the early 1940s before increasing the early 1980s. Snowfall at both stations decreased slightly in the last 15 years of the record.
1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000
Figure 12. Annual Snowfall at Sparta (solid line) and Pana (line with markers), Winters 1901-1902 to 1997-1998
"1m, t ,M~I'll
y
o
60
10
-Ul13O 20
50
22
.IAi IH ~. ~ ~ '.i~ l'
~LI III IFfY I~ V
1920 1930 1940 1950 1960 1970 1980 1990 2000
Figure 13 shows the number of days each winter with snowfall, from 1901-1902 through 1997-1998. The number of days with snow decreases through the early 1940s, then increasing through the ear1y-1980s, before decreasing in the last 15 years of the record. This pattern is very similar to the snowfall pattern discussed previously. A daily snowfall of more than 6 inches occurs about once every three years in Sparta and about once every other year in Pana. Snow cover is frequently experienced at both Sparta and Pana, typically lasting from a few days at a time to up to two months. The heaviest one-day snowfall between the two stations was 12.0" on February 15th
, 1908, at Sparta, lllinois.
40
135
30
III 25 s:.';20 IIIi;' 15 c '0.. 10
5
o 1900 1910
Figure 13. Annual Number ofDays with Measurable Snowfall at Sparta (solid line) and Pana (line with markers), Winters 1901-1902 to 1997-1998
Precipitation Deficits and Excesses
Following are the driest years in the Kaskaskia River Assessment Area in terms of annual precipitation shortfall, starting with the driest: 1912 (24.10"),1910 (24.29"), and 1963 (24.47") for Sparta. For Pana, they are 1914 (23.82"), 1976 (24.53"), and 1930 (25.06"). Driest summer seasons (June, July, and August) in the basin include: 1991 (3.43"), 1984 (4.79"), and 1919 (4.93") for Sparta. For Pana, they are 1936 (5.08"), 1930 (5.81"), and 1914 (5.96"). The three wettest years for Sparta are 1902 (56.11"), 1927 (47.39"), and 1993 (47.07"). The three wettest years for Pana are 1927 (57.03"), 1993 (56.49"), and 1957 (54.33"). .
Severe Weather
Tornadoes
Although tornadoes are not uncommon in lllinois, most people do not expect to be affected directly, even if they live in the state for a lifetime. This is because tornadoes are
23
I
I
I
I
I
I
I
generally only one-quarter mile in diameter, travel at roughly 30 miles per hour for only 15-20 minutes, and then dissipate, directly affecting a total area less than 2 square miles. Since llIinois observes an average of 28 tornadoes a year (though the actual number varies from fewer than ten to about 100 during the last 35 years), the total area directly affected by tornadoes annually is only about 55 square miles, 0.1 % the total area of the state. Even with 107 tornadoes reported in llIinois in 1974 (the greatest number reported in the last 30 years), the affected area was only about 0.3% the total area of the' state. These numbers do not diminish the effect on those experiencing property damage, injury, or worse, but they demonstrate the extremely low probability of direct impact at any given location.
The most recent study on tornadoes in llIinois (Wendland and Guinan 1988) examined events from 1955 to 1986 and found no apparent trend in tornado frequency or intensity. On average, the Kaskaskia River Assessment Area experiences about one tornado every year.
Hail
Hail events are somewhat rare and typically affect a very small area (from a single farm field up to a few square miles). Unfortunately, very few NWS Coop sites measure hail. The combination of small, infrequent events being measured by a sparse climate network makes for very few reliable, long-term records of these events, particularly for large areas.
Based on Changnon (1995), the Kaskaskia River Assessment Area experiences 2.4 hail days per year, with the actual number varying greatly from year to year. The year with the most hail days was 1909 with seven. There are no indications of trends in hail days, based on the records from St. Louis, Missouri from 1901 to 1994.
Thunderstorms
On average, the Kaskaskia River Assessment Area experiences about 37 days with thunderstorms each year. The annual number of days with thunder over the Kaskaskia River Assessment Area since 1945 is shown in Figure 14, which is composed of data from St. Louis, Missouri (1945-1997). There is substantial year-to-year variation in thunderstorm days, ranging from as many as 59 in 1982 to as few as 19 in 1971. There are no trends evident in thunderstorm days over the 1945-1997 period at St. Louis.
Summary
The average annual temperature for Sparta shows a warming trend through 1940, followed by a cooling trend through 1997. Pana records show a similar pattern except for a warming period from 1986 to 1995. The number of days with temperatures above or equal to 90°F shows an increase in the number through the mid-1930s, followed by a decline through the mid-1970s before returning to slightly higher numbers through 1998 for both stations. The number of days with temperatures below or equal to 32°F showed no clear trends.
24
60
~50 :::l
~40 .c 1 ~30 ~ '0 .. 20
A n•
\1' V'I\ V ".J
V\
10 1940 1950 1960 1970 1980 1990 2000
Figure 14. Annual Number ofDays with Thunderstorms at St. Louis, Missouri, 1945-1997
For precipitation, there was a slight downward trend through 1940 before reversing and becoming an upward trend through 1998 for both sites. The number of days with measurable precipitation showed no trend. Snowfall amounts decreased through the early 1940s before increasing the early 1980s. Snowfall at both stations decreased slightly in the last 15 years of the record.
Records extending back to 1901 show no clear trends in hail events. Similarly, there are no apparent trends in tornado events, although reliable records date only to 1955. The number of days with thunderstorms has been recorded since 1945 with no trends through 1997.
25
Streamflow and Trends in Streamflow
Surface water resources are an essential component of any ecosystem because they provide different types of habitats for aquatic and terrestrial biota. In addition to their natural functions, they are sources of water supply for domestic, industrial, and agricultural use. Changes in natural and human factors, such as climate, land and water use, and hydrologic modifications, can greatly affect the quantity, quality, and distribution (both in space and time) of surface waters in a river basin.
There are about 8,680 miles of rivers and streams in the Kaskaskia River Assessment Area. The status of these rivers and streams is monitored by streamgaging stations, which measure the flow of water over a period of time, providing information on the amount and distribution of surface water passing the station. Since it is not feasible to monitor all streams in a basin, gaging stations are established at selected locations, and the data collected are transferred to other parts of the watershed by applying hydrologic principles. Streamflow records are used to evaluate the impacts of changes in climate, land use, and other factors on the water resources of a river basin.
Streamgaging Records
The u.s. Geological Survey has operated 31 continuous-discharge streamgages in the Kaskaskia River Assessment Area that have had periods of record in excess of five years. These stations are listed in Table 9, and their locations are shown in Figure IS. Twenty of these gages are currently active. Only four of the stations have long-term records, in excess of 50 years. The gaging station on the Kaskaskia River at Vandalia has an 84year record, which is one of the longest continuous records of daily streamflow in the State.
Human Impacts on Streamflows in the Assessment Area
Climate variability causes the greatest influence on the changes in streamflows from year to year and decade to decade. Its influence is usually large enough to mask all or part of the impacts of the less obtrusive human modifications to the rivers' flows, including many types of land use modification. The major changes to the climate during this century are assumed to occur from natural climatic variability, but it is possible that in the future they may be shown to also have human influences.
The characteristics of streamflow in any moderately developed watershed will, over time, vary from earlier conditions because of the cumulative effect of human activities in the region. Like most locations in llIinois, the Kaskaskia River Assessment Area has experienced considerable land use modification since European settlement, including
27
Scale U362240
"""~====~~===~~"'.....
N Basin Boundary Gaging stations
StreamsN
Figure 15. Location of Streamgages in the Kaskaskia River Assessment Area
28
Table 9. USGS Streamgages in the Kaskaskia River Assessment Area with Daily Continuous Discharge Records for Five Years or Longer
USGSID 05590000 05590400 05590500 05590800 05591200 05591500 05591550 05591700 05592000 05592050 05592100 05592300 05592500 05592575 05592600 05592800 05592900 05593000 05593520 05593525 05593575 05593600 05593900 05594000 05594090 05594100 05594330 05594450 05594800 05595000
05595200
Drainage Station name area mi' Kaskaskia Ditch at Bondville Kaskaskia River near Pesotum Kaskaskia River at Ficklin Lake Fork at Atwood Kaskaskia River at Cooks Mills Asa Creek at Sullivan Whitley Creek near Allenville West Okaw River near Lovington Kaskaskia River at Shelbyville Robinson Creek near Shelbyville Kaskaskia River near Cowden Wolf Creek near Beecher City Kaskaskia River at Vandalia Hickory Creek near Brownstown Hickory Creek near Bluff City Hurricane Creek near Mulberry Grove East Fork Kaskaskia River near Sandoval Kaskaskia River at Carlyle Crooked Creek near Hoffman Crooked Creek near Posey Little Crooked Creek near New Minden Blue Grass Creek near Raymond East Fork Shoal Creek near Coffeen Shoal Creek near Breese Sugar Creek at Albers Kaskaskia River near Venedy Station Mud Creek near Marissa Silver Creek near Troy Silver Creek near Freeburg Kaskaskia River at New Athens
Richland Creek near Hecker
12 109 126 149 473
8 35
112 1054
93 1330
48 1940
44 78
152 113
2719 254 344
84 17 56
735 124
4393 72
154 464
5181
129
Period of record
42 1948-1990 14 1965-1979 10 1954-1964 26 1972-present 28 I970-present 32 1950-1982 18 1980-present 18 I980-present 58 1940-present 19 I979-present 28 I970-present 23 1959-1982 84 1914-present 10 I988-present 8 1980-1988
28 1970-present 19 1979-present 60 1938-present 24 1974-present
6 1968-1974 31 1967-present 22 1960-1982 35 1963-present 53 1945-present 9 1973-1982
29 1969-present II 1971-1982 32 1966-present 28 1970-present 43 1914-1921;
1935-1971 28 1970-present
Note: *RL '= record length
cultivation, removal of wetland areas, and deforestation. The most widespread land use modifications occurred prior to the onset of streamgaging activities, and thus their impact cannot usually be detected in the gaging records. More recent modifications to the landscape have included changes in agricultural management and urban development. These land use modifications may have a noticeable impact on the local hydrology, but the ability to detect these impacts within a gaging record may often be limited, particularly when the stream has a larger diverse watershed or there has been a significant trend in climate.
29
II
Water use and water resource projects often have the most readily-definable impacts on the streamflows. The temporal distribution of flows for many locations on the Kaskaskia River and several tributaries have been significantly impacted by reservoirs built for water use and flood control. In addition, the discharge of treated wastewaters has modified the low flow conditions of streams in the vicinity of urban areas, specifically near the East St. Louis metropolitan area, Champaign-Urbana, and Centralia.
Annual Streamflow Variability
A majority of the water that falls as precipitation is stored by the soil and eventually returns to the atmosphere through evapotranspiration (evaporation plus transpiration from plants). The average annual amount of evapotranspiration in the Kaskaskia River Assessment Area is roughly 29.5 inches, ranging from 28 inches along the northern edge of the watershed to 31 inches along the southern edge. The estimated amount of evapotranspiration has been decreasing over the 50 years such that average over the last 30 years is less than 29 inches per year. One possible explanation for this decrease is the general decrease in air temperatures observed in the assessment area since 1940. Another contributing factor could be changes in land use practices, with a trend away from forage and grass crops to row crops.
Most of the water that is not lost from the land surface through evapotranspiration •
ultimately flows to the streams, by way of either runoff following precipitation events or from the more gradual seepage of water stored in the soil and shallow groundwater. The average amount of streamflow during the last 60 years has been approximately 10.3 inches, equivalent to roughly 26% of the average amount of rainfall (40 inches) over that period. This represents an average flow of approximately 0.75 cubic feet per second (cfs) per square mile of drainage area. Over the last 30 years, the average annual precipitation over the basin has increased slightly, and the corresponding average streamflow has risen approximately 7% to about II inches per year. This rise in average flow coincides with the reduction in evapotranspiration, described in the preceding paragraph.
Average streamflow varies greatly from year to year, and can also show sizable variation between decades. Figure 16 shows the annual series of average streamflow for many of the USGS gages listed in Table 9. Flows are presented in units of inches of runoff over each stream's watershed. The series of average annual streamflows are generally very similar for gages in the largest watersheds (Figure 16a), which are primarily located on the Kaskaskia River. There is greater variability in the average flow on smaller streams (Figure 16b), and this is especially true when the gages are located on opposite ends of the assessment area.
The highest runoff amounts over the period of record, with annual runoff generally exceeding 20 inches, occurred in 1927, 1950, 1973, 1974, and 1993. The lowest annual runoff amounts, less than 3 inches, occurred in the drought periods of 1931,1940-1941, and 1954.
An examination of Figure 16b suggests that average streamflows have been noticeably greater in the past 30 years, as compared to the period from 1945 to 1970. The years
30
30 r-------,.=.,...==............=.,..."""""=-="'""'t;--------------,-+-Kaskaskia River at Cooks Mills ~Kaskaskia River at Shelbyville -A- Kaskaskia River near COwden -....H-Kaskaskia River at Vandalia25 __Kaskaskia River at Ca~yle
-IrKaskaskia River near Venedy Station --e- Kaskaskia River at New Athens,
5
a o+-__+-----:::.-+-__-+-_----l~--_+_--_+_--_+_--_+_---l
1915 1925 1935 1945 1955 1965 1975 1985 1995
30 -r---------------------------------, __Lake Fork at Atwood -+--Asa Creek at Sullivan -e-Hurricane Creek near Mulberry Grove -+- Little Crooked Creek near New Minden
25
5
--tr-East Fork Shoal Creek near Coffeen -+-Shoal Creek near Breese -e--Silver Creek near Troy --H-Richland Creek near Hecker
b o+------'4------+------+------t-----t-----l 1945 1955 1965 1975 1985 1995
Figure 16. Average Annual Streamjlows in the Kaskaskia River Assessment Area
31
1952-1966 were particularly dry, and several of the most severe droughts in the assessment area occurred during this period. The increase in average flow amounts are likely associated with a slight increase in precipitation over the last 30 years and a slight overall reduction in evapotranspiration, as described earlier.
Statistical Trend Analysis
Trend coefficients were estimated for the annual flow record for selected individual stations, and are presented in Table 10. In general, stations were chosen that have longer periods of record and are believed to be representative of general flow conditions throughout the watershed. Stations at some other locations, such as those on the Kaskaskia River at Shelbyville and Carlyle, were omitted because they are located immediately downstream of reservoirs and other features that have caused a well-defined modification to the flow conditions.
Table 10. Trend Correlations for Annual and Seasonal Flows
Station name Years
anal zed Kendall trend correlation
Annual Fall Winter S rin Summer. Kaskaskia Ditch at Bondville Kaskaskia River at Cooks Mills Kaskaskia River at Vandalia Hurricane Creek near Mulberry Grove Little Crooked Creek near New Minden East Fork Shoal Creek Near Coffeen Shoal Creek near Breese Silver Creek near Troy
1948-1990 1970-1997 1914-1997 1970-1997 1967-1997 1963-1997 1945-1997 1966-1997
0.244 0.046 0.110 0.022 0.172 0.136 0.074 0.090
0.263 -0.108 0.066 0.046 0.286 0.125 0.059 0.149
0.120 -0.071 0.149 -0.077 -0.044 0.004 0.070
-0.062
0.163 0.145 0.060 0.114 0.207 0.102 0.142 0.099
0.143 -0.108 0.104
-0.145 0.030
-0.008 -0.158 -0.103
The Kendall trend statistic was used to provide an indicator of the increase or decrease in the flow values. A Kendall correlation of 1.0 indicates that there is an absolute increasing trend, with each year having a higher flow than the previous year. A Kendall correlation of -1.0 indicates an absolute decreasing trend, and a correlation of 0.0 indicates no trend. The statistical significance of a trend correlation depends in part on the length of the record being analyzed. With a 50 year record, correlation values greater than 0.16 or less than -0.16 indicate that there exists a statistically significant trend, one that can be declared with 90% level of confidence. To establish statistical significance, shorter records require a higher correlation value and longer records do not need as high a correlation value.
The results of the trend analysis, given in Table 10, are variable. Though all of the stations display a positive coefficient for annual average flows, in only one case does the coefficient indicate a trend that is significant with 90% confidence, that being for the Kaskaskia River at Bondville. The gages on the Kaskaskia River at Vandalia and Little Crooked Creek have annual coefficients that are significant with 80% confidence, and all other locations are assumed to have no annual trend.
32
- - - - - -
- - - - - - - - - - - -- - - - - - - - - - - - - - -
Of additional interest is the season during which the flow increases have occurred. The Little Crooked Creek and the Kaskaskia Ditch gages also show increasing trends in Fall and Spring flows, but in general most stations show little or no trend throughout the four seasons.
Daily and Seasonal Flow Variability
As with all other locations in llIinois, streams in the Kaskaskia River Assessment Area display a well-defined seasonal cycle. As shown in Figure 17 for Shoal Creek near Breese, flows are expected to be greatest during the late winter and spring months, February-May, while lower flows are more common in late summer and autumn. This figure shows that the average flow in any month can vary considerably from the long-term median condition. Throughout most of the year, high flows are as much as ten times the average flow for any given month, while low flows are typically 20-25% of the average.
10000,....,-...,...,....,..-.-.-....,...,. ...,..."""",-,"",,-,...,..,.,..-. ..,....,""'. ...,.. ...,.. ...,.. . ..,.. . .,.,..,.,-,-.-. ...,..,-,-,..,.,..,.,""',-.-. . .,.,..,.,-.""'.-. . .,....,....,....,.,.... . .,. . ...,., - - . - - - - - - . - - - - - - - - . - -
- - - - - - - - - - - - - - . - -
1000
~ w ~ 100
u
i5'"10 -+-90%
-9-50"10 __10"10
1 ........--+--+_--+--+_--+--+_-_+--+---_+--+----1 Jan Feb Mar Apr May Jun Jul Aug Sep OCt Nov Dec
Figure 17. Probabilities ofExceedencefor Monthly Flows. Shoal Creek near Breese
Figures 18 and 19 are flow duration curves for selected gages within the Kaskaskia River Assessment Area. The flow duration curve is a graph that plots a given flow amount (on the y axis) with the estimated frequency at which that given flow will be exceeded (on the x axis).
Figure 18 plots the flow duration curves for gages on the Kaskaskia River for two different periods of record, 1940·1969 (Figure 18a) and 1970-1996 (Figure 18b). The two parts of Figure 18 show the difference in flow frequencies between the "natural" flow conditions
33
100000
10000
'lJ'" 1000 W <!l
~ ()
15 100
10
10 20 30 50 70 80 90
b--.~
~ """1'-, ..... ~ ........ "-- .....
~........::.....,~ ~t--- ~ ........ ~ ""'Ii... .....
....,~ .......... r---.. t::~~ ....,"--i"~ :--.
f--.l h .... ~ "-...... 1'"'-1 ~ ....r--, ~t--.. ..............Kaskaskia River at Shelbyville ~ -e-Kaskaskia River at Vandalia ~
__Kaskaskia River at Ca~y1e r---..... ~Kaskaskia River at New Athens '-.....
~ a 99
PERCENT CHANCE OF EXCEEDENCE
100000
10000
{lloo0 W
~ ~ 100is
10
99
- ...... ~"-
............... ~..... II---t 1'-111-< ~ ::-.....
~~~~ ~~~ .....
~ ~ .......'\ ~ ........ ~~~'" ........Kaskaskia River at Shelbyville ~
'"-e-Kaskaskia River at Vandalia ........, __Kaskaskia River at Ca~y1e ..........., __Kaskaskia River near Venedy Station
~ b
10 20 30 50 70 80 90 PERCENT CHANCE OF EXCEEDENCE
Figure 18. Flow Duration Curves"(Discharge Versus Probability) for the Kaskaskia River: a) 1940-1969; b) 1970-1997
34
10000 ,-t------t---j--j---j--t-t--j--j---j---t--t--t---t--t---j------t-,
1000
1l 100 W· <!l..a::I: o ~ 10
~Asa Creek at Sullivan -e-Hurricane Creek near Mulberry Grove -.-Little Crooked Creek near New Minden ........... East Fork Shoal Creek near Coffeen .-..-Shoal Creek near Breese --e-Silver Creek near Troy---*-Richland Creek near Hecker
0.1 -'-"'!-----I---:4:---I--::I:-+-:+:--I---:+--I---:~-I-:+--+-~:__---'l .....----""~ 10 20 30 50 70 80 90 99
PERCENT CHANCE OF EXCEEDENCE
Figure 19. Flow Duration Curves (Discharge Versus Probability) for Tributary Streams in the Kaskaskia River Assessment Area
as they existed prior to 1970 compared to that following the constructions of Lake Shelbyville and Carlyle Lake. The general shapes of the flow frequency curves are similar, however since the reservoir constructions the river has experienced a decrease in the magnitude of high flows, and an increase in the magnitudes of medium and low flows. The changes are especially apparent for the Carlyle gage, located immediately downstream of Lake Carlyle, for which the flow duration curves flatten out at the maximum reservoir outflow of 10,000 cfs and the minimum flow release of 50 cfs.
Figure 19 shows the flow duration curves for 7 tributary streams in the Kaskaskia River Assessment Area. The variations in the overall shapes of these flow duration curves normally point to either human impacts on strearnf10ws or major differences in the hydrology of the streams. For example, Richland Creek at Hecker, displays a very flat slope for low flow conditions, which indicates that the low flows in the stream are dominated by effluent discharges that occur upstream of the gage, specifically from the Belleville wastewater treatment facility. The flows at all of the other stations have only relatively small modifications as caused by reservoirs, withdrawals, or discharges. The low flows on large watersheds are generally sustained to a greater degree, as indicated by a flatter slope in the flow duration curve, while low flows on small watersheds tend to recess more quickly.
35
----------------------------------_._-
Flooding and High Flows
Figure 20 shows the annual series of peak flood discharges for selected gaging locations. The peak discharge records for the Kaskaskia River (Figure 20a) display the impacts of the two large flood control reservoirs at Shelbyville and Carlyle. Since 1970, the maximum peak outflows from Lake Shelbyville and Carlyle Lake have been roughly 5,000 and 10,000 cfs, respectively. Despite the substantial reductions in peakflows at the reservoirs, the flow reductions at downstream locations are less obvious. At Vandalia, located 30 miles downstream of Lake Shelbyville, the six largest events occurred prior to the construction of that lake. However, since 1970 the average annual flood peak has been as high if not higher than in previous years. The same can also be observed in comparing the New Athens (1935-1969) and Venedy Station (1970-1997) flood records, where both gages are located downstream or Carlyle Lake.
The annual flood peaks for the tributary gages, shown in Figure 20b, generally show little overall trend in the highest events. However there has been an increase in the average annual flood peak in many of these stations. This is especially noticeable for the Shoal Creek gage near Breese, where annual flood peaks of 13,000-15,000 cfs have become common. It is possible that reservoirs located upstream of Shoal Creek may influence the maximum peakflow that occurs at the Breese gage, however this cannot be determined without a detailed hydrologic study. One contributing factor to the increase in average annual peakflows for many of the gages shown in Figure 20b is the absence of droughts, such as the ones that occurred in the region during the 1940s, 1950s, and early 1960s. The possible impact of human-induced factors on flood peaks cannot be determined from the available records.
Statistical Trend Analysis
Table 11 presents results of a statistical trend analysis of flood records for gaging stations in the assessment area. The analysis of flood volumes given in this table uses the 7-day high flow as a representative parameter for flood volume. The trend coefficients indicate that the three gages in the northern portion of the Kaskaskia River Assessment Area, on Kaskaskia Ditch, Lake Fork, and the Kaskaskia River at Cooks Mills, have experienced noticeable increasing trends in both flood volumes and flood peaks.
The Kaskaskia River at Vandalia has experienced a slight increasing trend in peakflows, but has not experienced a trend in flood volumes. It is believed that the presence of Lake Shelbyville does not noticeably impact the flood peaks at Vandalia, which can be caused by floodwaters entering the river downstream of Shelbyville, but that the lake does reduce the duration at which the floods stay at high levels.
36
100000
{j w Cl ~ 10000 I U en i5
1000 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000
III 1'1 'J / - j
J#li i" ~ ~ I, r,! ~A "'SlfIA 'I I~ " "
~ .~
• I "'-L \I \I [l!t ~ 11 ~ '1m
'f Ii \J\ r \ Cl "" ijf
~ -e-Kaskaskia River at Shelbyville - ~Kaskaskja River at Vandalia
-e-Kaskaskia River at Carlyle -......!r-Kaskaskia River near Venedy Station a........Kaskaskia River at New Athens .
100000
10000 J!! " W Cla: <I U en i5
1000
100 1945
__Hurricane Creek near Mulbeny Grova -a- Little Crooked Creek near New Minden --East Fork Shoal Creek near Colfaen __Shoal Creek neer Breese --e- Kaskaskia Ditch at Bondvilla
I';. ~ ~ " ~ )/ 7\. v
~T":x'"\ •
'\ I. I ~ \I _'1'/
·~Cl~ \II --v. I~ rw. Q
r ~ . ~if •
<i..I""\ _'" M \ 1I
17\..::Ill 11 lJ;)u )".. 'V 'it 'll b 1955 1965 1975 1985 1995
Figure 20. Annual Peak Discharges for Gaging Stations in the Kaskaskia River Assessment Area
37
Table 11. Trend Correlations for Flood Volume and Peakflow
Streamgaging station Years
analyzed Kendall trend correlation
Flood volume
Peakflow
Kaskaskia Ditch at Bondville Lake Fork at Atwood Kaskaskia River at Cooks Mills Kaskaskia River at Vandalia Hurricane Creek near Mulberry Grove Little Crooked Creek near New Minden East Fork Shoal Creek Near Coffeen Shoal Creek near Breese Silver Creek near Troy
1948-1990 1973-1997 1970-1997 1914-1997 1970-1997 1967-1997 1963-1997 1945-1997 1966-1997
0.143 0.146 0.335 0.028 0.102 0.325 0.061 0.180 0.062
0.199 0.110 0.262 0.135 0.048 0.207
-0.009 0.062 0.075
A few tributary streams in the remainder of the watershed show noticeable increases in flooding, in particular Little Crooked Creek near New Minden and Richland Creek near Hecker (not shown in Table 11). However, most streams do not show any significant trends. The record for Shoal Creek near Breese shows a slight increasing trend for flood volumes, but not for flood peaks:
Seasonal Distribution of Flood Events
Table 12 presents the monthly distribution of the top 25 flood events at the five gages. The occurrences of most of the major floods are evenly distributed throughout the period February to June, although December is also a common month for flooding. Floods from July to November are relatively uncommon, except on some of the smallest watersheds such as the Kaskaskia Ditch.
Table 12. Monthly Distribution of Top Twenty-Five Flood Events at Selected Stations
Month Jan Feb Mar Jun Jul Au Oct Nov Dec Kaskaskia Ditch at Bondville Kaskaskia River at Cooks Mills Asa Creek near Sullivan Kaskaskia River at Vandalia Little Crooked Cr. near New Minden East Fork Shoal Cr. Near Coffeen Shoal Creek near Breese Silver Creek near Troy
0 2 3 5 6 4 3 1 1 0 0 0
3 5 1 3 6 1 1 2 0 0 1 2
1 1 3 3 4 7 0 1 1 1 0 3
2 3 4 3 4 4 0 0 0 1 0 4
3 5 4 5 1 0 0 0 I 1 2 3
3 0 6 2 3 1 0 0 1 2 6
2 3 2 4 6 1 1 0 0 1 0 5
1 3 2 7 4 2 1 0 0 0 0 5
38
---------------_._.--
1930-31 1933-34 Kaskaskia River
18-month drought 158 468 7-day low flow IS 34
Shoal Creek 18-month drought 7-day low flow
Drought and Low Flows
Two flow parameters are used here to describe dry period flows: the 7-day low flow and the 18-month drought flow. The 7-day low flow is representative of the minimum streamflows that are measured during any given year, whereas the 18-month drought flow is specifically estimated for drought periods and is more representative of the persistence of a drought. Table 13 lists the 7-day low flow and 18-month flows for seven major droughts, as measured for two locations: the Kaskaskia River at Vandalia and Shoal Creek near Breese. The three lowest 18-month drought flow periods occurred in 19301931, 1940-1941 and 1953-1954. The regional droughts since 1954 have been comparatively moderate. Strearnflows in this Kaskaskia River Assessment Area were generally not heavily impacted by the drought of 1988-1989, which was a more serious drought in the central portion of the State.
Table 13. Historical Droughts and Low Flows
1976-77 1988-89
321 57 466 648 772 16 5 16 17 28
30 67 116 220 0.0 0.4 2.4 0.3
Figure 21 gives the annual7-day low flow series for gaging records on the Kaskaskia River. Figure 21a illustrates that there has been an increase in low flows on the Kaskaskia River at Shelbyville and Vandalia, but not at the stations located farther downstream. The minimum flow release from Lake Shelbyville is the primary cause for the comparative low flow increases at these two gages. The variability of low flows downstream of Carlyle Lake has changed significantly, such that most years experience low flows equal to or slightly above the minimum flow release of 50 cfs. However, there is no overall trend in the average low flow conditions downstream of the lake.
Figure 21b displays the annual 7-day low flows for selected tributary streams in the assessment area. Most tributaries in the Kaskaskia River Assessment Area experience zero flow during dry years, and are not shown in Figure 21b. The exceptions are the lower reaches of Shoal Creek, which is the largest tributary to the Kaskaskia River, Crooked Creek, which receives treated wastewater from the cities of Salem and Centralia, and Silver and Richland Creeks, which receive effluent discharges from treatment plants in the East St. Louis metropolitan area. Of the low flows shown in Figure 21b, the Richland Creek and Silver Creek records display a noticeable increase in low flows, these being caused by increases in the effluent discharges on the stream.
39
1000 .,....------------------------.1------------,
100
10
-+-Kaskaskia River at Shelbyville ~Kaskaskia River at Vandalia __Kaskaskia River at Carlyle ~Kaskaskia River near Venedy Station ~Kaskaskia River at New Athens
0.1 +----+---+_---+--~+_--_+_---t__--_+_--__If_-l
1915 1925 1935 1945 1955 1965 1975 1985 1995
100 ,,=============;:-------------:----,-+-Hurricane Creek near Mulberry Grove -e-Shoal Creek near Breese ~S;'ver Creek near Troy -M- Richland Creek near Hecker
10
0.1
b 0.01 +-------+------+---..>----i------II-----6--+------l
1940 1950 1980 1970 1980 1990 2000
Figure 21. Seven-Day Low Flows for Gaging Stations in the Kaskaskia River Assessment Area
40
Statistical Trend Analysis
Table 14 presents the Kendall trend coefficients for low flows at eight gaging records in the assessment area. There is little or no trend in low flows for most locations in the assessment area Four stations given in Table 14 display significant trends in low flows. The increase in low flows for the Kaskaskia River at Vandalia are caused by two factors: I) the general reduction in the frequency of several droughts over the last 30 years and 2) the minimum flow release from Lake Shelbyville. The low flows for Silver Creek near Troy and Richland Creek near Hecker have increased as a result of population growth and the associated increase in the discharge of treated wastewaters. The Kaskaskia River at Cooks Mills shows a negative trend because of a reduction in an upstream discharge used to sustain low flows for water supply purposes. Most of the smaller streams, which experience zero flows, show no trends.
Table 14. Trend Correlations for Low Flows
Stream a in station Years
anal zed Kendall trend correlation
Low flows Kaskaskia Ditch at Bondville Kaskaskia River at Cooks Mills Kaskaskia River at Vandalia Hurricane Creek near Mulberry Grove Little Crooked Creek near New Minden East Fork Shoal Creek Near Coffeen Shoal Creek near Breese Silver Creek near Troy Silver Creek near Freeburg Richland Creek near Hecker
1948-1990 1970-1997 1914-1997 1970-1997 1967-1997 1963-1997 1945-1997 1966-1997 1970-1997 1970-1997
0.154 -0.217 0.136
-0.140 0.074 0.060 0.057 0.315 0.033 0.302
Summary
The average amount of streamflow during the last 60 years has been approximately 10.3 inches, equivalent to roughly 26% of the average amount of rainfall (40 inches) over that period. The average annual flow has increased slightly over the last 30 years to about II inches per year, which appears to coincide with a relatively small increase in precipitation and a small reduction in air temperature. In general, the assessment area has experienced little change in either flooding or low flow conditions, although nonsystematic trends may be observed over the last 25 years for a few individual streamgaging records. Flows in the Kaskaskia River downstream of the area's two largest reservoirs, Lake Shelbyville and Carlyle Lake, are regulated and show changes in flooding and high flows. Annual flood peaks are significantly reduced immediately downstream of these reservoirs, however the magnitude of the flood reduction is attenuated farther downstream from each lake. Each reservoir has a minimum flow release that eliminates the occurrence of extreme low flow events at downstream locations, but does not substantially change the low flows for average years. The discharge of treated wastewaters has modified the low flow conditions of tributary streams in the vicinity of urban areas, specifically near the East St. Louis metropolitan area, Champaign-Urbana, and Centralia.
41
--------------------....,..-----------------
Erosion and Sedimentation
Instream Sediment Load
Instream sediment load is the component of soil eroded in the watershed and from the streambanks that is transported to and measured at a gaging station. It indicates the actual amount of soil generated upstream of the gaging station and eventually transported to downstream reaches of the river. Given the complex dynamic process of soil erosion, sediment transport, and deposition, it is very difficult to quantify how much of the soil eroded from uplands and streambanks actually moves to downstream reaches.
The sediment transported by a stream is a relatively small percentage of the total erosion in the watershed. However, the amount of sediment transported by a stream is the most reliable measure of the cumulative results of soil erosion, bank erosion, and sedimentation in the watershed upstream of a monitoring station.
There are four gaging stations in the Kaskaskia River Assessment Area where instream sediment was monitored for some time. As shown in Figure 22, the four stations are located on the Kaskaskia River at Cooks Mills, near Cowden, at Vandalia, and near Venedy Station, respectively. Table 15 summarizes information about the monitoring stations.
Table 15. Suspended Sediment Monitoring Stations in the Kaskaskia River Assessment Area
Station name Kaskaskia River at Cooks Mills Kaskaskia River near Cowden Kaskaskia River at VandaIia Kaskaskia River near Venedy Station
USGS station number
05591200 05592100 05592500 05594100
473 1,330 1,940 4,393
Period of record Jan. 1979-Sept. 1997 Nov. 198D-Jan. 1982 Oct. 198D-Sept. 1993 May 198D-Sept. 1997
At the Kaskaskia River at Cooks Mills and near Venedy Station, the U.S. Geological Survey (USGS) monitored sediment yield for nineteen water years (1979-1997), and for seventeen water years (1980-1997), respectively. Data collected by the USGS were reported as daily average concentrations. Therefore, daily and annual sediment loads at the stations can be calculated.
Data were collected by the Dlinois State Water Survey (ISWS) for almost two water years (1981-1982) at the Kaskaskia River near Cowden. In addition, the ISWS collected
43
Scale 1: 1362240
N Basin Boundary • Sediment monitoring stations
N Streams
Figure 22. Location of Sediment Monitoring Stations in the Kaskaskia River Assessment Area
44
sediment data at the Kaskaskia River at Vandalia for almost twelve water years (19811988 and 1990-1993). The sediment data collected by the ISWS were instantaneous weekly samples. Therefore, only instantaneous sediment loads can be calculated, not average daily or annual sediment loads.
Figures 23-26 show daily and instantaneous sediment concentrations and loads for the four stations monitored. The figures show the variability of streamflow (Qw), suspended sediment concentration (C,), and suspended sediment load (Q,). Water years start on October 1 and end on September 30.
For the Kaskaskia River at Cooks Mills (Figure 23), concentrations varied from a low of 0.9 milligram per liter (mgll) to a high of 1,697 mgll measured by the USGS during the period of January 1979 to September 1997. Higher concentrations occurred in the spring (April and May), the summer (June and July), and, sometimes, in the winter (February). For the Kaskaskia River near Venedy Station (Figure 24), concentrations varied from a low of 4.9 mgll to a high of 3,114 mgll measured by the USGS during the period of May 1980 to September 1997. Higher concentrations frequently occurred in the spring (March, April, and May), and the summer (June and July). For the Kaskaskia River at Vandalia (Figure 25), concentrations varied from a low of 1 mgll to a high of 2,639 mgll based on the ISWS data. Data at this station show higher concentrations occurred during the spring (April and May) and the summer (June). For the Kaskaskia River near Cowden (Figure 26), concentrations varied from a low of 17 mg/l to a high of 3,015 mg/l during the water year 1981 based on the ISWS data.
To provide values in tons per day, sediment load was computed by multiplying the daily water discharge by the instantaneous sediment concentrations and applying the proper unit conversion factors. For stations with weekly sediment sampling--the Kaskaskia River near Cowden and at Vandalia --it was not possible to compute average daily and annual sediment loads. However, instantaneous sediment load provides a range of values to compare variability of sediment from year to year and from station to station.
For the Kaskaskia River at Cooks Mills and near Venedy Station, the average daily sediment load measured by the USGS varied from 0.1 tons per day to 26,100 tons per day, and from 1.9 tons per day to 46,200 tons per day, respectively. For the Kaskaskia River near Cowden and at Vandalia, the instantaneous sediment load measured by the ISWS varied from 1.6 tons per day to 28,860 tons per day, and from 0.2 tons per day to 26,828 tins per day, respectively.
It should be noted that sediment load depends on the size of the drainage area; therefore, a station with a larger drainage area will generally have a higher sediment load than one with a smaller drainage area under similar conditions. For this reason, the Kaskaskia River near Venedy Station had the highest daily sediment load.
Annual sediment load can be calculated for the Kaskaskia River at Cooks Mills and near Venedy Station for water years from 1979 to 1997, and for water years from 1981 to
45
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Date
Figure 23. Variabilities ofFlow Discharge and Suspended Sediment Concentration and Loadfor the Kaskaskia River at Cooks Mills
46
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Figure 24. Variabilities ofFlow Discharge and Suspended Sediment
Concentration and Loadfor the Kaskaskia River near Venedy Station
47
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Figure 25. Variabilities of Instantaneous Flow Discharge and Suspended
Sediment Concentration and Load/or the Kaskaskia River at Vandalia
48
5000 ~----------------------, 05592100 Kaskaskia River near Cowden
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Figure 26. Valiabilities ofInstantaneous Flow Discharge and Suspended Sediment Concentration and Loadfor the Kaskaskia River near Cowden
49
--------------------------------- --
1997, respectively, based on the USGS data. As shown in Table 16, annual sediment load at the Kaskaskia River at Cooks Mills varied from a low of 11,460 tons in 1980 to a high of 169,595 tons in 1979, with an annual average of 47,652 tons. It should be noted that the 1979 load for the Kaskaskia River at Cooks Mills was only for a period of nine months. The annual sediment load at the Kaskaskia River near Venedy Station varied from a low of 227,071 tons in 1992 to a high of 1,010,988 tons in 1983, with an annual average of 577,213 tons.
Table 16. Annual Sediment Load for the Kaskaskia River Basin
Station name Water ear Water disehar e (efs) Sediment load (tons) Kaskaskia River 1979 211,473 169,595' at Cooks Mills 1980 67,690 11,460
1981 152,031 44,137 1982 213,052 30,921 1983 194,394 70,854 1984 216,755 45,554 1985 137,846 44,995 1986 178,851 43,246 1987 95,600 15,071 1988 137,153 13,978 1989 126,464 47,225 1990 153,372 77,448 1991 178,027 30,388 1992 100,471 12,319 1993 300,890 44,735 1994 243,028 63,502 1995 142,400 35,329 1996 181,401 81,322 1997 120,807 23,317
Kaskaskia River 1981 633,777 430,589 near Venedy Station 1982 1,889,691 990,789
1983 2,130,758 1,010,988 1984 2,435,360 969,332 1985 1,975,247 756,820 1986 1,269,421 487,164 1987 628.146 283,680 1988 1,309,632 495,928 1989 920,176 430,144 1990 1,108,602 416,481 1991 1,471,795 469,726 1992 436,853 227,071 1993 2,006,418 737,669 1994 2,331,423 506,190 1995 1,565,742 705,151 1996 1,366,860 537,787 1997 965,290 357,113
50
The corresponding sediment yield per square mile ranged from 24 tons per square mile in 1980 to 359 tons per square mile in 1979, with an average of 101 tons per square mile for the Kaskaskia River at Cooks Mills. For the Kaskaskia River near Venedy Station, the sediment yield per square mile varied from 52 tons per square mile in 1992 to 230 tons per square mile in 1983, with an average of 131 tons per square mile.
Sedimentation
Sedimentation is the process by which eroded soil is deposited in stream channels, lakes, wetlands, and floodplains. In natural systems that have achieved dynamic equilibrium, the rates of erosion and sedimentation are in balance over a long period of time. This results in a stable system, at least until disrupted by extreme events. However, in ecosystems where there are significant human activities such as farming, construction, and hydraulic modifications, the dynamic equilibrium is disturbed, resulting in increased rates of erosion in some areas and a corresponding increased rate of sedimentation in other areas.
Erosion rates are measured by estimating soil loss in upland areas and measuring streambank and bed erosion along drainageways. These measurements are generally not very accurate and thus are estimated indirectly, most often through evaluation of sediment transport rates based on instream sediment measurements and empirical equations.
Similarly, measurement of sedimentation rates in stream channels is very difficult and expensive. Lake sedimentation surveys provide the most reliable sedimentation measurements. Since lakes are typically created by constructing dams across rivers, creating a stagnant or slow-moving body of water, they trap most of the sediment that flows into them. The continuous accumulation of eroded soils in lakebeds provides a good measure of how much soil has been eroded in the watershed upstream of the lake.
Lake sedimentation rates for ten lakes in the Kaskaskia River Basin have been surveyed and are presented in Table 17. For most of these lakes, sedimentation rates (in percent per year) are low to moderate in comparison to most lllinois lakes. The sedimentation rate for Lake Lou Yaeger is higher than normal.
Lake Carlyle is the largest artificial lake in lllinois. It was completed in 1967 by the U.S. Army Corps of Engineers as part of the Kaskaskia River Basin development plan. The plan provides for flood control, water supply, storage for navigation releases, recreation and fish and wildlife conservation. As part of the management of the lake, the Corps has conducted sedimentation surveys in 1971, 1976, 1982, and 1984. The report on the 1984 sedimentation survey includes summaries for only the 1976 and 1984 survey results.
Highland Silver Lake was completed in 1961 to serve as a water supply reservoir for the city of Highland, lllinois. In the early 1980's the lake and its watershed were selected for detailed monitoring under the Rural Clean Water Program. The sedimentation surveys for Highland Silver Lake were conducted as part of these studies.
51
Table 17. Lake Sedimentation Rates in the Kaskaskia River Assessment Area
Watershed Original Surveyed Lake area volume Year volume Loss rate
Lake name acre-feet) surve ed (acre-feet) % er ear Carlyle Lake 24,600 ·281,000 1976
1984 270,000 255,000
0.43 0.54
Silver Lake 49 598 7,340 1976 1984
6,350 6,220
0.67 0.66
Lake Centralia 7.1 281 3,200 1993 2,590 0.24
Raccoon Lake 48 685 5,580 1959 1993
5,080 4,090
0.56 0.53
Salem City Reservoir 4 74 598 1960 531 0.23
Walton Park Lake 2 31 376 1959 187 0.52
Lake Lou Yaeger 115 1,315 15,800 1977 13,900 1.09
Lake Shelbyville 1,054 11,118 212,980 1980 1984
206,763 202,609
0.29 0.35
Nashville Reservoir 1 40 321 1954 289 0.55
Lake Kinmundy 1 24 174 1959 149 0.25
Lake Centralia was constructed in 1913 to serve as the water supply source for the city of Centralia. The spillway was raised in 1934. From 1925 to· 1955, The Water Survey conducted a monitoring program to determine hydrologic balances for the lake. In 1943, Raccoon Lake was constructed and became the primary water supply source for the city. In 1993, Lake Centralia was used primarily for recreational purposes but is still used on a limited basis to supplement for water supply.
Raccoon Lake was constructed in 1943 to serve as the primary water supply source for the city of Centralia. Lake Centralia now serves as a secondary water supply.
Salem City Reservoir was constructed in 1912 as a water supply reservoir for the city of Salem.
Walton Park Lake was constructed in 1862. The park and lake are located south of Litchfield.
Lake Lou Yaeger was completed in 1966 The lake was constructed as part of the Shoal Creek Watershed project to provide flood control, public water supply, and recreational benefits.
Lake Shelbyville was completed 1970 by the U.S. Army Corps of Engineers as part of the Kaskaskia River Basin development plan. The plan provides for flood control, water
52
supply, storage for navigation releases, recreation and fish and wildlife conservation. As part of the management of the lake, the Corps has conducted sedimentation surveys in 1974, 1980, and 1984. The report on the 1984 sedimentation survey includes summaries for only the 1980 and 1984 survey results.
Nashville reservoir was constructed in 1936 as a water supply reservoir for the city of Nashville.
Lake Kinmundy was constructed in 1902 as a water supply reservoir for the city of Kinmundy.
53
Water Use and Availability
Statewide, water use has increased a modest 27% since 1965 (lllinois Department of Energy and Natural Resources, 1994). Most of that increase is in power generation. Public water supply (PWS) use has risen only about 7% during that time, less than the concurrent percentage increase in population. The number of public ground-water supply facilities in llIinois has risen significantly during that time, yet the total amount supplied by ground water remains near 25%.
A dependable, adequate source of water is essential to meeting existing and potential population demands and industrial uses in lllinois. Modifications to and practical management of both surface and ground-water use have helped make llIinois' water resources reliable. As individual facilities experience increases in water use, innovative alternative approaches to developing adequate water supplies must be developed, such as use of both surface and ground waters. Major metropolitan centers such as the Chicago area, Peoria, and Decatur, as well as smaller communities, have already developed surface and ground water sources to meet their development needs and to sustain growth. The construction of impounding reservoirs has become and will remain economically and environmentally expensive, making it a less common approach.
Proper management of water resources is also necessary to ensure a reliable, high quality supply for the population. Water conservation practices will become increasingly imponant to reduce total demand and avoid exceeding available supplies. Both our ground-water resources and surface reservoir storage must be preserved to maintain reliable sources for future generations.
Ground-Water Resources
Ground water provides approximately one-third of llIinois' population with drinking water. The sources of this water can be broken down into three major units: 1) sand and gravel, 2) shallow bedrock, and 3) deep bedrock. Most ground-water resources are centered in the nonhern two-thirds of llIinois.
Sand-and-gravel aquifers are found along many of the major rivers and streams across the state and also within "buried bedrock valley" systems created by complex glacial and interglacial episodes of surface erosion. There are also many instances of thin sand-andgravel deposits in the unconsolidated materials above bedrock. These thin deposits are used throughout llIinois to meet the water needs of small towns. Shallow bedrock units are more commonly used in the nonhern third of llIinois, whereas the deep bedrock units are most widely used in the nonheastern quarter (in and around the Chicago area).
55
The variety of uses and the volume of water used vary widely throughout the state. This section describes ground-water availability and use in the Kaskaskia River Assessment Area.
Data Sources
Private Well Information
The Dlinois State Water Survey (ISWS) has maintained well construction reports since the late 1890s. Selected information from these documents has been computerized and is maintained in the Private Well Database. These data are easily queried and summarized for specific needs and form the basis of well distribution studies in the area.
Public Well Information
Public Water Supply (PWS) well information has been maintained at the ISWS since the late 1890s. Municipal well books (or files) have been created for virtually all of the reported surface and ground-water PWS facilities in lllinois. Details from these files are assembled in the Public-Industrial-Commercial Database, which was created to house water well and water use information collected by the ISWS.
Ground Water Use Information
The water use data given in this report corne from the records compiled by the ISWS' Dlinois Water Inventory Program (IWIP). This Program was developed to document and facilitate planning and management of existing water resources in Dlinois. Information for this program is collected through an annual water use summary mailed directly to each PWS facility.
Data Limitations
Severallirnitations must be taken into consideration when interpreting these data:
1. Information is reported by drillers and by each PWS facility. 2. Data measuring devices are generally not very accurate. 3. Participation in the IWIP is voluntary.
Information assembled from well construction reports and from the IWIP is considered "reported" information. This means that the data are as accurate as the reliability of the individual reporting or as mechanical devices dictate. The quality of the reported information depends upon the skill or budget of the driller or facility, respectively. Moreover, the ISWS estimates that only one-third to one-half of the wells in the state are on file at the Survey, mainly due to the lack of reporting regulations prior to 1976.
In general, water use measuring devices, such as the meters used by PWS facilities, are not very accurate. In fact, errors of as much as 10% are not uncommon. Much of the information reported in the IWIP is estimated by the water operator or by program staff.
56
Participation in the program is not required by the State of lllinois, and each facility voluntarily reports its information through a yearly survey. However, not all facilities know of or respond to the water use questionnaire. After several mail and telephone attempts have been mode to gather this information, estimates are made using various techniques. To help reduce errors associated with the program, reported water use information is checked against usage from previous years to identify any large-scale reporting errors.
Ground-Water Availability
The Kaskaskia River Assessment Area encompasses portions of twenty counties: Bond, Champaign, Clinton, Coles, Douglas, Effingham, Fayette, Jefferson, Macoupin, Madison, Marion, Monroe, Montgomery, Moultrie, Perry, Piatt, Randolph, Shelby, St. Clair, and Washington. The portion of each county in the watershed varies from I % (Jefferson) to 100% (Bond and Clinton). This section summarizes ground-water availability in the area, taking into consideration only those portions of each county that are actually in the watershed.
Domestic and Farm Wells
Available regional information indicates that ground water for domestic and farm use in the area is mos~ly obtained from small-diameter drilled wells and large-diameter bored wells finished within the unconsolidated materials above bedrock. Because of the size of the assessment area, ground-water resources vary greatly from the northeastern to the southwestern ends. To the northeast, good quantity and quality ground water can be obtained from the Mahomet Buried Bedrock Valley Aquifer system. Within the central and southern portions of the assessment area, shallow sand and gravel lenses and strips provide ground water to bored and drilled wells for domestic use. The shallow bedrock also provides small quantities of ground water for domestic use throughout the basin, however, this water is typically of poor quantity and quality throughout this part of lllinois. Availability of ground water ranges from good at the extreme northeastern part of the basin, to poor throughout most of the central and southern portions. The many surface water reservoirs scattered throughout this area is a good indicator of the poor quantity and quality of ground water in this part of lllinois.
Public Water Supply Wells
Information from the ISWS Public-Industrial-Commercial database indicates that virtually all (99%) of the ground water for P\vS use in the Kaskaskia River Assessment Area is obtained from drilled wells finished in sand and gravel deposits found within the unconsolidated materials above bedrock. These wells range in depth from 25 to 343 feet. The shallow bedrock is typically only used as an emergency reserve for 3 communities in the basin.
A total of 79 PWS facilities provide water to a reported 335,641 residents in and around the watershed. Twenty-one of the PWS facilities use surface water, 48 use ground water,
57
and 10 facilities purchase water from a surface water source facility. Average per capita daily water use in the watershed from these facilities is 76.7 gallons per day (gpd).
1995 Ground-Water Use
Ground water constitutes approximately 48% of the total water use in the Kaskaskia River Assessment Area. Total ground water use in the area is estimated to be 38.37 million gallons per day (mgd). Public Water Supplies withdraw 22.58 mgd, selfsupplied-industries withdraw 2.67 mgd, rural/domestic withdrawals are estimated at 5.52 mgd, and livestock watering is estimated to withdraw 7.60 mgd.
Public Water Supply
In 1995, municipal residential use for 48 communities using ground water is reported to be 22.58 mgd, serving a reported population of 189,824. The average per capita use of these municipalities is 64.24 gpd.
Self-Supplied Industry
Self-supplied industries are defined as those facilities that meet all or a portion of their water needs from their own sources. In the Kaskaskia River Assessment Area, 20 facilities reported ground-water pumpage during 1995 totaling 2.67 mgd.
Rural!Domestic
There is no direct method for determining rural/domestic water use in the basin. To get a rough estimate for the area, several assumptions were made using existing information. The population served and number of services reported by PWS facilities were used to calculate an average population per service for all the PWS facilities in the area. This number was used as an estimate of population per reported domestic well. The average PWS per capita use was then used as a multiplier to determine the total rural/domestic water use from each well. Since the ISWS' Private Well Database shows 21,786 reported wells in the area (Table 18), an average of 3.3 people per service (well), and an estimated average of 76.7 gpd per person, the total rural/domestic water use was estimated to be 5.52 mgd.
Livestock Watering
Water withdrawals for livestock use in 1995 were estimated to be 7.60 mgd. Water use estimates for livestock are based on a fixed amount of water use per head for each type of animal. Percentages of the total animal population (lliinois Department of Agriculture and U.S. Department of Agriculture, 1996) for the major livestock (cattle and hogs) in the counties were calculated based upon the percentage of county acres in the Kaskaskia River Assessment Area. Daily consumption rates (beef cattle =12 gpd, all other cattle = 35 gpd, and hogs = 4 gpd) provided the basis for these calculations.
58
Table 18. Number of Reported Private Wells in the Kaskaskia River Assessment Area
(Source: ISWS Private Wen Database)
Depth range, feet Count 0-50 51-100 101-150 151-200 201-250 251-300 301-350 351-400 >400 Bond 1361 170 44 20 0 3 3 0 5 Champaign 53 201 495 260 83 101 24 5 3 Clinton 1637 243 51 69 138 11 2 1 6 Coles 142 117 17 3 2 7 4 5 6 Douglas 91 462 68 3 0 7 3 0 1
Effingham 125 33 15 9 2 0 0 0 I Fayette 1435 344 53 23 11 1 0 1 2 Jefferson 3 0 0 0 0 0 0 0 0 Macoupin 63 5 0 0 0 0 0 0 1 Madison 1399 213 57 32 31 15 4 1 7 Marion 604 191 61 7 2 0 1 1 1 Monroe 180 121 299 190 150 52 54 64 102 Montgomery 1773 214 36 19 5 1 0 3 14 Moultrie 152 454 168 48 24 12 4 0 0 Perry 27 5 6 1 1 0 0 0 0 Piatt 233 342 217 58 38 3 0 0 0 Randolph 442 151 47 26 67 49 37 18 17 St. Clair 1388 489 102 112 204 191 123 54 67 Shelby 918 462 189 52 12 4 0 0 0 Washin on 536 69 103 51 41 3 6 1 4
Total 12562 4286 2028 983 811 460 265 154 237
Ground-Water Use Trends
Ground-water use in the watershed has remained relatively constant for the 6 years summarized for this report. Total ground-water use in the Kaskaskia River Assessment Area has averaged 25.15 mgd and has ranged from 23.44 to 26.85 mgd. Public Water Supply use has averaged 21.72 mgd and has ranged from 20.73 to 23.27 mgd over the years. Self-Supplied-Industry (SSI) has averaged 3.43 mgd and has ranged from 2.60 to 4.62 mgd. Table 19 shows the individual totals per year for 1990 through 1995. A slight downward trend is shown for the SSI pumpage over the 6 years totaled for this report. Poor quantity and quality of ground-water in this assessment area are most likely the cause of this trend. Surface water sources are more reliable for SSI purposes in this area. No significant trends are evident from the PWS facility ground-water pumpage in the watershed.
59
Table 19. Ground-Water Use Trends in the Kaskaskia River Assessment Area
(in million gallons per day)
Year PWS SSI Total 1990 21.10 4.40 25.50 1991 21.65 4.62 26.27 1992 20.98 2.60 23.58 1993 20.73 2.71 23.44 1994 23.27 3.59 26.85 1995 22.58 2.67 25.25 Averages 21.72 3.43 25.15
Surface Water Resources
The rivers, streams, and lakes of the Kaskaskia River basin serve a wide variety of purposes, including uses for 1) public water supply; 2) recreation, including boating, fishing, and swimming; and 3) habitat for aquatic life. The primary focus of this section is on water withdrawn from streams for public, industrial, and agricultural water supply, and the surface water resources available for such use.
Public Water Supply
Approximately 5.8 billion gallons per year, equivalent to an average 16.0 million gallons per day (mgd), are withdrawn from surface waters in the Kaskaskia River Assessment Area for use in public water supply. These withdrawals provide water for 64 communities in the Assessment Area, as identified in Table 20. Groundwater is often considered to be the first choice for water supply. But, with the exception of the Champaign-Urbana area in the northeast portion of the watershed, most of the larger communities in the assessment area obtain their water from surface sources. For much of the assessment area there are few known local sources of groundwater capable of providing a sufficient supply of water for a larger community. Many of the surface-source public water supplies in the Kaskaskia River Assessment Area have become interconnected, with some systems supplying water to communities more than 15 miles away from the source of withdrawal.'
Many reservoirs in the assessment area are used for water supply, including Lake Lou Yaeger, Highland Silver Lake, Governor Bond Lake, Vandalia Lake, Lake Pana, and Raccoon Lake. The two largest reservoirs in the assessment area, Lake Shelbyville and Carlyle Lake, are not used much for water supply, even though they were designed to potentially provide a regional water supply in addition to their primary function for flood control. There is only one small public water supply withdrawal from these two largest reservoirs, that being for the town of Keyesport.
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Table 20. Communities Using Surface-Source Public Water Supplies
PWS s stem name American Water Company
Breese Carlyle
Centralia
Coulterville Evansville Farina FSH Water Commission
Greenville
Highland
Hillsboro
Kaskaskia Water District
Keyesport Kinmundy Litchfield Nashville Pana Patoka St. Elmo
Salem SLM Water Commission
Sorento Vandalia
Pri source Ma'or communities served Mississippi River
Shoal Creek Kaskaskia River
Raccoon Lake
Coulterville Reservoir Kaskaskia River Borrow Pit Purchased--SLM Water Comm,
Governor Bond Lake
Highland Silver Lake
Lake Hillsboro
Kaskaskia River
Lake Carlyle Kinmundy Reservor Lake Lou Yaeger Nashville Reservoir LakePana North Fork Kaskaskia River Lake Nellie
Salem Reservoir Kaskaskia River
Sorento Reservoir Vandalia Lake
Belleville Millstadt Breese Beckmeyer Boulder Carlyle Centralia Hoffman Irvington Junction City Odin Coulterville Ellis Grove Farina Freeburg Hecker Donnellson Greenville Mulberry Grove Grantfork Highland Coffeen Hillsboro Lenzburg Marissa ' Keyesport Alma Butler Nashville Pana Patoka Brownstown St. Elmo Salem Lebanon Mascoutah New Baden Sorento Vandalia
O'Fallon
Huey Shattuc
Richview Sandoval Walnut Hill Wamac
Evansville
Smithton
Panama Smithboro
Pierron St. Jacob Schram City Taylor Springs New Athens Tilden
Kinmundy Litchfield New Minden
Vernon St. Peter
New Memphis Summerfield Trenton
61
There are two inter-basin transfers of water. The communities of Belleville, Millstadt, and O'Fallon obtain their water from the American Water Company, which withdrawals water from the Mississippi River. Sparta, located several miles east of the assessment area in Randolph County, withdraws water from the Kaskaskia River for part of its water supply.
Industrial and Cooling Water Supply
Approximately 1.5 billion gallons per day are withdrawn from surface waters for cooling purposes at two electricity-generating facilities. Two of the larger lakes in the assessment area, Baldwin Lake and Coffeen Lake, provide water for these cooling needs. Three industries supply their own water from surface sources (small lakes) for a total use of 3.7 mgd. An additional 2.8 mgd are withdrawn throughout the assessment area for other purposes such as recreation and irrigation.
Trends in Surface Water Use
The overall amount of water use can vary significantly by year. In general, surface water use within the lllinois portion of the Kaskaskia River basin has not changed significantly in the 1990s. Table 21 shows the individual annual amount of water use for the period 1990-1995.
Table 21. Surface Water Use Trends within the Kaskaskia River Basin, 1990-1995
Year PWS SSI 1990 17.6 1329 1991 14.7 1547 1992 14.5 1614 1993 14.0 1787 1994 17.2 1648 1995 18.0 1509
Average 16.0 1572
Potential for Development of Additional Surface-Water Sources
Water supply systems generally obtain surface water in one of three manners: I) direct withdrawal from a stream, 2) impoundment of a stream to create a storage reservoir, and 3) creation of an off-channel (side-channel) storage reservoir into which stream water is pumped.
Direct Withdrawals from Streams
For a stream to be used for public water supply, it is essential that it have a continuous flow of water during extreme drought conditions. The only stream in the Kaskaskia River Assessment Area that naturally has flow during extreme droughts is the Kaskaskia River. Several other streams have sustained flows because they receive a significant amount of
62
treated wastewaters, including Richland and Silver Creeks in St. Clair County and the lower portion of Crooked Creek, downstream of Centralia.
Currently there are four water withdrawal locations on the Kaskaskia River, as identified in Table 20. There is also a direct withdrawal from Shoal Creek at Breese. Although Shoal Creek is reduced to zero flow for short periods during severe droughts, the amount of storage behind the low-channel dam is sufficient to provide the water needs during these short periods. Other withdrawals from streams listed in Table 20, such as at Patoka, rely on side-channel reservoirs for a sustained supply of water.
Impounding Reservoirs
There are numerous existing reservoirs in the Kaskaskia River Assessment Area as well as many additional potential reservoir sites. Dawes and Terstriep (1966) identify nearly 60 potential reservoir sites, ranging from mostly small reservoirs to larger reservoirs with surface areas in excess of 5 square miles. These potential reservoir sites are shown in Figure 27. .
In general, the construction of impounding reservoirs has become a less common option for developing a water supply, primarily because of costs and environmental concerns. As a result, the proximity of alternative sources should be considered in the proposed development of reservoirs. But with the sparseness of groundwater supplies, the region may continue to rely upon reservoirs for much of its water supply.
Side-Channel Reservoirs
Side-channel reservoirs are storage facilities that rely upon pumping from other sources for their primary source of water. In many cases, the side-channel reservoir is located adjacent to the stream, which provides its source of water except during dry periods when the stream has no flow. There are three known side-channel reservoirs in the Kaskaskia River basin used for public water supply. The Patoka system uses two side-channel reservoirs, both supplied by pumping from the North Fork Kaskaskia River. The SLM Water Commission uses a side-channel reservoir to supplement pumping from the Kaskaskia River during low flow periods. The construction of side-channel reservoirs is generally not limited by local topography and is considered to be a viable water supply option along most streams in the basin. The amount of water supply that off-channel storage can provide is limited primarily by the temporal distribution of flow in the stream and the size of the storage reservoir.
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Scale 1: 1362240
N Basin Boundary • Potential reservoirs
N Streams
Figure 27. Location of Potential Reservoirs in the Kaskaskia River Assessment Area
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Ground-Water Quality
This section examines ground-water quality records to determine temporal trends and to provide baseline water quality parameters in the Kaskaskia River Assessment Area. Increasingly, ground-water contamination is discussed in the news media, and it may seem that the entire ground-water resource has been affected. However, these contamination events are often localized and may not represent widespread degradation of the ground-water resource. By examining the temporal trends in ground-water quality in the area, it may be possible to determine whether large-scale degradation of the ground-water resource has occurred.
The general term "ground-water quality" refers to the chemical composition of ground water. Ground water originates as precipitation that filters into the ground. As the water infiltrates the soil, it begins to change chemically due to reactions with air in the soil and with the earth materials through which it flows. Human-induced chemical changes can also occur. In fact, contamination of ground water is generally the result of humaninduced chemical changes and not naturally occurring processes.
As a general rule, local ground-water quality tends to remain nearly constant under natural conditions because of long ground-water travel times. Therefore, significant changes in ground-water quality can often indicate degradation of the ground-water resource.
Data Sources
The ground-water quality data that are used in this report come from two sources: private wells and municipal wells. The private well water quality data are compiled by the Chemistry Division of the lllinois State Water Survey (ISWS) as part of its water testing program and are maintained by the Ground-Water Information group in a water quality database. The municipal well data come from ISWS analyses and from the lllinois Environmental Protection Agency (IEPA) laboratories.
The combined database now contains more than 50,000 records of chemical analyses from samples analyzed at the ISWS and IEPA laboratories. Some of these analyses date to the early part of the century, but most are from 1970 to the present. Before 1987, most analyses addressed inorganic compounds and physical parameters. Since then, many organic analyses have been added to the database from the IEPA Safe Drinking Water Act compliance monitoring program. This report presents information for only a portion of the chemical parameters in the ISWS database.
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Data Limitations
Several limitations must be understood before meaningful interpretation of the water quality data can begin:
I. Representativeness of the sample 2. Location information 3. Data quality (checked by charge balance) 4. Extrapolation to larger areas
Private well samples are likely not completely representative of regional ground-water quality. In most cases, private well owners submit samples for analysis only when they believe there may be a problem such as high iron or an odd odor or taste. This suggests that while one or more constituents may not be representative, in general the remainder of the chemical information will be accurate and useful. As a result, the composite data may be skewed toward analyses with higher than normal concentrations.
On the other hand, private well information probably gives a better picture of the spatial distribution of chemical ground-water quality than municipal well information because of the larger number of samples spread over a large area. Recent IEPA data from municipal wells will not be skewed because each well is sampled and analyzed on a regular basis. While this produces a much more representative sample overall, samples are generally limited to specific areas where municipalities are located. Therefore, these data may not be good indicators of regional ground-water quality.
Much of the location information for the private wells is based solely on the location provided by the driller at the time the well was constructed. Generally, locations are given to the nearest 10-acre plot of land. For this discussion, that degree of resolution is adequate. However, it is not uncommon for a given location to be in error by as much as 6 miles. To circumvent possible location errors, this report presents results on a watershed basis.
The validity of water quality data was not checked for this report. However, previous charge balance checking of these data was conducted for a similar statewide project (lliinois Department of Energy and Natural Resources, 1994). Charge balance is a simple measure of the accuracy of a water quality analysis. It measures the deviation from the constraint of electrical neutrality of the water by comparing total cations (positively charged ions) with total anions (negatively charged ions). Because many of the early analyses were performed for specific chemical constituents, a complete chemical analysis is not always available from which to calculate a charge balance.
The statewide study searched the water quality database for analyses with sufficient chemical constituents to perform an ion balance. The charge balance checking of those data found that more than 98% of the analyses produced acceptable mass balance, which suggests that the chemical analyses are accurate in the database. Using that assumption
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for this report, we feel confident that most of the analyses used are accurate and give representative water quality parameters for the Kaskaskia River Assessment Area. However, this may be true only for large samples, a factor that should be considered when reviewing the results, as this report presents data from ten decades and a wide range of sample sizes.
Extrapolating a point value (a well water sample) to a regional description of groundwater quality is difficult and theoretically beyond the scope of this report. However, none of the data provide a uniform spatial coverage. Therefore, it seems best to summarize the data on a watershed basis to ensure an adequate number of values. The private well analyses are more numerous and will likely provide better spatial coverage than the municipal well data, which are concentrated in isolated locations.
Chemical Components Selected for Trend Analysis
In many cases, ground-water contamination involves the introduction into ground water of industrial or agricultural chemicals such as organic solvents, heavy metals, fertilizers, and pesticides. However, recent evidence suggests that many ofthese contamination occurrences are localized and form finite plumes that extend down gradient from the source. Much of this information is relatively recent, dating back a few decades, but long-term records at anyone site are rare.
As mentioned earlier, changes in the concentrations of naturally occurring chemical elements such as chloride, sulfate, or nitrate also can indicate contamination. For instance, increasing chloride concentrations may indicate contamination from road salt or oil field brine, while increasing sulfate concentrations may be from acid wastes such as metal pickling, and increasing nitrate concentrations may result from fertilizer application, feed-lot runoff, or leaking septic tanks. These naturally occurring substances are the major components of mineral quality in ground water and are routinely included in ground-water quality analyses.
Fortunately, the ISWS has maintained records of routine water quality analyses of private and commercial wells that extend as far back as the 1890s. After examination of these records, six chemical constituents were chosen for trend analyses based on the large number of available analyses and because they may be indicators of human-induced degradation of ground-water quality. These components are iron (Fe), total dissolved solids (TOS), sulfate (S04), nitrate (NO)), chloride (CI), and hardness (as CaCO)).
Aquifer Unit Analysis
Ground water occurs in many types of geological materials and at various depths below the land surface. This variability results in significant differences of natural ground-water quality from one part of lllinois to another and from one aquifer to the next even at the same location. For the purpose of this trend analysis, wells that were finished within the
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unconsolidated sand and gravel units were grouped together, as were wells finished within the bedrock units. Of the total 2661 samples reported, 2048 samples (77 %) were from the unconsolidated materials above bedrock with the remaining 613 samples reported from the bedrock in the assessment area. Tables 22 and 23 summarize the water quality from unconsolidated materials and the bedrock units, respectively. In this report, unconsolidated and bedrock aquifers are discussed separately in the descriptions of each chemical constituent.
Table 22. Chemical Constituents Selected for Trend Analysis,
Chemical constituent Iron (Fe)
Sample size (N) Minima (mgIL) Maxima (mgIL) Mean (mgIL) Median (mgIL)
IDS Sample size (N) Minimum (mgll) Maximum (mgll) Mean (mgll) Median (mgll)
Sulfate (SO.) Sample size (N) Minimum (mgll) Maximum (mgll) Mean (mgll) Median (mgll)
Nitrate (NO.) Sample size (N) Minimum (mgll) Maximum (mgll) Mean (mgll) Median (mgll)
Chloride (C1) Sample size (N) Minimum (mgll) Maximum (mgll) Mean (mgll) Median (mgll)
Hardness (as CaCO.) Sample size (N) Minimum (mgll) Maximum (mgll) Mean (mgll) Median (mgll)
Unconsolidated Aquifer Systems
Decade" 0 1 2 3 4 5 6 7 8 9
15 11 12 153 116 227 347 717 387 97 0.1 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 12.0 8.5 9.0 192.0 23.6 276.0 47.0 136.0 40.0 24.7 3.6 1.9 2.8 5.4 3.6 5.8 3.7 3.3 3.2 2.8 2.3 1.3 2.5 1.0 2.2 2.3 1.8 1.3 2.4 1.9
13 16 12 162 117 230 348 708 383 96 370.0 377.0 352.0 102.0 132.0 132.0 230.0 7.5 94.0 119.0
1113.0 2225.0 1195.0 5132.0 3092.0 4138.0 4001.0 7004.0 1817.0 2860.0 640.1 924.7 588.2 801.7 529.7 592.8 595.9 759.9 513.0 472.7 500.0 658.5 529.0 525.0 445.0 463.0 498.0 538.0 470.0 434.0
14 16 12 158 66 56 20 314 342 97 0.0 4.0 0.0 0.0 0.0 0.0 0.0 0.0 2.5 10.0
462.0 448.0 414.0 2890.0 514.0 1997.0 109.0 1474.0 668.0 346.0 128.3 90.1 95.8 202.6 64.5 116.8 27.9 76.4 58.4 45.9 50.0 32.0 31.0 30.0 5.5 2.0 3.0 30.0 17.5 10.0
14 14 11 143 42 96 205 652 59 0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 6.2 335.8 44.3 549.0 32.6 359.0 494.0 1143.0 160.0 0.0 0.6 29.5 5.2 45.2 3.1 10.9 30.4 71.8 9.1 0.0 0.0 1.6 0.6 2.8 1.0 0.8 2.3 1.8 0.9 0.0
15 16 12 163 115 228 348 713 387 97 5.0 4.0 4.0 1.0 1.0 1.0 0.0 0.0 1.0 1.0
128.0 680.0 73.0 858.0 150.0 475.0 1100.0 1060.0 910.0 1593.0 29.6 189.6 20.5 58.1 18.4 38.3 40.6 59.8 36.3 54.1 20.0 39.0 7.5 24.0 8.0 11.0 13.0 22.0 16.0 16.0
12 12 10 155 117 229 348 685 286 48 29.0 197.0 311.0 31.0 64.0 8.0 0.0 0.0 63.0 227.0
690.0 1049.0 714.0 3117.0 2462.0 2242.0 3020.0 3040.0 1666.0 744.0 361.0 423.6 465.8 463.7 354.2 380.3 379.5 420.1 339.0 329.4 340.0 370.5 437.5 341.0 312.0 308.0 328.0 344.0 323.5 325.0
Note: * Decade 0=1900-1909, Decade 1=1910-1919, and so on.
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Table 23. Chemical Constituents Selected for Trend Analysis,
Chemical constituent Iron (Fe)
Sample size (N) Minima (mgIL) Maxima (mgIL) Mean (mgIL) Median (mgIL)
TDS Sample size (N) Minimum (mgll) Maximum (mgll) Mean (mgll) Median (mgll)
Sulfate (SO.) Sample size (N) Minimum (mgll) Maximum (mgll) Mean (mgll) Median (mgll)
Nitrate (N03) Sample size (N) Minimum (mgll) Maximum (mgll) Mean (mgll) Median (mgll)
Chloride (CI) Sample size (N) Minimum (mgll) Maximum (mgll) Mean (mgll) Median (mgll)
Hardness (as CaC03) Sample size (N) Minimum (mgll) Maximum (mgll) Mean (mgll) Median (mgll)
Bedrock Aquifer Systems
Decade* 0 2 3 4 5 6 7 8 9
8 0.2 7.0 1.8 0.4
I 0.3 0.3 0.3 0.3
2 0.1 1.8 1.0 1.0
31 0.0
175.0 7.5 0.3
55 0.1
96.0 5.8 1.3
70 0.0 87.0 5.0 0.6
44 0.0
22.0 2.5 1.2
286 0.0 47.0 2.0 0.6
69 0.0 12.8 1.2 0.5
7 0.1 0.9 0.3 0.1
17 148.0
1602.0 505.8 425.0
2 457.0 1080.0 768.5 768.5
4 551.0
7007.0 2310.0 841.0
31 288.0
26220.0
2132.3 750.0
58 246.0
.6594.0 1112.1 538.0
71 335.0
9858.0 1902.2 943.0
45 245.0
8872.0 1546.9 713.0
279 152.1
20040.0
1013.6 570.0
69 295.0 10080.0
733.5 442.0
7 373.0 1230.0 700.1 605.0
4 0.0
1512.0 390.5 25.0
2 13.0
1169.0 591.0 591.0
4 0.0
3558.0 904.2 29.5
30 0.0
843.0 125.6 27.0
20 0.0
338.0 74.6 36.0
11 0.0
4300.0 529.3 26.0
9 0.0
294.0 43.1 5.0
135 0.0
1347.0 46.4 14.0
65 10.0
1323.0 58.4 17.0
7 16.0 41.0 28.5 31.3
8 0.0 1.1 0.3 0.0
1 2.0 2.0 2.0 2.0
2 0.4 0.9 0.7 0.7
29 0.0
208.0 19.2 1.6
8 0.0 8.0 2.5 0.7
26 0.0 19.3 2.6 0.7
21 0.2
69.5 4.7
0.7
203 0.0
720.0 19.2 0.4
6 0.5 5.2 1.5 0.8
0 0.0 0.0 0.0 0.0
18 1.0
700.0 69.3 18.5
3 4.0
9050.0 3118.0 300.0
4 35.0 53.0 44.8 45.5
32 1.0
8365.0 671.9 51.0
61 1.0
3600.0 292.1 43.0
71 1.0
5700.0 623.0 115.0
45 1.0
5200.0 556.0 60.0
280 1.0
12000.0
282.9 35.0
69 4.7
4800.0 161.4 22.0
7 7.0
421.0 126.0 27.0
7 44.0
352.0 174.6 130.0
1 824.0 824.0 824.0 824.0
0 0.0 0.0 0.0 0.0
32 10.0
1219.0 262.9 166.0
61 7.0
6330.0 510.6 304.0
71 4.0
3400.0 414.3 260.0
45 4.0
1840.0 268.0 232.0
273 3.0
2450.0 245.2 220.0
49 10.0
908.0 247.5 256.0
I 35.0 35.0 35.0 35.0
Note: * Decade 0=1900-1909, Decade 1=1910-1919, and so on.
Discussion and Results
Temporal trends in the six chemical constituents from the unconsolidated materials and bedrock units are summarized in this section. Tables 22 and 23 present the results of data
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points and the maximum, minimum, mean, and median of the decade analyses for each of the six chemical constituents for the unconsolidated materials and bedrock, respectively.
Median values are given in the table by decade, beginning with 1900-1909 (Decade 0), 1910-1919 (Decade 1), and so on through the 1990s (Decade 9). Each decade covers the corresponding ten-year period, except for the partial decade of the 1990s. Median concentrations are given per decade so that temporal trends can be identified in the dataset. Median values are the midpoints of a set of data, above which lie half the data points and below which is found the remaining half. These values are used to look at the central tendency of the dataset. Although the arithmetic mean would also look at this statistic, it incorporates all data points into its analysis, which can move the mean value in one direction or another based upon maximum or minimum values.
•
In many datasets, outliers occur. These are extreme values that tend to stand alone from the central values of the dataset. They may lead to a false interpretation of the dataset, whereas the median values are true values that are central to the dataset. By looking at the median we can determine trends in the central portions of the data. However, for datasets with a small number of samples, the median may not necessarily be representative of the water quality in the area.
It is important to recognize that the values included in these tables are reported values. While every attempt to verify the values was made, the validity of each value with regard to method error, etc. is not known. For this reason, the tables include every analysis in the database and all analysis results regardless of whether a value seems excessive and regardless of the sample size in the decade.
Iron (Fe)
Iron in ground water occurs naturally in the soluble (ferrous) state. However, when exposed to air, iron becomes oxidized into the ferric state and forms fine to fluffy reddish-brown particles that will settle to the bottom of a container if allowed to sit long enough. The presence of iron in quantities much greater than 0.1 to 0.3 milligrams per liter (mg/l) usually causes reddish-brown stains on porcelain fixtures and laundry. The drinking water standards recommend a maximum limit of 0.3 mg/l iron to avoid staining (Gibb, 1973).
Unconsolidated Aquifer Systems
Iron concentrations for unconsolidated aquifer systems in the watershed are given for each decade in Table 22. Minimum and maximum concentrations for all ten decades are 0.0 and 276.0 mg/l, respectively. The median values range from 1.0 to 2.5 mg/l for all ten decades. While these median values could cause staining of porcelain fixtures (greater than 0.3 mg/l), they generally pose no threat to human health. Table 22 suggests no significant trend in iron concentrations in the area.
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Bedrock Aquifer Systems
Iron concentrations for bedrock aquifer systems in the watershed are given for each decade in Table 23. Minimum and maximum concentrations for all ten decades are 0.0 and 175.0 mgll, respectively. The median values range from 0.1 to 1.3 mgll for all ten decades. These concentrations would be considered typical for ground water in lllinois and generally pose no threat to human health. Table 23 suggests no significant trend in iron concentrations in the area from the bedrock aquifer systems.
Total Dissolved Solids (TDS)
The IDS content of ground water is a measure of the mineral solutes in the water. Water with a high mineral content may taste salty or brackish depending on the types of minerals in solution and their concentrations. In general, water containing more than 500 mgll IDS will taste slightly mineralized. However, the general public can become accustomed to the taste of water with concentrations of up to 2,000 mgll. Water containing more than 3,000 mgll IDS generally is not acceptable for domestic use, and at 5,000 to 6,000 mgll, livestock may not drink the water. Because IDS concentration is a lumped measure of the total amount of dissolved chemical constituents in the water, it will not be a sensitive indicator of trace-level contamination. However, it is a good indicator of major inputs of ions or cations to ground water.
Unconsolidated Aquifer Systems
IDS concentrations in the unconsolidated aquifer systems in the watershed are given for each decade in Table 22. Minimum and maximum concentrations for all ten decades are 7.5 and 7004.0 mgll, respectively. The maximum concentration (7004.0) is a reported value; however, it should be viewed as an outlier of the dataset, and not as representative of the water quality in the area. Median values range from 434.0 to 658.5 mgll for all ten decades. Water with these concentrations would taste mineralized'but generally pose no threat to human health. There is no significant trend in IDS concentration indicated in these aquifer systems in the watershed.
Bedrock Aquifer Systems
IDS concentrations for bedrock aquifer systems in the assessment area are reported for each decade in Table 23. Minimum and maximum concentrations for all ten decades are 148.0 and 26220.0 mgll, respectively. Here too, the maximum concentration (26220.0) is a reported value; however, it should be viewed as an outlier of the dataset, and not as representative of the water quality in the area. Median values range from 425.0 to 943.0 mgll for all ten decades. Generally, there is no significant trend in IDS concentrations within bedrock aquifer systems in the assessment area. Any fluctuations from one decade to the next are more likely related to data limitations than to any inherent changes in ground-water quality.
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Water with high sulfate concentrations often has a medicinal taste and a pronounced laxative effect on those not accustomed to it. Sulfates generally are present in aquifer systems in one of three forms: magnesium sulfate (sometimes called Epsom salt); sodium sulfate (Glauber's salt); or calcium sulfate (gypsum). They also occur in earth materials in a soluble form that is the source for natural concentrations of this compound. Human sources similar to those for chloride also can contribute locally to sulfate concentrations. Coal mining operations particularly are a common source of sulfate pollution, as are industrial wastes. Drinking water standards recommend an upper limit of 250 mg/l for sulfates. Trends in sulfate concentrations can suggest potential ground-water pollution.
Unconsolidated Aquifer Systems
Sulfate concentrations for unconsolidated aquifer systems in the watershed are reported for each decade in Table 22. Minimum and maximum concentrations for all ten decades are 0.0 and 2890.0 mg/l, respectively. Once again, the maximum concentration (2890.0) is a reported value; however, it should be viewed as an outlier of the dataset, and not as representative of the water quality in the area. Median values range from 2.0 to 50.0 mg/l for all ten decades.
Bedrock Aquifer Systems
Sulfate concentrations for bedrock aquifer systems in the watershed are reported for each decade in Table 23. Minimum and maximum concentrations for all ten decades are 0.0 and 4300.0 mg/l, respectively. Median values are all well below the drinking water. standard, and range from 5.0 to 36.0 mg/l for all ten decades. Table 22 indicates variability, but no significant trend in sulfate concentrations in the watershed.
Nitrates are considered harmful to fetuses and children under the age of one when concentrations in drinking water supplies exceed 45 mg/l (as N03), or the approximate equivalent of 10 mg/l nitrogen (N).. Excessive nitrate concentrations in water may cause "blue baby" syndrome (methmoglobinemia) when such water is used in the preparation of infant feeding formulas. Inorganic nitrogen fertilizer has proven to be a source of nitrate pollution in some shallow aquifers, and may become an even more significant source in the future as ever increasing quantities are applied to Dlinois farmlands. Trends in concentrations of nitrate may be a good indication that farm practices in the area are affecting the ground-water environment.
Unconsolidated Aquifer Systems
Nitrate concentrations for unconsolidated aquifer systems in the watershed are reported for each decade in Table 22. Minimum and maximum concentrations for all ten decades are 0.0 and 1143.0 mg/l, respectively. The median values, which are all well below the drinking water standards (45 mg/l), range from 0.0 to 2.8 mgll for all ten decades and are
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---------------------------------------
indicative of representative concentrations in the unconsolidated materials. The ISWS has documented numerous cases of elevated nitrate levels associated with rural private wells (Wilson et aI., 1992). The evidence suggests that rural well contamination is associated more with farmstead contamination of the local ground water or well than with regional contamination of major portions of an aquifer from land application of fertilizers. This topic continues to be actively studied.
Bedrock Aquifer Systems
Nitrate concentrations for bedrock aquifer systems in the watershed are reported for each decade in Table 23. Minimum and maximum concentrations for all ten decades are 0.0 and 720.0 mgll, respectively. The maximum concentration (720.0) is a reported value; however, it should be viewed as an outlier of the dataset, and not as representative of the water quality in the area. Median values are all well below the drinking water standards, and range from 0.0 to 1.6 mgll for all ten decades.
Chloride (CI)
Chloride is generally present in aquifer systems as sodium chloride or calcium chloride. Concentrations greater than about 250 mgll usually cause the water to taste salty. Chloride occurs in earth materials in a soluble form that is the source for normal concentrations of this mineral in water. Of the constituents examined in this report, chloride is one of the most likely to indicate the impacts of anthropogenic activity on ground water. Increasing chloride concentrations may indicate contamination from road salt or oil field brine. The drinking water standards recommend an upper limit of 250 mgll for chloride. In sand and gravel aquifers throughout most of the state, chloride concentrations are usually less than 10 mgll.
Unconsolidated Aquifer Systems
Chloride concentrations for unconsolidated aquifer systems in the watershed are reported for each decade in Table 22. Minimum and maximum concentrations for all ten decades are 0.0 and 1593.0 mgll, respectively. Median values are well below the drinking water standard and range from 7.5 to 39.0 mgll for all ten decades. Table 22 indicates no significant trend in chloride concentrations in the watershed.
Bedrock Aquifer Systems
Chloride concentrations for bedrock aquifer systems in the watershed are reported for each decade in Table 23. Minimum and maximum concentrations for all ten decades are 1.0 and 12000.0 mgll, respectively. Median values range from 18.5 to 115.0 mgll for all ten decades. Table 23 indicates no significant trend in chloride concentrations in the watershed.
Hardness (as CaCOJ )
Hardness in water is caused by calcium and magnesium. These hardness-forming minerals generally are of major importance to users since they affect the consumption of
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soap and soap products and produce scale in water heaters, pipes, and other parts of the water system. The drinking water standards do not recommend an upper limit for hardness. The distinction between hard and soft water is relative, depending on the type of water a person is accustomed to. The ISWS categorizes water from 0 to 75 mgJI as soft, 75 to 125 mgJI as fairly soft, 125 to 250 mgJI as moderately hard, 250 to 400 mg/l as hard, and over 400 mgJI as very hard.
Unconsolidated Aquifer Systems
Hardness concentrations for unconsolidated aquifer systems in the assessment area are reported for each decade in Table 22. Minimum and maximum concentrations for all ten decades are 0.0 and 3117.0 mgJI, respectively. Median values range from 308.0 to 437.5 mg/l for all ten decades indicating hard to very hard ground water in this area within the unconsolidated materials.
Bedrock Aquifer Systems
Hardness concentrations for bedrock aquifer systems in the watershed are reported for each decade in Table 23. Minimum and maximum concentrations for all ten decades are 3.0 and 6330.0 mgJI, respectively. Median values range from 130.0 to 304.0 mgJI for all ten decades. Waters with these concentrations are considered moderately hard to hard. No trend are observed in hardness concentrations from the bedrock in this area
Summary
This work was undertaken to examine long-term temporal trends in ground-water quality in the Kaskaskia River Assessment Area. Data from private and municipal wells were the primary sources of information used to show the trends in six chemical constituents of ground water in the area. These data demonstrate that on a watershed scale, ground water has not been degraded with respect to the six chemicals examined. Fluctuations from one decade to the next are more likely related to data limitations than to any inherent changes in ground-water quality. It is also evident that the sample size in each decade can playa role in trend analysis.
Much of the contamination of TIlinois' ground water is localized. Nonetheless, this contamination can render a private or municipal ground-water supply unusable. Once contaminated, ground water is very difficult and expensive to clean, and clean-up may take many years to complete. Clearly it is in the best interests of the people of lllinois to protect their ground-water resource through prevention of contamination.
Although no significant trends in water quality are apparent for these six constituents, the information provides baseline water quality for the watershed. This information can be used in future studies of the area as a reference to determine whether the local groundwater quality is degrading.
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References
Introduction
lllinois Department of Natural Resources. 1996. lllinois Land Cover, An Atlas. IDNR96/05. Springfield, ll...
Knapp, H.V. 1990, Kaskaskia River Basin Streamflow Assessment Model: Hydrologic Analysis.
Leighton, M.M., G.E. Ekblaw, and L. Horberg. 1948. Physiographic Divisions of lllinois. lllinois State Geological Survey Report of Investigation 129.
Mattingly, R.L., and E.E. Herricks. 1991. Channelization of Streams and Rivers in lllinois: Procedural Review and Selected Case Studies. lllinois Department of Natural Resources Report ll..ENRIRE-WR-91/01.
Runge, E.C.A., L.E. Tyler, and S.G. Carmer. 1969. Soil Type Acreages for lllinois. University of lllinois Agricultural Experiment Station, Bulletin 735. Prepared in cooperation with the Soil Conservation Service, U.S. Department of Agriculture.
Suloway, L., and M. Hubble. 1994. Wetland Resources oflllinois: An Analysis and Atlas. lllinois Natural History Survey Special Publication 15. Champaign, ll...
Climate and Trends in Climate
Changnon, S.A., Jr. 1984. Climate Fluctuations in lllinois: 1901-1980. lllinois State Water Survey Bulletin 68. Champaign, ll...
Changnon, S.A., Jr. 1995. Temporal Fluctuations of Hail in lllinois. lllinois State Water Survey Miscellaneous Publication 167. Champaign, ll...
lllinois Department of Energy and Natural Resources. 1994. The Changing lllinois Environment: Critical Trends. Volume 1: Air Resources. ll..ENRIRE-EA-94/05(l). Springfield, ll...
Wendland, W.M., and Guinan, P. 1988. A Tornado and Severe Weather Climatology for llIinois: 1955-1986. Transactions of the llIinois Academy of Science 81(1&2): 131146.
Streamflow and Trends in Streamflow
Singh, K.P., G.S. Ramamurthy, and I.W. Seo. 1988. 7-Day 10-Year Low Flows of Streams in the Rock, Spoon, La Moine, and Kaskaskia Regions. llIinois State Water Survey Contract Report 440.
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1
Water Use and Availability
Dawes, J.R., and M.L. Terstriep. 1967. Potential Surface Water Reservoirs of Northern lllinois. lllinois State Water Survey Report of Investigation 58.
lllinois Department of Energy and Natural Resources. 1994. The Changing lllinois Environment: Critical Trends. Volume 2: Water Resources. llENRIRE-EA94/05(2). Springfield, IL.
lllinois Department of Agriculture and U.S. Department of Agriculture. 1996. lllinois Agricultural Statistics, 1996. llIinois Agricultural Statistics Service Bulletin 96-1. Springfield, IL.
Ground-Water Quality
Gibb, J.P. 1973. Water Quality and Treatment of Domestic Groundwater Supplies. llIinois State Water Survey Circular 118. Champaign, IL.
lllinois Department of Energy and Natural Resources. 1994. The Changing llIinois Environment: Critical Trends. Volume 2: Water Resources. llENRIRE-EA94/05(2). Springfield, IL.
Wilson, S.D., KJ. IDinka, J .M. Shafer, J.R. Kamy, and K.A. Panczak. 1992. "Agricultural Chemical Contamination of Shallow-Bored and Dug Wells." In Research on Agricultural Chemicals in lllinois Groundwater: Status and Future Directions II. Proceedings of the second annual conference lllinois Groundwater Consortium, Southern lllinois University, Carbondale, IL.
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