Calibration: Calibration was sensitive to lateral conductivity and exponential decay in soil conductivity. The sediment module of DHSVM 3.0 was sensitive to the grain size distribution of silt loam. Silt loam is the dominant soil (covering 95% of basin) and was the input of interest for sediment module calibration.

Validation: The model was validated over 1966-1984 using reconstructed streamflow (via the MOVE.2 method, Hirsch 1982). The top figure shows the comparison of reconstructed streamflow to measured streamflow for 2003-2006. The middle and bottom figures show the results of model validation for streamflow against USGS observations and sediment against Department of Environmental Quality samples.

Modeling the Impacts of Climate Change on Suspended Sediment and Erosion in a Dryland Agricultural Basin

Erika Ottenbreit a, Jennifer Adam a, Michael Barber a, Jan Boll b, and Jeffrey Ullman c

a Department of Civil and Environmental Engineering, Washington State University, b Department of Biological and Agricultural Engineering, University of Idaho, c Department of Biological Systems Engineering, Washington State University

INTRODUCTION

The objective of this study is to investigate the effects of climate change on suspended sediment concentrations in the Potlatch River basin. Suspended sediment is a pollutant in many water systems and contributes to impairment of streams. Certain cropping practices and rain-on-snow events in the Palouse region of northern Idaho and eastern Washington produce some of the highest sediment losses per acre in the United States. Climate change may lead to further problems if more frequent and intense storm events lead to a great amount of sediment generation.

Many hydrological models have been developed which examine suspended sediment in river systems. The Potlatch River basin near Julietta, ID was examined using Distributed Hydrology Soil Vegetation Model (DHSVM; [Wigmosta et al., 1994]). The model’s ability to quantify channel and soil surface erosion was used to model sediment yield. DHSVM was calibrated and evaluated over the historical period of streamflow observation and predicts results for the year 2045.

Model Parameterization

SUMMARYThe results show that as the projected climate-driven intensity of storms increase, more sediment is predicted in the Potlatch River.

Suspended sediment and streamflow are predicted to increase during the late fall through the early spring. This increase occurs during times of heightened runoff when suspended sediment concentration in the river is highest. Further analysis of increases in erosion and suspended sediment during high-intensity storm events under different climate and land use scenarios may be beneficial. In the long-term, this research can lead to examination of the effects of climate change on the riparian habitat of rainbow and steelhead trout in the Potlatch basin and the sediment budget of the surrounding area.

Acknowledgements: Funding provided by the Inland Northwest Research Alliance (INRA)References: Elsner, M., L. Cuo, N. Voisin, J. Deems, A. Hamlet, J. Vano, K. Mickelson, S. Lee, and D. Lettenmaier (2010), Implications of 21st century climate

change for the hydrology of Washington State, Climatic Change, 225-260.Hirsch, R. M., 1982: A comparison of 4 streamflow record extension techniques. Water Resources Research, 18, 1081-1088.Mote, P., and E. Salathe (2010), Future climate in the Pacific Northwest, Climatic Change, 29-50.Wigmosta, M.S., L.W. Vail, and D.P. Lettenmaier (1994), A distributed hydrology-vegetation model for complex terrain, Water Resour. Res., 30, 1665-

1669.

Global Climate Models

Calibration and Validation

Results

Methods

Storm Event: Historical and future streamflow simulations are shown for a typical winter event (below) and for the period of 1967-1983 (right).

Erosion: It is shown that most of the hillslope erosion occurs when the streamflow is within the upper 25% of daily flow volumes (bottom right).

Global Climate Models (GCMs) Nine GCMs were chosen to be run for the year 2045. They were chosen based on a model ranking for the Pacific Northwest [Mote and Salathé, 2010]. Both the GCMs were run for A1B and B1 emissions scenarios. The changes to mean monthly temperature and precipitation were analyzed for a 30 year period. The statistically downscaled future metrological data were derived by perturbing the historical record (Elsner et al. 2010). As a result, overlapping time periods can be compared directly and the climate change effect can be analyzed. Historical values are shown below as blue lines, while red lines are the mean of the future forcings.

• The model was calibrated for streamflow over the time period 08/15/2003 – 12/31/2006 using daily U.S. Geological Survey streamflow records for the Potlatch River. DHSVM 3.0 was run and for the time period 10/01/1970 – 10/01/1976 with identical hydrologic inputs to the calibrated model. The first two years were dedicated to spin-up.

• The sediment module was run with only Surface Erosion and Channel Routing as the sediment routing mechanisms.

• The inputs were on a 150 m grid over a 1520 km2 area. The inputs included soil, vegetation, a digital elevation model (DEM), a stream network file, a soil depth file, and forcing meteorological data.

DEM Soil Stream Network

Input Generation: •Vegetation was determined from Idaho GAP landcover data. • Soil was determined from SSURGO database. The mask determining the basin area was created using Watershed tools within ArcGIS.

• The stream network and soil depth grid were created with Arc commands from the DEM and mask file. The soil depth ranged from 0.5-2m.

• Daily gridded (to 1/16th degree) meteorological (MET) data (Elsner et al. 2010) were disaggregated to 3-hour time steps prior to inputting to the model.

Sediment Module: Inputs required for the Sediment Module include Manning’s n for all soil types, d50 & d90 sizes for debris flow and channel parent particles, parameters that determine cohesiveness, and a d50 for each soil type.

d50 Silt Loam: 0.055 mm d50 Loam: 0.206 mm d50 Cobbly Silt Loam: 0.303 mm d50 Debris Flow: 0.06 mm

Modeled stream network

Observed streams (ESRI’s TIGER lines)

1 2 3 4 5 6 7 8 9 10 11 120

20

40

60

80

100

120

140

160

180 Monthly Precipitation 1960-1990ccsm3_A1B

ccsm3_B1

cgcm3.1_t47_A1B

cgcm3.1_t47_B1

cnrm_cm3_A1B

cnrm_cm3_B1

echam5_A1B

echam5_B1

echo_g_A1B

echo_g_B1

hadcm_A1B

hadcm_B1

ipsl_cm4_A1B

ipsl_cm4_B1

miroc_3.2_A1B

miroc_3.2_B1

pcm1_A1B

pcm1_B1

GCM average

historical

Month

Mea

n M

onth

ly P

reci

pita

tion

(m

m)

1 2 3 4 5 6 7 8 9 10 11 12

-5

0

5

10

15

20

25

30

Mean Monthly Temperature 1960 -1990

Month

Mea

n M

onth

ly T

emp

(°C

)

Jul 2003 Jan 2004 Jul 2004 Jan 2005 Jul 2005 Jan 2006 Jul 2006 Jan 20070

1000

2000

3000

4000

5000

6000Calibrated Streamflow

OBS MODEL

Date

Flo

w (

cfs)

8 9 10 11 12 1 2 3 4 5 6 7-200

0

200

400

600

800

1000

1200

1400Average Monthly Flow 2003-2006MOVE.2 Poltatch

Month

Mon

thly

mea

n st

ream

flow

(cf

s)

Oct-01 Nov-01 Jan-02 Feb-02 Apr-02 Jun-02 Jul-02 Sep-020

5

10

15

20

25

30

35

40

Lower Reaches in Potlatch Basin (compared to select DEQ measurements)

DEQ

PotlatchGauge

PotlatchRiver

Date

SSC

(pp

m)

*Two DEQ mea-surements not shown (3/12/02 – 606 ppm and 4/15/02 – 131 ppm)

2/16/1968 2/18/1968 2/20/1968 2/22/1968 2/24/1968 2/26/1968 2/28/1968 3/1/1968 3/3/1968 3/5/19680

2

4

6

8

10

12

0

2

4

6

8

10

12

14

16

18

Storm Event 2/20/1968

historical streamflow GCM 2045 streamflow

historical sediment GCM 2045 sediment

Date

Stre

amfl

ow (

cfs)

Susp

ende

d Se

dim

ent

Con

cent

rati

on a

t M

outh

of

Riv

er (

ppm

)

9/28/1974 4/16/1975 11/2/1975 5/20/1976 12/6/1976 6/24/1977 1/10/19780

2

4

6

8

10

12

-3

-2.5

-2

-1.5

-1

-0.5

0Comparison of Hillslope Erosion and StreamflowModeled Streamflow25% ThresholdCumulative Hillslope Erosion

Date

Stre

amfl

ow (

cfs)

Cum

ulat

ive

Ave

rage

Hil

lslo

pe E

rosi

on

(mm

)

1967 1969 1971 1973 1975 1977 1979 1981 19830

100

200

300

400

500

600

700

800

Annual mean flows for GCMs ccsm_A1Bccsm_B1cgm3.1_t47_A1Bcgm3.1_t47_B1cnrm_cm3_B1cnrm_cm3_A1Becham5_A1Becham5_B1echo_g_B1echo_g_A1Bhadcm_A1Bhadcm_B1ipsl_cm4_A1Bipsl_cm4_B1miroc_3.2_A1Bmiroc_3.2_B1pcm1_A1Bpcm1_B1Historical FlowGCM Weighted Av-erage

Year

Ann

ual A

vera

ge S

trea

mfl

ow (

cfs)