WEPP—A Process-Based Hydrology and Erosion Model for Watershed Assessment and Restoration
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Transcript of WEPP—A Process-Based Hydrology and Erosion Model for Watershed Assessment and Restoration
WEPP—A Process-Based Hydrology WEPP—A Process-Based Hydrology and Erosion Model for Watershed and Erosion Model for Watershed
Assessment and RestorationAssessment and Restoration
Joan Q. Wu, Markus Flury, Shuhui Dun, R. Cory GreerJoan Q. Wu, Markus Flury, Shuhui Dun, R. Cory GreerWashington State University, Pullman, WAWashington State University, Pullman, WA
Donald K. McCoolDonald K. McCoolUSDA ARS PWA, Pullman, WAUSDA ARS PWA, Pullman, WA
William J. ElliotWilliam J. ElliotUSDA FS RMRS, Moscow, IDUSDA FS RMRS, Moscow, ID
Dennis C. FlanaganDennis C. FlanaganUSDA ARS NSERL, West Lafayette, INUSDA ARS NSERL, West Lafayette, IN
Major Funding AgenciesMajor Funding Agencies
USDA National Research Initiatives (NRI) Programs
US Forest Service Rocky Mountain Research Station (RMRS)
US Geological Survey/State of Washington Water Research Center
In-house funding from various collaborating research In-house funding from various collaborating research institutesinstitutes
The NeedsThe Needs
Protecting and improving water quality in agricultural watersheds are major goals of the USDA NWQ and NRI Programs
For many watersheds, sediment is the greatest pollutant
In watershed assessment, it is crucial to understand sedimentation processes and their impacts on water quality
To successfully implement erosion control practices, it is necessary to determine the spatiotemporal distribution of sediment sources and potential long-term effectiveness of sediment reduction by these practices
Surface runoff and erosion from undisturbed forests are negligible
Stream formed due to subsurface flow has low sediment
Both surface runoff and erosion can increase dramatically due to disturbances
Models are needed as a tool for forest resource management
The WEPP ModelThe WEPP Model
WEPP: Water Erosion Prediction Project
a process-based erosion prediction model developed by the USDA ARS
built on fundamentals of hydrology, plant science, hydraulics, and erosion mechanics
WEPP’s unique advantage: it models watershed-scale spatial and temporal distributions of soil detachment and deposition on event or continuous basis
Equipped with a geospatial processing interface, WEPP has great potential as a reliable and efficient tool for watershed assessment
The WEPP Model cont’d
WEPP Windows Interface
WEPP Internet Interface
GeoWEPP
Long-term Research EffortsLong-term Research Efforts
Goal Continuously refine and apply the WEPP model for watershed
assessment and restoration under different land-use, climatic and hydrologic conditions
Objectives Improve the subsurface hydrology routines so that WEPP can be
used under both infiltration-excess and saturation-excess runoff conditions in crop-, range- and forestlands
Improve the winter hydrology and erosion routines through combined experimentation and modeling so that WEPP can be used for quantifying water erosion in the US PNW and other areas where winter hydrology is important
Continually test the suitability of WEPP using data available from different localities across the world
ProgressesProgresses
Numerous modifications to WEPP have been made to Correct the hydraulic structure routines
Improve the water balance algorithms
Incorporate the Penman-Monteith ET method (FAO standard)
Improve the subsurface runoff routines
Expand and improve winter hydrology routines to better simulate
Freeze-thaw processes
Snow redistribution processes
WEPP newest release accessible at NSERL’s website http://topsoil.nserl.purdue.edu/nserlweb/index.html
Comparison of ProcessesComparison of Processes
* Previous version of WEPP typically overestimated Dp
RedistributionRedistributionof Infiltration Water in WEPPof Infiltration Water in WEPP
E v a p o ra tio na n d
T ra n sp ira tio n
D e e pP e rc o la tio n
S u b su rfa c eL a te ra l
F lo w
In filtra ted W a ter
22 3311
Code ModificationCode Modification
Provide options for different applicationsProvide options for different applications a flag added to the soil input filea flag added to the soil input file
User-specified vertical hydraulic conductivity User-specified vertical hydraulic conductivity KK for the added restrictive layerfor the added restrictive layer
e.g., 0.005 mm/hre.g., 0.005 mm/hr basalt (basalt (Domenico and SchwartzDomenico and Schwartz, 1998), 1998)
User-specified anisotropy ratio for soil saturated User-specified anisotropy ratio for soil saturated hydraulic conductivityhydraulic conductivity
horizontal horizontal KKh h vertical vertical KKvv, e.g., K, e.g., Khh/K/Kvv = 25= 25
Code ModificationCode Modification cont’dcont’d
Subroutines modified to properly Subroutines modified to properly write the “pass” fileswrite the “pass” files
WEPP’s approach to passing outputsWEPP’s approach to passing outputs subsurface flow not “passed” previouslysubsurface flow not “passed” previously
Simplified hillslope-channel relationSimplified hillslope-channel relation all subsurface runoff from hillslopes assumed to all subsurface runoff from hillslopes assumed to
enter the channelenter the channel flow added and sediment neglectedflow added and sediment neglected
A Case Application:Modeling Forest Runoff and Erosion
Study Site: Hermada WatershedStudy Site: Hermada Watershed
Physical SettingPhysical Setting Located in the Boise National Forest, SE Lowman, ID
Instrumented during 1995−2000 to collect whether, runoff, and erosion data
5-yr observed data showing an average annual precipitation of 860 mm, among which nearly 20% was runoff
Temperature
-60
-40
-20
0
20
40
60
0 200 400 600 800 1000 1200 1400 1600 1800 2000 2200
days
Tem
pera
ture
, c
Tmax
Tmin
Tdew
Precipitation
0
10
20
30
40
50
60
70
1 55 109
163
217
271
325
379
433
487
541
595
649
703
757
811
865
919
973
1027
1081
1135
1189
1243
1297
1351
1405
1459
1513
1567
1621
1675
1729
1783
1837
1891
1945
1999
2053
2107
2161
days
Pre
cipi
tatio
n,m
m
Watershed DiscretizationWatershed Discretization
Model InputsModel Inputs
TopographyTopography Derived from 30-m DEMs using GeoWEPPDerived from 30-m DEMs using GeoWEPP 10-ha in area, 3 hillslopes and 1 channel10-ha in area, 3 hillslopes and 1 channel 40−60% slope40−60% slope
SoilSoil Typic Cryumbrept loamy sand 500 mm in depthTypic Cryumbrept loamy sand 500 mm in depth
underlying weathered graniteunderlying weathered granite
ManagementManagement 1992 cable-yarding harvest1992 cable-yarding harvest 1995 prescribed fire on W and N slopes1995 prescribed fire on W and N slopes
ClimateClimate 11/1995−09/2000 observed data11/1995−09/2000 observed data
Results
Living Biomass and Ground Cover
(a)
1995 1996 1997 1998 1999 2000
Liv
ing
Bio
mas
s k
g m
-2
0
1
2
3
4
5
(b)
Year
1995 1996 1997 1998 1999 2000
Liv
ing
Bio
mas
s k
g m
-2
0
1
2
3
4
5
(a)
1995 1996 1997 1998 1999 2000
Gro
un
d C
ove
r
0.85
0.90
0.95
1.00
(b)
Year
1995 1996 1997 1998 1999 2000
Gro
un
d C
ove
r
0.85
0.90
0.95
1.00
PredictedObserved
* (a) unburned, (b) burned
Runoff and Erosion: Obs vs PreRunoff and Erosion: Obs vs Pre
* Observation Period: 11/3/1995−9/30/2000
Water Year
Precipitation (mm)
Observed Watershed Discharge
(mm)
Observed Sediment
(t/ha)
Simulated Hillslope Runoff (mm)
Simulated Hillslope
Lateral Flow (mm)
Simulated Watershed Discharge
(mm)
Simulated Watershed Sediment
(t/ha)1995–1996 966 87 0 0 436 433 0.11996–1997 884 89 0 0 253 250 01997–1998 1085 322 0 28 288 313 01998–1999 690 172 0 0 164 162 01999–2000 689 142 0 0 150 147 0
Average 863 162 0 7 258 261 0.0
(b)
Month
M J S D M J S D M J S D M J S D M J S D M J S
Ob
serv
ed R
un
off
, mm
0
2
4
6
8
10
12
(a)
M J S D M J S D M J S D M J S D M J S D M J S
Pre
dic
ted
Ru
no
ff, m
m
0
2
4
6
8
10
12 Cu
mu
lative P &
RM
, mm0
200
400
600
800
1000
1200
Runoff Cum. P Cum. RM
(b)
Month
O N D J F M A M J J A S
Ob
serv
ed
Ru
no
ff, m
m
0
2
4
6
8
10
12
Prec
ipita
tion
, mm
0
20
40
60
80
100
(a)
O N D J F M A M J J A S
Pre
dic
ted
Ru
no
ff, m
m
0
2
4
6
8
10
12 Cu
mu
lative P &
RM
, mm0
200
400
600
800
1000
1200
Runoff Cum. P Cum. RM
Water year 1997–1998
SummarySummary
Modifications were made in the approach to, and algorithms for modeling deep percolation of soil water and subsurface lateral flow
The refined model has the ability to more properly partition infiltration water between deep percolation and subsurface lateral flow
For the Hermada forest watershed Vegetation growth and ground cover were described realistically
WEPP-simulated watershed discharge for 1998–2000 was compatible with field observation; however, the agreement was poor for first two years
Overall, predicted annual watershed discharge and sediment yield were not significantly different from the observed (paired t-test)
Nash-Sutcliffe model efficiency coefficient for daily runoff was –1.7, suggesting improvement needed
Ongoing Efforts
Palouse Conservation Field Station Palouse Conservation Field Station (PCFS), Pullman, WA, USA(PCFS), Pullman, WA, USA
Laboratory and field experimentation on runoff and erosion as affected by freezing and thawing of soils
Tilting flume at PCFS
Experimental plots at PCFS
Collaborating Research UnitsCollaborating Research Units Testing WEPP using data collected at
USDA ARS CPCRC, Pendleton, OR, USA (Dr. John Williams) Ag Exp Farm, University of Bologna, Italy (Dr. Paola Rossi Pisa)
Other PNW Watersheds Testing and applying WEPP for evaluating DEM effect on
soil erosion prediction Paradise Creek Watershed, ID, USA (Dr. Jan Boll) Mica Creek Watershed, ID, USA (Dr. Tim Link)
Thank You!
Questions?
Important Parameters
Parameters Values
Surface Soil Effective K, mm/hr
16.6
Bedrock K, mm/hr 1.0E−2
Anisotropy Ratio 25