Water Erosion Research Water Erosion Research at Washington State at Washington State University University Joan Wu, Markus Flury, Shuhui Dun, Cory Greer, Prabhakar Joan Wu, Markus Flury, Shuhui Dun, Cory Greer, Prabhakar Singh Singh Washington State University, Pullman, WA Washington State University, Pullman, WA Don McCool Don McCool USDA ARS PWA, Pullman, WA USDA ARS PWA, Pullman, WA Bill Elliot Bill Elliot USDA FS RMRS, Moscow, ID USDA FS RMRS, Moscow, ID Dennis Flanagan Dennis Flanagan USDA ARS NSERL, West Lafayette, IN USDA ARS NSERL, West Lafayette, IN
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Water Erosion Research at Washington State University
Water Erosion Research at Washington State University. Joan Wu, Markus Flury, Shuhui Dun, Cory Greer, Prabhakar Singh Washington State University, Pullman, WA Don McCool USDA ARS PWA, Pullman, WA Bill Elliot USDA FS RMRS, Moscow, ID Dennis Flanagan USDA ARS NSERL, West Lafayette, IN. - PowerPoint PPT Presentation
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Water Erosion ResearchWater Erosion Researchat Washington State Universityat Washington State University
Joan Wu, Markus Flury, Shuhui Dun, Cory Greer, Prabhakar SinghJoan Wu, Markus Flury, Shuhui Dun, Cory Greer, Prabhakar Singh
Washington State University, Pullman, WAWashington State University, Pullman, WA
Don McCoolDon McCool
USDA ARS PWA, Pullman, WAUSDA ARS PWA, Pullman, WA
Bill ElliotBill Elliot
USDA FS RMRS, Moscow, IDUSDA FS RMRS, Moscow, ID
Dennis FlanaganDennis Flanagan
USDA ARS NSERL, West Lafayette, INUSDA ARS NSERL, West Lafayette, IN
Major Funding SourcesMajor Funding Sources
In-house funding from various collaborating research institutes
US Forest Service Rocky Mountain Research Station
Inland Northwest Research Alliance
USDA National Research Initiatives Programs
US Geological Survey/State of Washington Water Research Center
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 spatio-temporal 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 to replace the functional model USLE
built on fundamentals of hydrology, plant science, hydraulics, and erosion mechanics
WEPP uses observed or stochastically-generated climate inputs to predict spatial and temporal distributions of soil detachment and deposition on an event or continuous basis, along a hillslope or across a watershed
Equipped with a geospatial processing interface, WEPP is a promising tool in watershed assessment and management
The WEPP Model cont’d
WEPP Windows Interface
WEPP Internet Interface
GeoWEPP
Long-term Research EffortsLong-term Research Efforts
Goal Continuously develop, 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 cold regions where winter hydrology is important
Continually test the suitability of WEPP using data available from different localities within and outside the US
Progresses MadeProgresses Made
Numerous modifications to WEPP have been made to Correct the hydraulic structure routines
Improve the water balance algorithms
Incorporate the Penman-Monteith ET method (UN FAO standard)
Improve the subsurface runoff routines
Expand and improve winter hydrology routines to better simulate
Freeze-thaw processes
Snow redistribution processes
WEPP new releases accessible at NSERL’s website http://topsoil.nserl.purdue.edu/nserlweb/index.html
Palouse Conservation Field Station Palouse Conservation Field Station (PCFS), Pullman, WA(PCFS), Pullman, WA
Laboratory and field experimentation on runoff and erosion as affected by freezing and thawing of soils
Tilting flume at PCFS
Experimental plots at PCFS
WEPP Applications at UB, Italy Experimental Watershed, University of Bologna,
Italy (Drs. Paola Rossi Pisa and Marco Bittelli) Joint MS program providing source of studentsJoint MS program providing source of students State-of-the-science research facilityState-of-the-science research facility
DEM Effects on WEPPErosion Modeling
Paradise Creek Watershed, ID (Dr. Jane Zhang)
WEPP Applicationsfor Watershed Erosion Modeling
Reeder Experimental Watershed at the USDA ARS CPCRC, Pendleton, OR (Dr. John Williams)
Paradise Creek Watershed, ID (Drs. Jan Boll and Erin Brooks)
Mica Creek Watershed, ID (Dr. Tim Link)
Long-term Research EffortsLong-term Research Efforts
Goal Continuously develop, 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 cold regions where winter hydrology is important
Continually test the suitability of WEPP using data available from different localities within and outside the US
Comparison of ProcessesComparison of Processes
* Earlier versions 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 layer for the added restrictive layer
e.g., 0.005 mm/hre.g., 0.005 mm/hr
User-specified anisotropy ratio for soil User-specified anisotropy ratio for soil saturated hydraulic conductivitysaturated hydraulic conductivity
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
West and North slopes with low-severity burnWest and North slopes with low-severity burn South slope and channel unburnedSouth slope and channel unburned
ClimateClimate 11/1995−09/2000 observed data11/1995−09/2000 observed data
Results
Living Biomass and Ground Cover(WEPP v2004.7)
* (a) and (b) unburned S slope; (c) and (d) burned W slope
(a)
Liv
ing
Bio
mas
s (k
g m
-2)
0
1
2
3
4
5
(c)
O J A J O J A J O J A J O J A J O J A J O
Liv
ing
Bio
mas
s (k
g m
-2)
0
1
2
3
4
5
(b)
Gro
un
d C
ove
r (%
)
70
80
90
100
(d)
O J A J O J A J O J A J O J A J O J A J O
Gro
un
d C
ove
r (%
)
70
80
90
100
PredictedObserved
1996 1997 1998 1999 2000 1996 1997 1998 1999 2000
* (a) and (b) unburned S slope; (c) and (d) burned W slope
Living Biomass and Ground Cover(WEPP v2006.5)
(a)
Liv
ing
Bio
mas
s (k
g m
-2)
0
1
2
3
4
5
(c)
O J A J O J A J O J A J O J A J O J A J O
Liv
ing
Bio
mas
s (k
g m
-2)
0
1
2
3
4
5
(b)
Gro
un
d C
ove
r (%
)
70
80
90
100
(d)
O J A J O J A J O J A J O J A J O J A J O
Gro
un
d C
ove
r (%
)
70
80
90
100
PredictedObserved
1996 1997 1998 1999 2000 1996 1997 1998 1999 2000
Runoff and Erosion: Obs. vs Pre.Runoff and Erosion: Obs. vs Pre.(WEPP v2004.7)(WEPP v2004.7)
SummarySummary Numerous modifications have been incorporated into
WEPP v2006.5
Specifically, changes 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 annual watershed discharge was compatible with field observation; and predicted annual sediment yield was not significantly different from the observed
Nash-Sutcliffe model efficiency coefficient for daily runoff of −0.77 suggests further improvement on winter routines are needed