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The SWAT Model Mauro Di Luzio, TAES-BREC Blackland Research and Extension Center, Temple, TX Jeff Arnold, USDA-ARS Grassland Research and Extension Center,

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Presentation on theme: "The SWAT Model Mauro Di Luzio, TAES-BREC Blackland Research and Extension Center, Temple, TX Jeff Arnold, USDA-ARS Grassland Research and Extension Center,"— Presentation transcript:

1 The SWAT Model Mauro Di Luzio, TAES-BREC Blackland Research and Extension Center, Temple, TX Jeff Arnold, USDA-ARS Grassland Research and Extension Center, Temple, TX Jerry Whittaker, USDA-ARS National Forage Seed Production Research Center, Corvallis, OR Rem Confesor, Oregon State University National Forage Seed Production Research Center, Corvallis, OR The Distributed Model Intercomparison Project (DMIP-2) Workshop Hydrology Laboratory National Weather Service September 10-12, 2007 Silver Spring, MD ARS

2 Soil and Water Assessment Tool Arnold et al. (1998) SWAT is a product of over 30 years of USDA model development History Time Line CREAMS USLE (CLEAN WATER ACT) EPIC SWRRB SWAT 1960’s 1970’s 1980’s 1990’s GLEAMS WEPP ANN AGNPS AGNPS

3  Partnership – Texas A&M, ARS, EPA, NRCS Developing models, GIS, databases, applications  Worldwide User Community  Widely used for water quality

4 TMDL Applications  Bosque River – Dairy Waste, Agriculture Range, Treatment Plants  Wisconsin – Nitrogen and Phosphorus  Texas – Atrazine  Missouri – Atrazine  Oklahoma – Nutrients  Nehalem River – OR  Cannonsville Reservoir – NY  ………….

5 Conservation Effects Assessment Project C.E.A.P.—the acronym

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7 SWAT River Basin Model River Routing and Non-Cultivated Lands CEAP National

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9 Channel routing: Muskingum routing method.

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11 Di Luzio et al., 2004

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15 Used Data DEM1 arc-second (30 m) USGS NED LandUse/Land CoverNLCD 1992 ( National Land Cover Dataset) (30 m)21 classes Soil Map STATSGO (State Soil Geographic) 1:250,000-scale HydrographyNHD ( National Hydrography Dataset) Precipitation NEXRAD DMIP2 (Hourly Time Step) TemperatureNCDC Cooperative Network (daily)

16 Elk River (119) Baron Fork (41) Illinois River (129, 78) Blue River (55)

17 The Blue River near Blue, Oklahoma (1,233 Square Km) DMIP1

18 Single objective measure: sum of square of the residuals (SSQ). Optimization algorithm: Shuffled Complex Evolution Method (SCE) (Duan, 1991; Sorooshian et al., 1993). Automatic Calibration DMIP1

19 Event 2, November 12–27, 1994 Event 6, September 17 – 24, 1995 Event 7, September 26–October 11, 1996 Event 9, November 6–21, 1996 DMIP1

20 Optimization of Multiple Objectives Objective 2 Objective 1 * * * * * * * * *

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23 24 Pentium 4 processors (2.4 GHz) 1 GB of RAM,– 12 with hyperthreading technology 24 port, 1 gigabit/second ethernet switch Integrated INTEL 10/100/1000 Mbps network interface card 24 ports - KVM switches Linux, Fedora Core2, kernel version 2.6.5smp NFSPRC Beowulf Cluster

24 Tahlequa9,228 40 variables, 129 sub-basins, 419 HRU Blue4,198 Baron3,422 Elk7,946 Illinois4,893 Number of calibration parameters

25 Thanks! Questions?


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