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Effect of Soil Data on SWAT Modeling

Effect of Soil Data on SWAT Modeling. SSURGO, STATSGO, and SoLIM derived. Objectives:. Compare the accuracy of a SWAT hydrological model for the St. Joseph River Watershed using three soil datasets: SSURGO 2.2 STATSGO2 SoLIM derived soil map ( So il L and I nference M odel).

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Effect of Soil Data on SWAT Modeling

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  1. Effect of Soil Data on SWAT Modeling SSURGO, STATSGO, and SoLIM derived

  2. Objectives: Compare the accuracy of a SWAT hydrological model for the St. Joseph River Watershed using three soil datasets: • SSURGO 2.2 • STATSGO2 • SoLIM derived soil map (Soil Land Inference Model)

  3. St. Joseph River Watershed: • NE of Indiana, NW of Ohio, S of Michigan • HUC-8, 694,400 acres • 9 HUC-11 subwatersheds • NW boundary of Western Lake Erie Basin • Flows NE to SW • Rolling hills in Hillsdale, Williams, Noble, Steuben counties • Nearly flat plain in DeKalb and Allen counties • Parent material: dense glacial till • Texture: silt loam, silty clay loam, and clay loam • Udic moisture regime

  4. Data: • Watershed boundary • 1/3” NED • SSURGO 2.2 dataset • STATSGO2 dataset • Landuse/management data • Drainage network • Climatic data • Stream flow data • Soil scientist input

  5. Methodology: • Build the SoLIM soil map • Setup SWAT similarly for the 3 different models • Only difference is soil data • Will impact the number of HRUs and the soil parameters in each HRU • Run the three models, uncalibrated • Compare the streamflow output of each with actual • Expected results: • Increased accuracy from STATGO2 -> SSURGO 2.2 -> SoLIM

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