Effect of soil data on swat modeling
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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

Effect of Soil Data on SWAT Modeling

SSURGO, STATSGO, and SoLIM derived


Objectives
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)


St joseph river watershed
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


Effect of soil data on swat modeling
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


Methodology
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