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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
slide4
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
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