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Assessment of Flow Paths in Upland Areas and Vegetated Buffers

Assessment of Flow Paths in Upland Areas and Vegetated Buffers. ASAE Annual Meeting 2004. August 2, 2004 I.J. Kim, S.L. Hutchinson, and J.M.S. Hutchinson* The department of Biological and Agricultural Engineering *The department of Geography Kansas State University, Manhattan, KS.

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Assessment of Flow Paths in Upland Areas and Vegetated Buffers

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  1. Assessment of Flow Paths in Upland Areas and Vegetated Buffers ASAE Annual Meeting 2004 August 2, 2004 I.J. Kim, S.L. Hutchinson, and J.M.S. Hutchinson* The department of Biological and Agricultural Engineering *The department of Geography Kansas State University, Manhattan, KS

  2. Research Background (1) • Model assumption: • Uniform overland flow • Ex) WEPP, REMM, VFSMOD • Reality: • Concentrated surface runoff in fields • Dillaha, 1986 / Fabis et al, 1993 / Dosskey, 2002

  3. Research Background (2) • Digital elevation model (DEM) • Calculation of hydrological attributes • Slope, contour line, hill shade, aspect, etc • Flow path and length • LS factor • Delineating contributing area (e.g. watershed) • Risk assessment for landscape susceptibility • 30 m DEM widely used for GIS-Hydrologic model • Accessible data source (i.e., USGS 30m DEM) • Less costly

  4. Typical grid resolution in DEM High Cost and data storage

  5. Purposes of Study • Delineating flow path networks and drainage boundaries for hillside areas and vegetated buffers • Determining a suitable grid size for parameterizing model inputs at field scale site

  6. The study area: Fort Riley NE NIR Image Kansas River

  7. Buffer: brushes / trees Study Site Hillside: grass

  8. GPS Receiver Settings • Date: March 24th, 25th and April 14th 2004 • Base station for DC: Range Control Office Station, Ft. Riley • PDOP*: position dilution of precision • Accuracy: ± 50 cm • Vertical accuracy error • a vertical control point (KF0640) • root mean square error (RMSE)

  9. Elevation Data Collection

  10. Method for Creating DEM • TOPOGRID is essentially based on a discretised thin plate spline technique and an iterative finite difference interpolation.

  11. Limitations and Assumption • Accuracy of grid DEM is dependent on GPS accuracy • Becoming overland flow to channel flow is dependent on the contributing area (the number of cells)

  12. Drainage network delineation:Eight direction (D8) model N, 26 E, 20 W, 24 S, 22 • FILL / FLOWDIRECTION / FLOWACCUMULATION • Define flow paths from the specific accumulation area (# cell) • BASIN / FLOWLENGTH

  13. Hillside and Buffer Zone Data Points # of points: 2998 AVG PDOP: 2.68 Highest: 399.0 m Lowest: 382.5 m RMSE - 0.307 (XRS) - 0.526 (XR)

  14. Surface Elevation Variability 30m DEM USGS 30m DEM 10m DEM 3 m DEM

  15. Highest and Lowest Elevationat the Entire Areas and within the Buffers

  16. Flow Path and Catchment Area Boundary (CAB) 30m DEM USGS 30m DEM 10m DEM 3 m DEM

  17. Longest Flow Length & CAB *Flow length is the longest in the catchment boundary

  18. Flow Path and CAB (3 m DEM) TH:90m2 TH:9m2 TH:450m2 TH:900m2

  19. Conclusions • 30m resolution should be avoided for determining flow paths, especially in the buffer areas • Grid size significantly influences flow direction, catchment area shape, and surface terrain complexity on the hillside and buffer areas. • 3m DEM provides the most detailed flow paths and catchment area boundaries • 90m2 (10 cells) in 3m DEM required for flow path delineation with in the buffer

  20. Future Studies,,, • Applying larger resolution (e.g. 1m DEM) to the area and/or Ft. Riley • Applying advanced method to the flow direction • Evaluating effects of the flow length to hydrologic responses in a model

  21. Acknowledgements • The Strategic Environmental Research Development Program (SERDP) • Kansas State University Agricultural Experiment Station

  22. Questions and Comments?

  23. Buffer: brushes / trees Study Site Hillside: grass

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