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Re-conceptualizing SWAT for Variable Source Area Hydrology

Re-conceptualizing SWAT for Variable Source Area Hydrology. Zachary Easton 1* , Daniel Fuka 1 , Todd Walter 1 , Dillon Cowan 2 , Elliot Schneiderman 3 , Tammo Steenhuis 1 1 Dept. Biological and Environmental Engineering, Cornell University

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Re-conceptualizing SWAT for Variable Source Area Hydrology

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  1. Re-conceptualizing SWAT for Variable Source Area Hydrology Zachary Easton1*, Daniel Fuka1, Todd Walter1, Dillon Cowan2, Elliot Schneiderman3, Tammo Steenhuis1 1Dept. Biological and Environmental Engineering, Cornell University 2School of Civil and Environmental Engineering, Cornell University 3New York City Dept. Environmental Protection, Kingston, NY *zme2@cornell.edu

  2. Re-conceptualizing SWAT • Variable Source Area (VSA) Hydrology • Curve Number and VSA hydrology • Convincing SWAT it recognizes VSAs

  3. Infiltration “Runoff” Common Perception of Runoff Rain Infiltration Excess a.k.a. Hortonian Flow (Horton 1933, 1940)

  4. NewYork 100 90 80 June 70 60 May September July 50 % of Area Generating Hortonian Flow 40 August 30 20 October April 10 November 0 March 1 10 100 Return Period (yr) Is Hortonian Flow Common? Walter et al. 2003. ASCE J. Hydrol. Eng. 8: 214-218

  5. Rain Subsurface water rises Some areas saturate to the surface Saturation Excess Runoff

  6. Rain Upland interflow may exfiltrate Saturation Excess Runoff Rain on saturated areas becomes overland flow Dunne and Black. 1970. Water Resour. Res. 6: 478-490 Dunne and Black. 1970. Water Resour. Res. 6: 1296-1311

  7. Flow Path Variable Source Areas • Current Water Quality Models were not Intended to Capture this Complexity • General Watershed Loading Function (GWLF) • Soil Water Assessment Tool (SWAT) • Agricultural Nonpoint Source Pollution Model (AGNPS)

  8. Re-conceptualizing SWAT • Variable Source Area (VSA) Hydrology • Curve Number and VSA hydrology • Convincing SWAT it recognizes VSAs

  9. USDA-NRCS Curve Number Model “Runoff”=Pe2/(Pe+S) S=25400/CN-254 Tables link CN to land use and soil infiltration capacity

  10. Curve Numbering VSA hydrology P Q = Pe2/(Pe+S) Watershed Q Af DQ = AfDPe Unsaturated Saturated dQ/dPe = Af Af = f(S,Pe) Steenhuis et al. 1995. ASCE Div Drain. & Irr. 121:234-238

  11. We know how much area is contributing… Af = f(S,Pe) …but from where in the landscape?

  12. Soil Topographic IndexWetness Index Classes Soil Topographic Index Wetness Index Classes s8=f(S) 10 s7=f(S) 33.10 3.52 s9=f(S) s10=f(S) 1 s1=f(S) si = local storage s6=f(S) s2=f(S) s5=f(S) s3=f(S) Easton et al., 2008. J. Hydrol. 348: 279-291. Lyon et al. 2004. Hydrol. Proc. 18(15): 2757-2771. Schneiderman et al. 2007. Hydrol. Proc. 21: 3420-3430. s4=f(S)

  13. Re-conceptualizing SWAT • Variable Source Area (VSA) Hydrology • Curve Number and VSA hydrology • Convincing SWAT it recognizes VSAs

  14. Revisit the HRU concept • Define HRUs as the coincidence of soil type and landuse • Hydrological/chemical properties are defined at the HRU • So runoff/P loss is the same here (lowland pasture) • As here (upland pasture) • Is this a good assumption? Landuse Soils HRUs

  15. VSA concept defines HRUs as the coincidence of soil topographic index and landuse • So runoff/P loss is now not the same here (lowland pasture) • As here (upland pasture) • Better Assumption? STI Landuse SSURGO HRUs

  16. Distributing CN-values • Average of Standard CNs = 73.1 distributed according to landuse/soils • Average of VSA CNs = 73.1, distributed according to a wetness index Wetness Index Classes 10 1

  17. Modify the Available Water Content • High runoff prone area = high moisture content (in general) • We relate local soil water storage, e,i, to AWC with the following: • ρb = soil bulk density (g cm-3) • clay = soil clay content (cm3 cm-3). Wetness Class 10 Wetness Class 9 Wetness Class 2 Wetness Class 1

  18. Test Results: Streamflow r2= 0.76 E = 0.82 r2 = 0.74 E = 0.83 -Standard

  19. Test Results: Runoff from Pastures SWAT-VSA SWAT-Standard Easton et al., 2008. J. Hydrol. 348: 279-291

  20. Test Results: Runoff SWAT-VSA SWAT-Standard Easton et al., 2008. J. Hydrol. 348: 279-291

  21. Test Results: Soil water SWAT-VSA SWAT-Standard Easton et al., 2008. J. Hydrol. 348: 279-291

  22. N 0 100 m Data curtsey of : Lyon et al. 2006. Adv. Water Resour. 29(2): 181-193. Lyon et al. 2006. HESS. 10: 113-125. Wetness Index Classes Test Results: Soil Water 10 1 585 m 1m Cont. Water Level Loggers 600 m

  23. SWAT-VSA Movie courtesy of Dr. Steve Lyon

  24. Test Results: Soil water a b Index Easton et al., 2008. J. Hydrol. 348: 279-291

  25. Test Results: Phosphorus a r2 = 0.76 E = 0.71 b -Standard r2 = 0.68 E = 0.47

  26. Test Results: Phosphorus SWAT-VSA SWAT-Standard

  27. Take-home Messages • Storm runoff is generated from small parts of the landscape • Areas prone to saturate – e.g., toe slopes, shallow soils, topographically converging areas • Variable Source Areas – they expand and contract • We can predict where and when storm runoff will be generated • We can improve integrated and distributed predictions by considering VSAs • Implications for watershed management

  28. Curve Numbering VSA hydrology Q = Pe2/(Pe+S) P Af = dQ/dPe Watershed Af = 1-(S2/(Pe+S)2 Q Af As= 1-(S2/(σe+S)2 Unsaturated Saturated σe=S(√(1/(1-As))-1 Af = f(S,Pe) Steenhuis et al. 1995. ASCE Div Drain. & Irr. 121:234-238

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