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ARS Home » Northeast Area » University Park, Pennsylvania » Pasture Systems & Watershed Management Research » Research » Publications at this Location » Publication #217439
Title: Improving daily water yield in the Little River Experimental Watershed: SWAT adjustments

Author
item WHITE, ERIC - CORNELL UNIV
item Feyereisen, Gary
item Veith, Tameria - Tamie
item Bosch, David - Dave

Submitted to: Proceedings of the American Society of Agricultural and Biological Engineers International (ASABE)
Publication Type: Proceedings
Publication Acceptance Date: 12/3/2007
Publication Date: 7/1/2008
Citation: White, E., Feyereisen, G.W., Veith, T.L., Bosch, D.D. 2008. Improving daily water yield in the Little River Experimental Watershed: SWAT adjustments.Proceedings of the American Society of Agricultural and Biological Engineers Annual International Meeeting. Providence, RI. Paper No. 084257.

Interpretive Summary: An interpretive summary is not required.

Technical Abstract: Hydrologic models are being used to evaluate watershed scale water quantity and quality impacts of land cover, land use, and climate change. Water quality estimates depend heavily on accurate assessment of water yield. This study was conducted to improve Soil and Water Assessment Tool (SWAT) hydrologic model daily water yield estimates in the Little River Experimental Watershed in South Georgia. Refinements were made to two SWAT input parameters from a previous set of calibration parameters, SURLAG, and ALPHA_BF. The SWAT code was altered to recognize a difference in curve number between growing and dormant seasons, to use an initial abstraction, Ia, of 0.05 S rather than 0.2 S, and to adjust curve number based upon the level of soil saturation in riparian zones in low-lying areas. The combined changes improved the daily Nash-Sutcliffe model efficiency (NSE) from 0.42 to 0.66. Further calibration of the SURLAG coefficient effected the greatest improvement of the five alterations and changing the Ia was next greatest. Over the 10-year investigation period, the model predicted annual average water yield within 1% and deviation between observed and simulated values for stormflow was less than or equal to 2.2%. Daily NSEs for all ten years were improved; for two years affected by seasonal tropical storm events, NSEs were changed from negative to positive values. The results of this study support the adjustment of the Ia ratio in the runoff curve number and show that additional changes to SWAT are needed to address overprediction of water yield for large events and underprediction of water yield during wet seasons.