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ARS Home » Northeast Area » University Park, Pennsylvania » Pasture Systems & Watershed Management Research » Research » Publications at this Location » Publication #221807

Title: Improving daily water yield estimates in the Little River Watershed: SWAT adjustments

item Feyereisen, Gary
item Veith, Tameria - Tamie
item Bosch, David - Dave

Submitted to: Transactions of the ASABE
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 2/18/2009
Publication Date: 2/18/2009
Citation: White, E.D., Feyereisen, G.W., Veith, T.L., Bosch, D.D. 2009. Improving daily water yield estimates in the Little River Watershed: SWAT adjustments. Transactions of the ASABE. 52(1):69-79.

Interpretive Summary: Because there was a substantial increase in funding for conservation programs in the 2002 Farm Bill, Congress and stakeholders in the agricultural community have become increasingly interested in quantifying the benefits of conservation practices. The USDA Natural Resources Conservation Service (NRCS) and USDA Agricultural Research Service (ARS) have chosen to analyze the effects of conservation practices on watershed hydrology and water quality with computer simulation models that mathematically represent natural watershed processes. Water quality estimates are highly influenced by water quantity estimates. We studied various approaches to improve the daily streamflow estimates for the Little River Experimental Watershed (LREW) in South Georgia. The simulation model we used was the Soil and Water Assessment Tool (SWAT), which has been developed by the ARS and has been widely applied to agricultural landscapes. SWAT uses the USDA-NRCS curve number (CN) method to calculate daily storm runoff based upon daily precipitation, land use, and soil-cover complex. Because previous field plot work near the LREW indicated that CNs are different for the growing versus dormant seasons, we hypothesized that changing SWAT to reflect these differences would improve daily water yield estimates. The results showed there was only a slight improvement, based upon a commonly-used comparison statistic, the Nash-Sutcliffe efficiency. Through subsequent work we found that adjusting the SWAT input parameter that affects the lag time of the storm runoff peak had the largest improvement. Using an initial abstraction ratio from 0.2 to 0.05S in the NRCS CN equation, where S represents the maximum retention of the soil at the beginning of runoff, had the next largest improvement of the five changes that were studied. The combined changes made to SWAT improved the Nash-Sutcliffe efficiency from 0.42 to 0.66 for daily water yield for the 16.9 km2 subwatershed K of the LREW. Although improvements were made for each year of the ten-year study period (1995-2004), SWAT continued to overpredict streamflow after long dry periods and large seasonal storms, and SWAT underpredicted streamflow during wetter periods.

Technical Abstract: Researchers are assessing the beneficial effects of conservation practices on water quality with hydrologic models. The assessments depend heavily on accurate simulation 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 (LREW) in South Georgia. 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 low-lying riparian zones. Refinements were made to two SWAT input parameters, SURLAG and ALPHA_BF, from a previous set of calibration parameters. The combined changes improved the daily Nash-Sutcliffe model efficiency (NSE) from 0.42 to 0.66 for water yield at the outlet of the 16.9 km2 subwatershed K of the LREW for the ten-year period 1995 – 2004. Further calibration of the SURLAG coefficient affected the largest improvement of the five alterations and changing Ia affected the next largest improvement. Over the 10-year investigation period, the model predicted annual average water yield within 1% of measured streamflow and deviation between observed and simulated values for stormflow was less than or equal to 2.2%. Annual daily NSEs for each of the ten years were improved; for two years marked by seasonal tropical storm events, NSEs changed from negative to positive values. The results of this study support the adjustment of the Ia ratio in the runoff curve number and suggest that additional changes to SWAT would improve water yield prediction for southern Coastal Plain locations.