U.S. Department of Agriculture: Agricultural Research Service, Lincoln, Nebraska

 

Date of this Version

2007

Comments

Published in Journal of Hydrologic Engineering, Vol. 12, No. 6, November 1, 2007.

Abstract

Based on recent reviews of 11 physically based watershed models, the long-term continuous model soil and water assessment tool (SWAT) and the storm event dynamic watershed simulation model (DWSM) were selected to examine their hydrologic formulations, calibrate, and validate them on the 620 km2 watershed of the upper Little Wabash River at Effingham, Ill., and examine their compatibility and benefits of combining them into a more comprehensive and efficient model. Calibration and validation of the SWAT by comparing monthly simulated and observed flows and adjusting the model-assigned resulted in coefficients of determination and Nash–Sutcliffe coefficients for individual years and cumulatively for the calibration period (1995–1999) and for the entire simulation period (1995–2002) mostly above or near 0.50 with an exception of 0.05 and −0.27, respectively, in 2001, relatively a dry year. Visual comparisons of the hydrographs showed SWAT’s weakness in predicting monthly peak flows (mostly underpredictions.) Therefore, SWAT needs enhancements in storm event simulations for improving its high and peak flow predictions. Calibration of DWSM was not necessary; its three physically based parameters were taken from SWAT. Validation of DWSM on three intense storms in May 1995, March 1995, and May 2002 resulted 1, −29, and 16% errors in peak flows and 0, −11, and 0% errors in times to peak flows, respectively. Comparisons of DWSM’s 15-min flow hydrographs with SWAT’s daily flow hydrographs along with the 15-min and daily observed flow hydrographs during the above three storms confirmed that DWSM predicted more accurate high and peak flows and precise arrival times than SWAT. DWSM’s robust routing scheme using analytical and approximate shock-fitting solutions of the kinematic wave equations was responsible for the better predictions, the addition of which along with its unique combination with the popular runoff curve number method for rainfall excess computation to SWAT would be a significant enhancement. Parameters and data of both the models are interchangeable and, therefore, are compatible and their combination will result in a more comprehensive and efficient model.

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