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Published by the American Society of Agricultural and Biological Engineers, St. Joseph, Michigan

Citation:  Transactions of the ASAE. Vol. 48(3): 1025-1040. (doi: 10.13031/2013.18514) @2005
Authors:   M. W. Van Liew, J. G. Arnold, D. D. Bosch
Keywords:   Calibration, Hydrology, Modeling, Optimization, Simulation, SWAT, Validation

An investigation was conducted to evaluate strengths and limitations of manual calibration and the existing autocalibration tool in the watershed-scale model referred to as the Soil and Water Assessment Tool (SWAT). Performance of the model was tested on the Little River Experimental Watershed in Georgia and the Little Washita River Experimental Watershed in Oklahoma, both USDA-ARS watersheds. A long record of multi-gauge streamflow data on each of the watersheds was used for model calibration and validation. Model performance of the streamflow response in SWAT was assessed using a six-parameter manual calibration based on daily mass balance and visual inspection of hydrographs and duration of daily flow curves, a six-parameter autocalibration method based on the daily sum of squares of the residuals after ranking objective function (referred to as SSQRauto6), a six-parameter method based on the daily sum of squares of residuals (SSQauto6), and an eleven-parameter method based on the daily sum of square of residuals (SSQauto11). Results show that for both watersheds, manual calibration generally outperformed the autocalibration methods based on percent bias (PBIAS) and simulation of the range in magnitude of daily flows. For the calibration period on Little River subwatershed F, PBIAS was 0.0%, -24.0%, -21.5%, and +29.0% for the manual, SSQRauto6, SSQauto6, and SSQauto11 methods, respectively. Based on the coefficient of efficiency (NSE), the SSQauto6 and SSQauto11 methods gave substantially better results than manual calibration on the Little River watershed. On the Little Washita watershed, however, the manual approach generally outperformed the automated methods, based on the NSE error statistic. Results of this study suggest that the autocalibration option in SWAT provides a powerful, labor-saving tool that can be used to substantially reduce the frustration and uncertainty that often characterize manual calibrations. If used in combination with a manual approach, the autocalibration tool shows promising results in providing initial estimates for model parameters. To maintain mass balance and adequately represent the range in magnitude of output variables, manual adjustments may be necessary following autocalibration. Caution must also be exercised in utilizing the autocalibration tool so that the selection of initial lower and upper ranges in the parameters results in calibrated values that are representative of watershed conditions.

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