MULTI-SITE CALIBRATION OF THE SWAT MODEL FOR HYDROLOGIC MODELING
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The growing popularity of applying complex, semi-physically based distributed hydrologic models to solve water resource problems poses important issues that must be addressed related to the use of spatial data to calibrate and validate such models. In this study, a single-objective optimization method (GA) and a multi-objective optimization algorithm (SPEA2) were applied to optimize the parameters of the Soil and Water Assessment Tool (SWAT) using observed streamflow data at three monitoring sites within the Reynolds Creek Experimental Watershed, Idaho. Results indicated that different optimization schemes can lead to substantially different objective function values, parameter solutions, and corresponding simulated hydrographs. Thus, the selection of an optimization scheme can potentially impact modeled streamflow. Parameters estimated by optimizing the objective function at three monitoring sites consistently produced better goodness-of-fit than those obtained by optimization at a single monitoring site. This stresses the importance of collecting detailed, spatially distributed data to conduct simultaneous multi-site calibrations. When applied with multi-site data, the single-objective (GA) method better identified parameter solutions in the calibration period, but the multi-objective (SPEA2) method performed better in the validation period. Overall, the application of different optimization schemes in the Reynolds Creek Experimental Watershed demonstrated that the single-objective (GA) and the multi-objective (SPEA2) optimization methods can provide promising results for multi-site calibration and validation of the SWAT model. These results are expected to help the users of SWAT and other distributed hydrologic models understand the sensitivity of distributed hydrologic simulation to different calibration methods and to demonstrate the advantages and disadvantages of single-objective and multi-objective parameter estimation methods. 2008 American Society of Agricultural and Biological Engineers.
