Paper No. JAWRA-08-0161-P of the Journal of the American Water Resources Association (JAWRA). Discussions are open until six months from print publication.
Impact of Watershed Subdivision and Soil Data Resolution on SWAT Model Calibration and Parameter Uncertainty1
Article first published online: 19 AUG 2009
© 2009 American Water Resources Association
JAWRA Journal of the American Water Resources Association
Volume 45, Issue 5, pages 1179–1196, October 2009
How to Cite
Kumar, S. and Merwade, V. (2009), Impact of Watershed Subdivision and Soil Data Resolution on SWAT Model Calibration and Parameter Uncertainty. JAWRA Journal of the American Water Resources Association, 45: 1179–1196. doi: 10.1111/j.1752-1688.2009.00353.x
- Issue published online: 5 OCT 2009
- Article first published online: 19 AUG 2009
- Received August 29, 2008; accepted May 19, 2009.
- hydrologic modeling;
- watershed subdivision;
- parameter uncertainty;
- Soil Water Assessment Tool;
Abstract: Impact of watershed subdivision and soil data resolution on Soil Water Assessment Tool (SWAT) model calibration and parameter uncertainty is investigated by creating 24 different watershed model configurations for two study areas in northern Indiana. SWAT autocalibration tool is used to calibrate 14 parameters for simulating seven years of daily streamflow records. Calibrated parameter sets are found to be different for all 24 watershed configurations, however in terms of calibrated model output, their effect is minimal. In some cases, autocalibration is followed by manual calibration to correct for low flows, which were underestimated during autocalibration. In addition to normal validation using four years of streamflow data for each calibrated parameter set, cross-validation (using a calibrated parameter set from one model configuration to validate observations using another configuration) is performed to investigate the effect of different model configurations on streamflow prediction. Results show that streamflow output during cross-validation is not affected, thus highlighting the non-unique nature of calibrated parameters in hydrologic modeling. Finally, parameter uncertainty is investigated by extracting good parameter sets during the autocalibration process. Parameter uncertainty analysis suggests that significant parameters show very narrow range of uncertainty across different watershed configurations compared with nonsignificant parameters. Results from recalibration of some configurations using only six significant parameters were comparable to that from calibration using 14 parameters, suggesting that including fewer significant parameters could reduce the uncertainty arising from model parameters, and also expedite the calibration process.