Abstract:
The objective of this study was to assess the performance and predictive uncertainty
of the Soil and Water Assessment Tool (SWAT) model on the Bani River Basin, at catchment and
subcatchment levels. The SWAT model was calibrated using the Generalized Likelihood Uncertainty
Estimation (GLUE) approach. Potential Evapotranspiration (PET) and biomass were considered in
the verification of model outputs accuracy. Global Sensitivity Analysis (GSA) was used for identifying
important model parameters. Results indicated a good performance of the global model at daily as
well as monthly time steps with adequate predictive uncertainty. PET was found to be overestimated
but biomass was better predicted in agricultural land and forest. Surface runoff represents the
dominant process on streamflow generation in that region. Individual calibration at subcatchment
scale yielded better performance than when the global parameter sets were applied. These results
are very useful and provide a support to further studies on regionalization to make prediction in
ungauged basins.
