Examining model performances and parameter uncertainty for streamflow and suspended sediment regime simulation: Comparison of three calibration methods

Abstract

Spatially distributed watershed models are commonly utilized to address a wide range of water-related issues. However, setting up a reliable watershed model is a difficult task involving several essential decisions making. Choice of calibration method is one of the most important decisions that has been sparsely investigated in semi-distributed watershed models. In this study, therefore, we used the Soil and Water Assessment Tool (SWAT) model to investigate the impact of three calibration methods: sequential (SQN), simultaneous (SML) and sequential-simultaneous (SQN_SML) on model performance and parameter uncertainty in the Kantamal catchment of the Mahanadi basin, India. The findings across the calibration methods; evaluated fit scores of streamflow for respective calibration and validation period; showed that SQN_SML calibration has the least amount of bias (PBAIS = 1.7, −4.2), the highest NSE (0.91, 0.92), KGE (0.95, 0.94) and R2 (0.91, 0.92). Furthermore, SQN_SML outperformed the other two methods in all three streamflow regimes (low, medium and high) of flow duration curve analysis. Suspended sediment load (SSL) analyses of partitioned sediment duration curve showed the best performance of SQN_SML for mid and low SSL regimes while all three calibration methods performed similarly in the high SSL regime. SML calibration approach showed the least parameter uncertainty followed by SQN_SML and SQN. The P-factor for sediment simulation was better for the SQN_SML approach, indicating the minimal model error for sediment simulation. The SQN_SML produced the least equifinal solution, while the SQN approach produced the highest equifinal solution. Overall, the findings of this study may help the watershed modelling communities for selecting suitable calibration strategies when dealing with integrated water resources management.