Comparative Analysis of SWAT Model Performance under Varying Land Use and Soil Data Resolutions in Eastern India

Abstract

This study investigated the impact of land use/land cover (LULC) and soil data resolution on hydrological modeling using the Soil and Water Assessment Tool (SWAT) in the Bargarh command area of the Mahanadi River Basin, India. Six scenarios combining different resolutions of LULC (1:250000, 1:50000, and 10m spatial resolution) and soil data (1:5000000 and 1:50000) were used to simulate streamflow. The SWAT model was calibrated (2000-2012) and validated (2013-2020) using the SUFI-2 algorithm. Model performance was evaluated using the Nash-Sutcliffe efficiency (NSE), coefficient of determination (R2), percent bias (P-bias), R-factor, and P-factor. The results showed that the simulated streamflow matched well with the observed data for all scenarios, with the D1L1S1, D1L3S1, and D1L3S2 setups exhibiting the best agreement. The NSE values ranged from 0.76 to 0.89, R2 from 0.86 to 0.91, P-bias from -3.8% to 31.7%, R-factor from 0.56 to 1.20, and P-factor from 0.73 to 0.91 during calibration and validation. This study highlights the importance of the combination and classification of datasets in hydrological modeling, indicating that fitted parameter values do not adjust uniformly for all uncertainty sources. These findings provide guidance for selecting appropriate precision levels of input data for future applications to improve the accuracy and reliability of hydrological predictions. This study also highlights the practical relevance of hydrological modeling for water resource planning and management. The findings provide guidance on selecting appropriate input data resolutions to improve the accuracy and reliability of streamflow predictions using the SWAT model.