Morphological and hydrological analysis of Kantamal sub-basin of the Mahanadi River, Odisha (India), using QSWAT model

Morphometric parameters of drainage basins offer valuable insights into landscape attributes derived from elevation surfaces and drainage networks. In this study, we analyse the drainage characteristics of the Kantamal Sub-basin of the Mahanadi River, employing geospatial analysis. Hydrologic parameters are calculated through the application of the Soil and Water Assessment Tool (QSWAT) model. The calibration of the QSWAT model spans eight years (1980-1987), including a two-year warm-up period, achieved via the Sequential Uncertainty Fitting (SUFI-2) algorithm within the SWAT Calibration and Uncertainty Program. Subsequent validation for the period 1993 to 1996 is performed using observed data. Model performance shows a good degree of agreement between observed and simulated discharge, as measured by Coefficient of determination R2 (0.75), Nash - Sutcliffe efficiency coefficient ENS (0.75), and percent bias PBIAS (1.1) values. 14 sub-watersheds make up the study area. 22 morphometric parameters were calculated for each of three main categories: linear, areal, and relief characteristics. Correlations between various morphometric and hydrologic parameters reveal their interconnectedness and influence on basin hydro-geomorphology. Stronger connections are seen between stream frequency (Fs) and potential evapotranspiration, base flow, deep percolation, and water yield (0.75-0.93), whereas R2 values show modest relationships for metrics including drainage density (Dd), sediment yield, and evapotranspiration (0.30-0.40). Additionally, R2 values of 0.48 to 0.70 are present in relationships between the infiltration number (If), potential evapotranspiration, base flow, and sediment yield. This study underscores the significance of integrating morphometric parameters, geospatial techniques, and the QSWAT model to address data limitations and enhance our understanding of basin dynamics. To address the issue of a lack of observed data, morphometric parameters, a GIS, and the QSWAT model have all been integrated in this study.