Vulnerable area identification of a Coastal river basin of India using SWAT model

The soil and water assessment tool (SWAT) was employed to evaluate hydrological fluxes in the Subarnarekha river basin, a coastal tropical region in India. The study utilized a spatially explicit approach, dividing the area into discrete sub-basins (166 units) and subdividing them into hydrologic response units (HRUs) 1335 units, based on exclusive combinations of slope, land use, and soil combinations. With an area of 26105 km2 and surface elevations ranging from 0 to 1172 m above mean sea level (amsl), the basin predominantly features less than 8% slope (81.43% area of total basin area). The soil composition varied between loamy, clay loam, and clay. The SWAT model underwent calibration (2000-2007) and validation (2008-2012) using observed monthly average river discharge data from four gauging locations on the Subarnarekha and Budhabalanga hydrologic reaches. The sequential uncertainty fitting 2 (SUFI-2) framework with 22 parameters yielded model efficiencies (NSE) greater than 0.5 for all gauging locations in both periods. Sensitivity analysis identified the curve number (R_CN2.mgt) as the most sensitive parameter among the 22. The runoff and sediment yield data for each sub-basin were normalized to fit into a scale of 0 to 1. An equal weightage of 0.50 was assigned to both the parameter runoff and sediment yield to identify the hotpots area in the Subarnarekha river basin. The basin was divided into five vulnerability categories: slight, low, moderate, high, and extreme, covering 63.27%, 26.40%, 5.58%, 2.21%, and 2.52% of the total basin area, respectively. Subbasins 38, 40, 126, 148, 142, and 125 exhibited high and extreme vulnerability, respectively. Approximately 10% of the total area fell under moderate to high to extreme vulnerability, emphasizing the need for priority for soil and water conservation measures. The developed methodology can be replicated to delineate vulnerable zones in other river basins to prioritize natural resource management.