HYDROLOGICAL MODELING FOR EFFICIENT WATER RESOURCE PLANNING AND MANAGEMENT

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Area:	Department of Civil Engineering
Abstract:	This study presents an empirical investigation of rainfall-runoff dynamics in monsoon-influenced watersheds, employing integrated hydrological modeling to assess water availability and flood risk under varying climatic conditions. Watershed-scale analysis across three distinct physiographic regions revealed nonlinear relationships between antecedent moisture conditions and surface runoff generation. Machine learning–aided runoff prediction achieved Nash-Sutcliffe Efficiency (NSE) coefficients ranging 0.76–0.89 during calibration phases. Monthly water balance assessments indicated 34–51% of incident precipitation converts to surface runoff, with the remainder distributed between infiltration and evapotranspiration. Seasonal groundwater recharge estimates fluctuated between 120–340 mm annually depending on monsoon intensity and soil permeability. Empirical findings underscore the necessity of process-based modeling frameworks for aquifer replenishment forecasting and flood mitigation design. Management implications centre on staggered check-dam construction in upper reaches and riparian restoration to enhance base-flow sustainability. This research establishes quantitative hydrological signatures applicable across semi-humid and sub-humid agro-climatic zones of South Asia.
Author:	Ravi Kumar Sonwani¹, NK Dhapekar²
DUI:	180724/IJORAR-1545
Page:	9
Paper Id:	1545
Publication Date:	10-Jan-2026
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