International Journal of Environment and Climate Change

Quantitative assessment of water-balance components is essential for effective watershed planning and sustainable water-resources management. However, continuous observations of runoff, soil moisture, groundwater recharge, and evapotranspiration are often unavailable in data-scarce or ungauged watersheds, whereas rainfall data are comparatively easier to obtain through automatic weather stations and rain-gauge networks. Therefore, developing statistical relationships between rainfall and other water-balance components provides a practical approach for estimating hydrological variables where direct measurements are limited. The present study was conducted in the Sonnenahalli micro-watershed of Kolar District, Karnataka, to develop relationships between rainfall and the major water-balance components, namely runoff, soil moisture, groundwater recharge, and actual evapotranspiration. Monthly water-balance components were estimated for the period from January 2023 to December 2024, and correlation and regression analyses were performed using R software. The statistical evaluation revealed a very strong relationship between rainfall and runoff (R² = 0.985, r = 0.82, NSE = 0.98, and RMSE = 1.89), indicating that rainfall is a reliable predictor of runoff generation. Rainfall also exhibited an extremely strong relationship with groundwater recharge (R² = 0.994 and r = 0.996), although the negative NSE (−0.76) and high negative PBIAS (−90.19%) indicated systematic bias in the groundwater simulation. A moderate relationship was observed between rainfall and soil moisture (R² = 0.288 and NSE = 0.52), whereas the relationship between rainfall and evapotranspiration was weak to moderate (R² = 0.439, r = 0.018, and NSE = 0.27), suggesting that these components are influenced by additional climatic and soil-related factors. The developed regression models demonstrate that rainfall can be used effectively to estimate runoff and groundwater recharge and, to a reasonable extent, soil moisture and evapotranspiration. These findings provide a simple tool for hydrological assessment and support water-resources planning, watershed management, and decision-making in data-limited, semi-arid regions.