Abstract This study presents a spatiotemporal assessment of soil water balance within the Nagarjunasagar Left Bank Canal (NSLBC) command area, aimed at evaluating irrigation water demand and supply dynamics over time. A distributed water balance simulation model was developed using the Google Earth Engine (GEE) cloud platform to analyse the geographic and temporal variability of irrigation water availability. The model integrates key hydrological components, including groundwater storage fluctuations, precipitation inputs, and water losses from runoff and evapotranspiration. Data sources include MODIS (evaporation), TerraClimate (soil moisture), GRACE (terrestrial water storage), and the SCS Curve Number method (runoff estimation). Evapotranspiration was calculated using the Surface Energy Balance Algorithm for Land (SEBAL). Simulation results from 2003 to 2013 indicate a generally favourable water balance, with only a minor deficit of 6 mm in January 2010 and a peak surplus of 477 mm in July 2010. Trend analysis using Sen’s Slope estimator and the Mann-Kendall test reveals consistent growth of water balance in the command area, accompanied by notable spatiotemporal variability. Monthly water balance values ranged from − 1.5 mm to 233 mm across the region. Model validation against actual canal flow data from 2003 yielded a root mean square error (RMSE) of 29 mm - less than 10% of the observed water balance range - demonstrating high reliability. These findings underscore the value of cloud-based platforms like GEE for large-scale hydrological modelling and offer actionable insights for sustainable irrigation water management in semi-arid agricultural regions.
Sankriti et al. (Sat,) studied this question.