Remote Sensing and Geographic Information System based Spatial Water Budget Assessment in Major Crops of a Semi-arid Region in India

Water budgeting is essential for efficient water resource management especially in semi-arid and drought-prone regions of the world such as Ahilyanagar district of Maharashtra state, which lies in the rain-shadow zone of the Western Ghats in India. This study assessed water budget components spatially using remote sensing and geographic information system (GIS) techniques to support sustainable water management and agricultural decision-making. In this study, rainfall data of 14 rain gauge stations and temperature data of five meteorological stations for 13-year period (2003-2015) were integrated spatially to estimate reference evapotranspiration (ET₀), crop evapotranspiration (ETc), surface runoff, and soil water storage. Land use/land cover (LULC) analysis revealed that agricultural land dominated with 75.4% area, while soil texture is largely composed of clay (66.9%) and loamy soils (32.6%), which strongly influenced infiltration capacity, runoff generation, and soil moisture retention. The mean annual rainfall exhibited notable spatial variability (458-877 mm), with annual runoff ranging from 100 to 332 mm, representing approximately 2.7%-33.0% of the total rainfall. The ET₀ varied between 1724 and 1979 mm, indicating high atmospheric water demand across the study area. Estimates of the crop water demand showed significant deficits for water-intensive crops such as sugarcane (1610-1710 mm), rice (777-887 mm) and cotton (635-703 mm), whereas low water demanding crops such as pearl millet, chickpea, black gram, and green gram typically required less than 350 mm water and were found more suitable for water deficit areas. Overall, the results demonstrated that GIS-based spatial water balance modeling is an effective tool for delineating water-stressed zones, optimizing irrigation strategies, guiding crop selection, and promoting long-term sustainable water resource management in semi-arid and drought-affected landscapes.