Spatial data modelling of atmospheric water availability and stress in Jharkhand, India

Abstract Due to climate and human activity, water supply in Jharkhand, India, fluctuates. This study measured AWS and AWA in Jharkhand, India. MODIS NDVI and Terra Climate data processed by Google Earth Engine (GEE) are used in the analysis. Based on mean annual values for NDWI, run-off, precipitation, and ET, AWS and AWA are categorised. Results show significant regional differences in ET, precipitation, runoff, AWS, and AWA in Jharkhand. Purbi Singhbhum has far higher ET rates than Garhwa, Palamu, and Chatra. High AWS levels in Sahibganj, Godda, Pakur, Garhwa, and Kodarma indicate serious water scarcity. Therefore, these locations need focused water management approaches. Different districts including Giridih, Chatra, Jamtara, Latehar, Simdega, and Hazaribagh have different levels of AWS, highlighting the need for individualised treatments. The AWA index helps resource managers make educated decisions by detecting water-scarce places. Climate variability affects temperatures and precipitation, worsening AWS in high-AWS areas. Water scarcity mitigation requires local infrastructure development and water management measures. To verify remote sensing data accuracy, future study should improve data resolution and include in-situ measurements. These findings can help policymakers and stakeholders in Jharkhand create efficient water resource management strategies to reduce water stress and assure water supply.