Spatial Data Modelling of Atmospheric Water Availability and Stress in Jharkhand, India

Abstract

The levels of Atmospheric Water Stress (AWS) and Atmospheric Water Availability (AWA) in Jharkhand, India was investigated in this study. The analysis makes use of MODIS NDVI and Terra Climate data that have undergone Google Earth Engine (GEE) processing. Following the computation of mean annual values for Normalized Difference Water Index (NDWI), run-off, precipitation, and Evapotranspiration (ET), AWS and AWA are classified based on these indices. Significant geographical variations in ET, precipitation, runoff, AWS, and AWA are revealed by the results across a few Jharkhand regions. Purbi Singhbhum exhibits significantly higher rates of ET than Garhwa, Palamu, and Chatra, which experience comparatively lower rates. Geographic areas with high levels of AWS, including Sahibganj, Godda, Pakur, Garhwa, and Kodarma, serve as indicators of more severe water scarcity. Consequently, these regions necessitate the implementation of targeted water management strategies. Conversely, varying degrees of AWS are observed in districts including Giridih, Chatra, Jamtara, Latehar, Simdega, and Hazaribagh, underscoring the need for individualized interventions. By identifying regions with limited water availability, the AWA index facilitates the formulation of well-informed resource management decisions. AWS is exacerbated by climate variability, which impacts the distribution of temperatures and precipitation, particularly in regions where AWS levels are high. Local infrastructure development and the implementation of water management strategies are crucial for mitigating the effects of water scarcity.