An Integrated Geospatial Techniques and Drought Indices Approach for Assessing Drought Risk in Chitradurga Taluk, Karnataka, India

Abstract Drought poses a significant threat to water security, agriculture, and socio-economic stability in semi-arid regions like Chitradurga Taluk, Karnataka, India. This study integrates geospatial techniques and meteorological indices (SPI, NDVI, NDWI, LST) to assess drought risk from 2000 to 2020. Rainfall analysis reveals high variability, with stations like Bahadhurghatta recording extreme fluctuations (270.96 mm in 2010 to zero in subsequent years), while others (e.g., Holalkere) show stability (778.44 mm average). The SPI identifies severe droughts (e.g., 2019, SPI: -2.16) and wet extremes (2011, SPI: 2.00), correlating with agricultural stress. Vegetation health, accessed via NDVI and VCI, indicates severe stress in 2000 (NDVI: -0.3; VCI: 1 to 25) due to low rainfall and high land surface temperature (LST: 47°C), with recovery in 2015 to 2020 (NDVI: 0.41; VCI: 71 to143) as temperatures moderated (LST: 40 to 41°C). Hydrological conditions, evaluated through NDWI, show acute water scarcity in 2000 (NDWI: -0.41) and improved availability in 2015 (NDWI: 0.39). Spatiotemporal analysis highlights the interplay between meteorological deficits, thermal stress, and ecological responses, with geospatial mapping identifying high-risk zones for targeted mitigation. Machine learning and trend analysis further enhance drought prediction by linking drivers like groundwater depletion and land use changes. The study advocates for multi-index drought monitoring to improve early-warning systems and adaptive strategies, supporting sustainable development goals aligned water management. Findings offer a replicable framework for semi-arid regions globally, emphasizing integrated approaches to build resilience against climate extremes.