Climate change and surface water resources: a district-level study of MNDWI, NDVI, and climate anomalies in India

Climate-induced variability in water resources poses significant challenges for regional water security, particularly in climate-sensitive economies such as India. This study examines the impact of climatic variations on surface water availability and vegetation health at the district level using a monthly panel dataset of 471 districts for the period 2014-2022. Surface water presence is measured using the Modified Normalized Difference Water Index (MNDWI) derived from Landsat 8 imagery, while vegetation health is captured using NDVI from the AVHRR GIMMS-3G+ dataset. Climatic variability is represented by temperature and precipitation anomalies constructed from gridded CRU and NOAA datasets. A random effects model is employed to estimate the associations and to assess the moderating role of baseline climate heterogeneity. The average normalized MNDWI value of 0.40 and NDVI value of 0.53 indicate moderate surface water availability and vegetation cover across districts. Temperature anomalies exert a statistically significant negative effect on both surface water and vegetation: a one-standard-deviation increase in temperature anomalies reduces MNDWI by 0.9% of its standard deviation and NDVI by 4.14% of its standard deviation. Precipitation anomalies exhibit an inverted-U-shaped relationship with MNDWI, while their direct effect on NDVI remains less consistent. The moderating analysis shows that the positive impact of additional rainfall on vegetation is stronger in drier regions, whereas districts with higher baseline surface water availability display a weaker vegetation response. These findings underscore the importance of region-specific water management and climate adaptation strategies. Future research can integrate groundwater dynamics, longer remote sensing time series, and extreme event indicators to better capture the adverse effects of climate variability.