Spatial Assessment of Drought and Water Scarcity in the Bundelkhand Region, India: A GIS and Remote Sensing–Based Review and Synthesis

The Bundelkhand region of central India, spanning parts of Uttar Pradesh and Madhya Pradesh, is among the most chronically drought-affected tracts of the country, owing to its hard-rock craton geology, low and erratic monsoon rainfall, and a predominantly rain-fed agrarian economy. Over the last decade, Geographic Information Systems (GIS) and remote sensing (RS) have become the principal tools for characterising meteorological drought, delineating groundwater potential, and monitoring land and vegetation stress across this data-sparse terrain. This paper synthesises peer-reviewed GIS- and RS-based studies (2015–2025) on drought and water scarcity in Bundelkhand to build an integrated understanding of the region's hydro-meteorological vulnerability. Following a structured literature-synthesis methodology, sources were screened from Scopus-indexed journals (ScienceDirect, Springer, MDPI, ASCE, and MAUSAM) using combinations of the terms "Bundelkhand," "drought," "groundwater potential," "GIS," and "remote sensing." The synthesis shows that (i) the Standardized Precipitation Index (SPI) and the Standardized Precipitation Evapotranspiration Index (SPEI) consistently reveal declining monsoon rainfall and rising drought frequency in the northern districts (Jalaun, Hamirpur, Lalitpur, Banda), (ii) frequency-ratio and multi-influencing-factor GIS models classify roughly one-third of the craton as having only low-to-very-low groundwater potential, concentrated in high-slope, low-rainfall, built-up terrain, and (iii) groundwater-dependent ecosystems and streamflow indices corroborate an intensifying hydrological drought signal since the 1980s. A clear research gap emerges: existing studies treat meteorological drought indices, groundwater potential zonation, and vegetation-stress monitoring as separate exercises, rarely integrated into a single, updateable, cross-state spatial decision-support framework. The paper concludes by proposing such an integrated, cloud-based GIS-RS framework, combining SPI/SPEI time series, GRACE-based groundwater storage anomalies, and Google Earth Engine–processed vegetation indices, to support evidence-based drought mitigation and groundwater management across the entire Bundelkhand craton.