Smart Watersheds, Smarter Governance: A Unified AI-GIS-IoT Framework for Climate-Resilient Maharashtra

Maharashtra's 36 districts face mounting challenges in groundwater and climate resource management, characterized by widespread groundwater depletion, increasing frequency of extreme weather events, and the absence of real-time, integrated monitoring systems. This research aims to design and propose a centralized, AI-enabled, and IoT- integrated groundwater and climate monitoring framework tailored to the hydro-climatic diversity of the state. The methodology follows a phased approach: (i) high-resolution data collection through ground-based sensors—piezometers for groundwater levels, automated weather stations (AWS) for meteorological data, and in-situ soil moisture probes; (ii) integration of satellite remote sensing data including NDVI, IMERG, and SMAP products; (iii) seamless real-time data transmission via IoT-enabled devices and cloud infrastructure; (iv) advanced analytics using AI and machine learning algorithms for forecasting droughts, flood risks, and potential recharge zones; and (v) visualization and decision support through GIS-based dashboards at the Groundwater Surveys and Development Agency (GSDA) Headquarters, Pune. The study reveals stark spatial disparities—such as recurrent droughts in Marathwada, erratic rainfall in Vidarbha, coastal flooding in Konkan, and groundwater over-extraction in Western Maharashtra—underscoring the limitations of the current fragmented and outdated monitoring systems. The proposed integrated model demonstrates significant improvement in predictive accuracy, early warning capability, and district-specific resource management. The results confirm the scalability, adaptability, and transformative potential of this AI-powered system as a replicable blueprint for sustainable water governance across Maharashtra and other climate-vulnerable regions in India.