Published Paper Details:

ABSTRACT Water is one of the most vital natural resources that sustains life and meets our fundamental needs. Every drop of water is valuable, making its preservation and judicious utilization essential. The accessibility of this resource is determined largely by surface and groundwater bodies. However, climate change--manifested through rising temperatures, shifting precipitation patterns, variability in rainfall, and sea level rise--has altered river flow and groundwater recharge. Consequently, groundwater resources are highly sensitive to these climatic changes. Rapid urbanization, industrial expansion, and intensive agricultural practices have significantly transformed land use patterns. This has led to excessive extraction of groundwater, causing not only depletion and over-mining of aquifers but also deterioration in water quality. Added to this, global warming, deforestation, and irregular rainfall have further aggravated water scarcity and reduced recharge potential. To address these challenges, geospatial technologies such as the Global Positioning System (GPS) and Geographic Information Systems (GIS) have emerged as powerful tools for analysing land resources and water availability. This study employs GIS-based analysis, integrated with ontology and semantic web techniques, to survey underground water resources and explore strategies to enhance their quality. Sustainable development in any region requires effective water resource management, and computer-aided analysis--particularly through the combined application of Remote Sensing (RS) and GIS--offers a highly valuable approach. The research focuses on applying RS and GIS to agricultural water management in India, aiming to improve efficiency and effectiveness in managing water resources. By assessing the current role of geospatial technology in Indian agriculture, the study introduces a proposed model where geospatial ontology and Query-based GIS (QGIS) are employed. The system is designed to identify areas, especially in hilly terrains, where rainwater can be effectively harvested and absorbed into the soil, thereby enhancing groundwater recharge and improving drinking water quality. The QGIS framework allows for queries related to locating underground drinking water sources and mapping regions near the Western Ghats of Maharashtra, India. Additionally, semantic processes are incorporated for advanced query handling, enabling the system to identify areas suitable for rainwater stoppage and infiltration. The ontology-driven design ensures that query services are semantically linked, improving the search process and the overall utility of the model. This proposed model highlights the potential of integrating RS, GIS, ontology, and semantic web technologies to strengthen agricultural water management and support sustainability in India.