International Journal For Multidisciplinary Research

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GIS based analysis of availability of underground water inside the land using ontology and semantic web

Author(s) Mr. Pankaj Vishwas Phadtare, Dr. Shaileshkumar
Country India
Abstract Water is one of the most essential natural resources, critical for meeting basic human needs such as drinking, sanitation, agriculture, and industrial use. With increasing urbanization and industrial growth, the demand for water has surged dramatically. However, this rising demand is not being met with sustainable supply practices, leading to the over-extraction and deterioration of both surface and groundwater resources. Groundwater, a vital component of the hydrological cycle, is particularly sensitive to the impacts of climate change. These effects manifest through changes in groundwater recharge rates, river levels, and flow patterns. Variations in average temperature, precipitation, and sea levels directly influence the availability and quality of groundwater. Factors such as rising temperatures, erratic rainfall, and coastal changes contribute to altered recharge patterns and depleted groundwater tables. Rapid changes in land use, driven by urban sprawl, industrial expansion, and intensified agricultural practices, are also contributing to the excessive withdrawal of groundwater. This has led to the depletion of aquifers and the degradation of water quality. Additionally, deforestation and global warming have resulted in inconsistent and declining rainfall patterns, further complicating the groundwater recharge process. In this context, geospatial technologies such as Global Positioning System (GPS) and Geographic Information System (GIS) have emerged as powerful tools for mapping, analyzing, and managing land and water resources. This study proposes a geospatial and ontology-driven approach for assessing groundwater availability and improving its quality using semantic web technologies. The effective management of water resources is essential for sustainable development, particularly in regions like India where water scarcity is a growing concern. The integration of remote sensing (RS) and GIS offers a robust framework for computer-aided resource analysis and decision-making. This research focuses on leveraging RS and GIS to address challenges in agricultural water management, aiming to enhance the efficiency and sustainability of water use in agriculture. The study explores the current application of geospatial technologies in India’s agricultural water management practices. It introduces a proposed model that combines geospatial ontology with a Query-based Geographic Information System (QGIS). The system is designed to identify and map regions, particularly in hilly terrains, where rainwater can be effectively harvested. This would promote natural groundwater recharge and improve the overall quality of drinking water.
The proposed QGIS framework includes queries designed to:
• Locate underground drinking water sources using GIS survey data.
• Map areas near the Western Ghats in Maharashtra, India, that are suitable for rainwater retention.
• Perform semantic analysis to identify potential regions for rainwater harvesting in mountainous areas, where water can be absorbed by the soil to boost groundwater levels.
The core objective of this model is to use ontology-based methods to semantically relate user queries with available geospatial data. This enables more precise and meaningful search results, enhancing the system’s capability to support groundwater management decisions. This research highlights the importance of integrating semantic web technologies with geospatial systems for effective and sustainable groundwater management. The proposed ontology-based QGIS model aims to facilitate data-driven planning and help improve water availability and quality in water-stressed regions of India.
Keywords GIS, Ontology, Semantic Web, GPS, RS
Field Computer Applications
Published In Volume 7, Issue 5, September-October 2025
Published On 2025-10-03
DOI https://doi.org/10.36948/ijfmr.2025.v07i05.57108
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