A review of integrated GIS techniques for optimization of urban water management
Year: 2026
Type: article
Abstract: Sustainable management of water resources in urban areas is a critical issue due to rapid urbanization. Building resilient urban water supply and demand systems requires an appropriate understanding of how anthropogenic activities, climate change, and environmental factors affect water availability and distribution. An integrated, holistic approach is essential to achieve effective urban water resource management. This research reviews the challenges of water scarcity driven by unprecedented urban expansion. The study aims to analyse water issues across the globe and understand their water management system. Systematic technological trends were observed in urban water science, from econometric techniques of the 1980s to geospatial technologies in the 20th century to extensive integration of artificial intelligence in the 21st century. The study aims to highlight the integration of advanced techniques within a Geographic Information System (GIS) framework for urban water management. It provides a comprehensive overview of various spatial techniques and analytical technologies, including Geospatial models, geostatistical models, hydraulic models, and artificial intelligence/machine learning approaches, and discusses how these methodologies are interoperable within a GIS environment to study water. Combining various techniques is a good practice for accurate analysis and prediction-based urban water studies. GIS is a powerful decision-support tool that enables multidisciplinary approaches by integrating diverse spatial and non-spatial datasets on a single digital platform for comprehensive urban water analysis. An integrated GIS framework provides better resource allocation, raises awareness about responsible water use, and promotes water-saving technologies.
Source: Applied Water Science
Language: English
Subfield: Ocean Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $2,490
OpenAlex ID: W7203924012
