Hydroinformatics and GIS Integration for Intelligent Water Resource Management - Mayowa Jimoh; Audu Khadijah (International Journal of Scientific Research in Science and Technology, 2025)
Intelligent water resource management (IWRM) has emerged as a critical response to increasing global pressures on freshwater systems caused by climate variability, urbanization, and growing population demands. Addressing these challenges requires integrated technological approaches capable of analyzing complex hydrological processes and spatial environmental dynamics. This study investigates the synergistic integration of hydroinformatics and Geographic Information Systems (GIS) as a comprehensive framework for intelligent water resource management. Hydroinformatics provides advanced computational capabilities for hydrological modeling, simulation, and data-driven analysis, while GIS offers powerful spatial data management, visualization, and geospatial analytics necessary for understanding geographically distributed water systems. The study synthesizes existing literature to examine the evolution of both disciplines and identifies key methodological approaches for integrating hydrological modeling with spatial intelligence platforms. A conceptual Hydroinformatics–GIS Integration Framework is proposed to illustrate the interaction between environmental data acquisition, hydrological modeling engines, spatial analysis tools, and decision support systems. The analysis demonstrates that the integration of hydroinformatics and GIS significantly enhances predictive modeling, spatial risk assessment, and data-driven decision-making in applications such as urban flood management, groundwater monitoring, irrigation optimization, and climate adaptation planning. Emerging technologies including machine learning, remote sensing, and sensor-based monitoring networks further expand the analytical capabilities of integrated systems by enabling real-time data processing and predictive analytics. Despite these advancements, challenges remain regarding data heterogeneity, interoperability, institutional coordination, and technical integration across platforms. The study concludes that integrated hydroinformatics–GIS systems represent a transformative paradigm for developing adaptive, resilient, and sustainable water management strategies capable of supporting long-term water security in a changing global environment.
Keywords: Hydroinformatics; Geographic Information Systems (GIS); Intelligent Water Management; Water Resources; Machine Learning; Remote Sensing; Decision Support Systems; Urban Flooding; Irrigation; Climate Adaptation; Data Integration