Impact Of GIS-Based Spatial Decision Support Systems on Urban Water Supply Network Optimization: A Qualitative Evaluation

Abstract

This study examined the impact of GIS-based Spatial Decision Support Systems on the optimization of urban water supply networks using a quantitative cross-sectional case study design. Data were collected from 120 professionals, including engineers, GIS analysts, planners, and maintenance supervisors, alongside operational and spatial data from 15 urban water network zones. Descriptive and inferential statistical analyses were conducted to evaluate relationships between 3SDSS utilization and key performance indicators such as network efficiency, pressure stability, leakage detection, service coverage, and maintenance prioritization. The findings revealed strong positive correlations between SDSS usage and network optimization outcomes, with correlation coefficients ranging from 0.55 to 0.72, all statistically significant at p < 0.05. Regression analysis indicated that GIS-based SDSS variables explained 62% of the variance in network performance (R² = 0.62), demonstrating substantial predictive power. Leakage rates were significantly lower in high SDSS integration zones (17.9%) compared to low integration zones (27.1%), while pressure stability scores improved from 3.42 to 4.25 on a five-point scale. Sub-group analysis showed that GIS analysts reported higher effectiveness scores (mean = 4.32) compared to maintenance personnel (mean = 3.61), highlighting the influence of user expertise. Reliability testing confirmed strong internal consistency (Cronbach’s alpha = 0.82). The results demonstrated that GIS-based SDSS significantly enhanced decision-making accuracy and operational efficiency, particularly in complex and high-demand network environments. Overall, the study provided empirical evidence supporting the effectiveness of GIS-based spatial decision tools in improving urban water supply system performance and infrastructure management.