Development of a GIS-Coupled Water Quality Model for Dynamic Pollution Management in River Basins: A Decision Support System Approach (International Journal of Computer Science and Engineering, 2026)
The complexity inherent in basin-scale water quality management, characterized by multifaceted pollution sources and pronounced spatiotemporal heterogeneity, frequently challenges the efficacy of conventional static assessment methodologies. This study endeavors to address this gap by developing an integrated decision support system that couples a Geographic Information System with a dynamic water quality model, specifically tailored for adaptive pollution management in a representative data-scarce basin. The DSS architecture was constructed to enable the visualization of pollution hotspots and the simulation of pollutant transport under various hydrological and management scenarios. A significant challenge encountered during development was the calibration of the model's sensitive parameters, particularly the nutrient decay coefficients, which exhibited considerable variability across different sub-catchments due to unaccounted land-use practices. This necessitated a shift from a purely automated calibration to a more iterative, semi-automated approach incorporating localized expert knowledge. The calibrated system demonstrated a reasonable capacity to reproduce historical water quality events, with simulation errors for Biochemical Oxygen Demand and Total Nitrogen remaining within an acceptable range for most monitoring stations, although deviations were noted during extreme precipitation events, pointing to potential limitations in the model's representation of surface runoff processes.