Development of Decision Support System for Reusing Underground Infrastructure Water

This study evaluates the reuse potential of deep underground storage water by conducting inflow water quality analysis using urban stream monitoring data, integrating literature-based nonlinear coagulation reaction expressions, calibrating regression coefficients with experimental observations, and developing a decision support system (DSS) for determining optimal combinations of coagulant dosage, pH, and reaction time. Analysis of the Water Environment Information System dataset revealed that key parameters such as TN, TP, and total coliforms in major urban streams of Seoul were at levels requiring management, indicating the need for appropriate pretreatment prior to reuse. To reflect the nonlinear behavior inherent in coagulation–flocculation processes, reaction expressions reported in the literature were combined and subsequently refined using experimental data, resulting in predictive models for turbidity, TSS, COD, BOD, TN, TP, and total coliforms. The DSS integrates these models with use-specific water quality criteria and automatically derives optimal operating conditions, thereby reducing reliance on empirical judgment and enabling more consistent decision-making. In addition, because the DSS framework and coagulation-based pretreatment rely on low-cost and lowcomplexity operational requirements, the proposed approach exhibits practical applicability in diverse regional contexts, particularly in climate-vulnerable or low-income areas where stormwater-derived or variable-quality water must be managed. This study provides an analytical foundation for establishing reuse strategies for deep underground storage water and can be further extended to a real-time operational system incorporating continuous sensor data.