Collaborative spatial decision making empowering urban flood governance toward city resilience

Urban flood management increasingly relies on adaptive and integrated systems alongside conventional structural measures. Rapid urbanization has escalated the complexity of managing floods. This paper proposes a novel, integrated spatial decision-making approach to enhance flood governance. The study emphasizes the collaborative engagement of stakeholders, including municipal authorities, water agencies, and local communities, within a GIS-based multi-criteria decision analysis (MCDA) framework. A toolbox developed in ArcGIS incorporates the analytic hierarchy process (AHP). While previous studies often treat spatial analysis and stakeholder participation separately, our model integrates these within a spatial planning support system (SPSS). Results from a case study in Tehran, Iran, demonstrate the model's practical effectiveness in supporting urban flood governance. A final flood hazard map classified the study area into six distinct risk levels: approximately 6% of the area fell into the very-high-risk category, mainly in low-slope, high-density zones with limited drainage capacity, whereas 43% represented moderate-to-high risk and 42% low risk. Least cost path (LCP) analysis, informed by land use, slope, and geology criteria, was applied to delineate optimal urban runoff collection routes, minimizing construction costs by leveraging existing channels and natural gradients. Overall, the proposed model advances data-driven and participatory flood governance by providing a transparent, reproducible, and governance-oriented framework that supports resilient infrastructure planning and policy decision-making in complex urban environments.