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Assessment of Urban Flood Vulnerability in Manila City, Philippines under Variable Rainfall Scenarios: A Spatiotemporal Analysis Approach
1 , 1 , 1 , 1 , * 1, 2 , 2
1  Department of Software Technology, College of Computer Studies, De La Salle University Manila, 2401 Taft Avenue, Manila 1004, Philippines
2  Department of Physics, College of Science, De La Salle University Manila, 2401 Taft Avenue, Manila 1004, Philippines
Academic Editor: Simeone Chianese

Abstract:

Manila, the capital of the Philippines, is among the most densely populated cities globally and is highly susceptible to flooding due to its low-lying terrain, rapid urban development, inadequate drainage infrastructure, and geographic proximity to the Pasig River and Manila Bay. The city regularly experiences pluvial, fluvial, and tidal flooding, exacerbated by climate variability and sea-level rise. This study presents a spatiotemporal analysis of urban flood vulnerability in Manila under three distinct rainfall scenarios: light, moderate, and heavy intensity. Flood hazard maps were generated for each scenario using hydrodynamic simulations and integrated with socio-demographic data at the Barangay level to evaluate population exposure and sensitivity. Spatial correlation and spatial autocorrelation techniques, including Moran’s I and Local Indicators of Spatial Association (LISA), were applied to identify statistically significant clusters of flood vulnerability. Vulnerability was assessed as a function of flood intensity, population density, poverty incidence, age distribution, and access to basic services and infrastructure. In addition to mapping high-risk areas, the study identified flood-resilient “safe zones”, geographic locations that consistently remained outside flood extents across all modeled scenarios. These areas were evaluated for their suitability as evacuation centers and emergency response sites based on proximity to vulnerable populations and existing infrastructure. Findings highlight a clear spatial overlap between flood-prone zones and socioeconomically disadvantaged communities, indicating the need for targeted disaster risk reduction and urban planning strategies. The results provide evidence-based recommendations for policy development aimed at enhancing flood resilience and adaptive capacity in Manila’s urban landscape.

Keywords: Urban flooding; Flood vulnerability; Spatiotemporal analysis; HEC-RAS; Rainfall scenarios; Spatial autocorrelation; Moran’s I; LISA; Socio-demographic data; Manila City; Safe zones; Disaster risk reduction; Climate resilience; Flood hazard mapping; Urban
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