Improving Government-Provided Urban Flood Vulnerability Assessment for Adaptation Decision Support

VESTAP, a climate decision support tool offered by the South Korean government, supports sector-specific vulnerability assessments for local and regional governments based on the IPCC AR4 framework. As a multi-indicator, spatially based assessment tool, VESTAP conceptualizes vulnerability as a composite of climate exposure, sensitivity, and adaptive capacity, with sub-indicators derived from administrative-unit-level data and aggregated using weighted sums. However, the current assessment of building vulnerability to flooding has limited capacity to reflect the highly localized distribution of key risk factors driving pluvial flooding, which tend to emerge heterogeneously within administrative units. As a result, improvements in spatial discrimination for priority area identification and in the explanatory power of assessment results are required.

Effective climate adaptation requires the precise identification of vulnerable areas to support priority setting. Pluvial flooding, the focus of this study, occurs within urban areas due to insufficient drainage capacity and topographic water retention during heavy rainfall, with risk factors often concentrated at highly localized scales. It is widely recognized that administrative-unit-level assessments are insufficient for identifying flood-prone areas under such conditions. Recent studies have addressed this limitation by quantifying the spatial distribution of risk factors at finer spatial units-such as parcels, households, and grids-and by integrating physical models with socio-economic indicators to better capture spatial heterogeneity.

This study aims to improve a government-offered vulnerability assessment for Suwon, South Korea, by enhancing spatial resolution and indicator composition to provide actionable information for local adaptation planning. Compared to a baseline setup (S0), five improvement strategies are introduced: (1) region-specific adjustment of indicator weights, (2) incorporation of nationally available spatial explanatory datasets, (3) addition of literature-based key indicators, (4) transition from simple aggregation to an overlapping analytical approach, and (5) integration of municipality-produced datasets. The results of each pilot application are quantitatively compared in terms of changes in the spatial patterns of vulnerable areas, and their validity is evaluated through consistency with observed flood damage records and recovery and prevention investment histories. In addition, interviews with local government officials are conducted to assess practical relevance and usability.

By diagnosing the existing vulnerability assessment framework for pluvial flooding in light of theory and prior research, and by comparing pilot application results, this study examines the potential for improving spatial sensitivity and assessment validity. The findings provide more precise and explainable evidence to support priority setting and resource allocation for local climate adaptation planning.