Integrated urban flood vulnerability assessment using local spatial dependence-based probabilistic approach

Abstract

Vulnerability assessment is an essential step for urban flood risk management. Due to the objective existence of statistical errors in the variables and spatial heterogeneity, as well as the similarity of flood experience, precautionary status and environments for neighbouring areas, an urban flood vulnerability assessment essentially entails a multi-factor decision-making process that accounts for uncertainties and the local spatial dependence of neighbourhoods. To address these issues, an uncertainty-based vulnerability assessment approach embedded with an improved moving split-window (IMSW) analysis and probabilistic method is proposed. To develop an integrated urban flood vulnerability assessment model, three technical issues need to be resolved: (1) the development of damage curves of land-use types, (2) an uncertainty model and spatial dependence model of damages based on an IMSW analysis, and (3) an uncertainty-based framework to quantify vulnerability considering the uncertainties and local spatial dependence of the damage curves as well as the spatial heterogeneity of risky assets simultaneously. The proposed method is applied to an urban area in China and provides an integrated vulnerability assessment for different land-use types. Moreover, uncertainty and sensitivity analyses were performed to analyse the spatial differentiation and the dominant parameters of vulnerability. Compared with two other commonly used methods, the proposed local-correlated method (LCM) is more in line with reality, and provides more reasonable information for making a better-informed decision.