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Urban Flood Resilience under Climate Change

Introduction

Urban flood hazards pose formidable challenges to sustainable development, jeopardizing the safety and security of inhabitants and their assets. The ramifications of these risks may be intensified by global climate change and accelerated urbanization. This study incorporates resilience concepts into a robust flood risk assessment framework, with particular emphasis on the Hangzhou Sanjiang region within the Yangtze River Delta, China—a locale characterized by heightened flood susceptibility. Advanced multi-scenario precipitation projections derived from the CMIP6 climate model suite are utilized, integrating SCS-CN and GIS methodologies to generate flood risk under different Shared Socioeconomic Pathways(SSP) scenarios across an array of return periods. A comprehensive evaluation of regional flood resilience risk is undertaken, incorporating dimensions of hazard exposure, vulnerability, sensitivity, and adaptive capacity. Subsequently, we employ a cutting-edge BP neural network algorithm to delineate flood resilience zoning under an assortment of climate change scenarios, culminating in the proposition of targeted resilience augmentation strategies. The findings contribute to the burgeoning body of knowledge surrounding urban flood disaster modeling and assessment within a climate resilience framework, offering valuable insights and transferable lessons for flood management in analogous regions.

Key words

Urban Flood Resilience; Climate Change; SCS-CN; BP Neural Network; CMIP6

CMIP6-SSPs

CMIP6 Future Climate Prediction Dataset: BCC-CEM2-MRFuture Climate Prediction Dataset (Beijing Climate Center, China Meteorological Administration, China)

Worldclimate


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