Ecological Indicators (Oct 2024)
A novel framework for evidence-based assessment of flood resilience integrating multi-source evidence: A case study of the Yangtze River Economic Belt, China
Abstract
Floods are extremely destructive to the society, economy and nature, and severely restrict sustainable urban development. There is an urgent need to assess the level of flood resilience, analyze its evolutionary characteristics and improve the flood resilience of the region. However, few previous studies have integrated multi-source evidence into a framework for assessing flood resilience over a longer time span. This study integrated multi-source evidence to analyze the Yangtze River Economic Belt, including literature-based evidence, policy texts and social media data. Subsequently, the Kruskal algorithm and Jaccard coefficient were used to construct collinear networks and identify the clustering dimensions of flood resilience. After evidence judgment, a flood resilience indicator system was constructed. The flood resilience index was calculated using the improved Critic method. The dynamic evolution characteristics and key influencing factors were illustrated by the Kernel density and Grey correlation methods, respectively. The principal contribution is to integrate multi-source evidence to assess flood resilience, with a newly constructed indicator system that systematically considers local public demand, policy priorities and common indicators from previous literature. The results show that: the flood resilience index of the Yangtze River Economic Belt is in the range of [0.16, 0.75] from 2000 to 2022, with higher values in the downstream compared to those in the midstream and upstream. The social dimension dominating the overall flood resilience. The kernel density curve of the YREB is characterized by a right trailing. The inter-regional differences tend to widen and have a polarization effect. The special funds for water conservancy finances and the length of flood prevention levees are key factors influencing the level of flood resilience. Finally, strategies for enhancing flood resilience were proposed. This study provides a feasible framework for constructing an indicator system and assessing flood resilience by integrating multi-source data. It is important for flood risk management and helps to the development of urban flood prevention and resilience strategies.
