Center for Geodata and Analysis, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China.
School of Hydraulic Engineering, Dalian University of Technology, Dalian 116024, China.
Sci Total Environ. 2023 Oct 1;893:164852. doi: 10.1016/j.scitotenv.2023.164852. Epub 2023 Jun 17.
The assessment of flood risk and resilience has become increasingly important in recent years for effective urban flood management. While flood resilience and risk are two distinct concepts with unique assessment metrics, there is lack of quantitative analysis and understanding of the relationship between them. This study aims to investigate this relationship at the grid cell level in urban areas. To assess flood resilience for high-resolution grid cells, this study proposes a performance-based flood resilience metric, which is calculated using the system performance curve based on flood duration and magnitude. Flood risk is calculated as the product of maximum flood depth and probability, considering multiple storm events. The case study of Waterloo in London, UK is analyzed using a two-dimensional cellular automata-based model CADDIES, which consists of 2.7 million grid cells (5 m × 5 m). The results indicate that over 2 % of grid cells have risk values exceeding 1. Furthermore, there is a 5 % difference in resilience values below 0.8 between the 200-year and 2000-year design rainfall events, specifically 4 % for the former and 9 % for the latter. Additionally, the results reveal a complex relationship between flood risk and resilience, though decreasing flood resilience generally leads to increasing flood risk. However, this relationship varies depending on the land cover type, with building, green land, and water body cells showing higher resilience for the same level of flood risk compared to other land uses such as roads and railways. Classifying urban areas into four categories, including high risk vs. low resilience, high risk vs. high resilience, low risk vs. low resilience, and low risk vs. high resilience, is crucial in identifying flood hotspots for intervention development. In conclusion, this study provides an in-depth understanding of the relationship between risk and resilience in urban flooding, which could help improve urban flood management. The proposed performance-based flood resilience metric and the findings from the case study of Waterloo in London could be valuable for decision-makers in developing effective flood management strategies in urban areas.
近年来，洪水风险评估和韧性已成为有效城市洪水管理的重要内容。尽管洪水韧性和风险是两个具有独特评估指标的截然不同的概念，但对于它们之间的关系缺乏定量分析和理解。本研究旨在在城市地区的网格单元层面上研究这种关系。为了评估高分辨率网格单元的洪水韧性，本研究提出了一种基于性能的洪水韧性指标，该指标是根据洪水持续时间和规模的系统性能曲线计算得出的。洪水风险被计算为最大洪水深度和概率的乘积，同时考虑了多个风暴事件。使用基于二维元胞自动机的模型 CADDIES 对英国伦敦滑铁卢的案例进行了分析，该模型由 270 万个网格单元（5m×5m）组成。结果表明，超过 2%的网格单元的风险值超过 1。此外，在 200 年和 2000 年设计降雨事件下，韧性值低于 0.8 的网格单元之间存在 5%的差异，具体而言，前者为 4%，后者为 9%。此外，研究结果揭示了洪水风险和韧性之间的复杂关系，尽管洪水韧性降低通常会导致洪水风险增加。然而，这种关系因土地覆盖类型而异，与道路和铁路等其他土地利用方式相比，建筑物、绿地和水体单元在相同的洪水风险水平下具有更高的韧性。将城市区域分为高风险与低韧性、高风险与高韧性、低风险与低韧性以及低风险与高韧性四类，对于确定干预发展的洪水热点至关重要。总之，本研究深入了解了城市洪水风险和韧性之间的关系，这有助于改善城市洪水管理。提出的基于性能的洪水韧性指标以及对伦敦滑铁卢案例的研究结果，可为决策者在城市地区制定有效的洪水管理策略提供有价值的参考。
