A Novel Flood Risk Analysis Framework Based on Earth Observation Data to Retrieve Historical Inundations and Future Scenarios

作者：Kezhen Yao, Saini Yang, Zhihao Wang, Weihang Liu, Jichong Han, Yimeng Liu, Ziying Zhou, Stefano Luigi Gariano, Yongguo Shi, Carlo Jaeger · 发表于：Remote Sensing · 年份：2024 · DOI：10.3390/rs16081413 · 被引用次数：6 · 研究领域：Flood Risk Assessment and Management、Hydrology and Watershed Management Studies、Tropical and Extratropical Cyclones Research

Global warming is exacerbating flood hazards, making the robustness of flood risk management a critical issue. Without considering future scenarios, flood risk analysis built only on historical knowledge may not adequately address the coming challenges posed by climate change. A comprehensive risk analysis framework based on both historical inundations and future projections to tackle uncertainty is still lacking. In this view, a scenario-based, data-driven risk analysis framework that for the first time integrates recent historical floods and future risk trends is here presented, consisting of flood inundation-prone and high-risk zones. Considering the Poyang Lake Eco-Economic Zone (PLEEZ) in China as the study area, we reproduced historical inundation scenarios of major flood events by using Sentinel-1 imagery from 2015 to 2021, and used them to build the risk baseline model. The results show that 11.7% of the PLEEZ is currently exposed to the high-risk zone. In the SSP2-RCP4.5 scenario, the risk would gradually decrease after peaking around 2040 (with a 19.3% increase in high-risk areas), while under the traditional fossil fuel-dominated development pathway (SSP5-RCP8.5), the risk peak would occur with a higher intensity about a decade earlier. The attribution analysis results reveal that the intensification of heavy rainfall is the dominant driver of future risk increase and that the exploitation of unused land such as wetlands induces a significant increase in risk. Fina...