当前位置：
X-MOL 学术
›
Remote Sens.
›
论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
A Novel Flood Risk Analysis Framework Based on Earth Observation Data to Retrieve Historical Inundations and Future Scenarios
Remote Sensing ( IF 5 ) Pub Date : 2024-04-16 , DOI: 10.3390/rs16081413 Kezhen Yao 1, 2, 3, 4 , Saini Yang 1, 2 , Zhihao Wang 1, 3, 4 , Weihang Liu 3, 4 , Jichong Han 2, 5 , Yimeng Liu 1, 3, 4 , Ziying Zhou 1, 2, 5 , Stefano Luigi Gariano 6 , Yongguo Shi 7 , Carlo Jaeger 8
Remote Sensing ( IF 5 ) Pub Date : 2024-04-16 , DOI: 10.3390/rs16081413 Kezhen Yao 1, 2, 3, 4 , Saini Yang 1, 2 , Zhihao Wang 1, 3, 4 , Weihang Liu 3, 4 , Jichong Han 2, 5 , Yimeng Liu 1, 3, 4 , Ziying Zhou 1, 2, 5 , Stefano Luigi Gariano 6 , Yongguo Shi 7 , Carlo Jaeger 8
Affiliation
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. Finally, a hierarchical panel of recommended management measures was developed. We hope that our risk analysis framework inspires newfound risk awareness and provides the basis for more effective flood risk management in river basins.
更新日期：2024-04-16
京公网安备 11010802027423号