{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,6]],"date-time":"2026-03-06T06:02:12Z","timestamp":1772776932156,"version":"3.50.1"},"reference-count":92,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2024,4,16]],"date-time":"2024-04-16T00:00:00Z","timestamp":1713225600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Science Technology Department of Zhejiang Province","award":["2022C03107"],"award-info":[{"award-number":["2022C03107"]}]},{"name":"International Center for Collaborative Research on Disaster Risk Reduction (ICCRDRR)","award":["2022C03107"],"award-info":[{"award-number":["2022C03107"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>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.<\/jats:p>","DOI":"10.3390\/rs16081413","type":"journal-article","created":{"date-parts":[[2024,4,17]],"date-time":"2024-04-17T07:54:36Z","timestamp":1713340476000},"page":"1413","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["A Novel Flood Risk Analysis Framework Based on Earth Observation Data to Retrieve Historical Inundations and Future Scenarios"],"prefix":"10.3390","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4455-2600","authenticated-orcid":false,"given":"Kezhen","family":"Yao","sequence":"first","affiliation":[{"name":"Joint International Research Laboratory of Catastrophe Simulation and Systemic Risk Governance, Beijing Normal University, Zhuhai 519087, China"},{"name":"School of National Safety and Emergency Management, Beijing Normal University, Zhuhai 519807, China"},{"name":"Key Laboratory of Environmental Change and Natural Disaster, Ministry of Education, Beijing Normal University, Beijing 100875, China"},{"name":"Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3390-8264","authenticated-orcid":false,"given":"Saini","family":"Yang","sequence":"additional","affiliation":[{"name":"Joint International Research Laboratory of Catastrophe Simulation and Systemic Risk Governance, Beijing Normal University, Zhuhai 519087, China"},{"name":"School of National Safety and Emergency Management, Beijing Normal University, Zhuhai 519807, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhihao","family":"Wang","sequence":"additional","affiliation":[{"name":"Joint International Research Laboratory of Catastrophe Simulation and Systemic Risk Governance, Beijing Normal University, Zhuhai 519087, China"},{"name":"Key Laboratory of Environmental Change and Natural Disaster, Ministry of Education, Beijing Normal University, Beijing 100875, China"},{"name":"Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0732-4898","authenticated-orcid":false,"given":"Weihang","family":"Liu","sequence":"additional","affiliation":[{"name":"Key Laboratory of Environmental Change and Natural Disaster, Ministry of Education, Beijing Normal University, Beijing 100875, China"},{"name":"Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jichong","family":"Han","sequence":"additional","affiliation":[{"name":"School of National Safety and Emergency Management, Beijing Normal University, Zhuhai 519807, China"},{"name":"School of Systems Science, Beijing Normal University, Beijing 100875, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0009-0388-6250","authenticated-orcid":false,"given":"Yimeng","family":"Liu","sequence":"additional","affiliation":[{"name":"Joint International Research Laboratory of Catastrophe Simulation and Systemic Risk Governance, Beijing Normal University, Zhuhai 519087, China"},{"name":"Key Laboratory of Environmental Change and Natural Disaster, Ministry of Education, Beijing Normal University, Beijing 100875, China"},{"name":"Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ziying","family":"Zhou","sequence":"additional","affiliation":[{"name":"Joint International Research Laboratory of Catastrophe Simulation and Systemic Risk Governance, Beijing Normal University, Zhuhai 519087, China"},{"name":"School of National Safety and Emergency Management, Beijing Normal University, Zhuhai 519807, China"},{"name":"School of Systems Science, Beijing Normal University, Beijing 100875, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1605-7701","authenticated-orcid":false,"given":"Stefano Luigi","family":"Gariano","sequence":"additional","affiliation":[{"name":"National Research Council, Research Institute for Geo-Hydrological Protection (CNR IRPI), via della Madonna Alta 126, 06128 Perugia, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yongguo","family":"Shi","sequence":"additional","affiliation":[{"name":"Key Laboratory of Safety Engineering and Technology, Zhejiang Academy of Emergency Management Science, Hangzhou 310061, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Carlo","family":"Jaeger","sequence":"additional","affiliation":[{"name":"Global Climate Forum, 10178 Berlin, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2024,4,16]]},"reference":[{"key":"ref_1","unstructured":"EM-DAT (2022, October 04). 2022 Disasters in Numbers. 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