Dr. Li Hsin-Chi is currently a researcher in the Climate Change and Socio-Economic Division at the National Science and Technology Center for Disaster Reduction (NCDR). His primary work focuses on integrating multidisciplinary climate change impact assessment approaches and developing theoretical frameworks for risk adaptation, which are applied by both central and local governments in climate adaptation practice.
He also serves as an Associate Professor in the Department of Hydraulic Engineering at National Cheng Kung University, where he teaches courses on hydro-meteorological disaster risk reduction and adaptation. His research interests include the impacts of climate change on landslides, socio-economic loss assessment, social vulnerability analysis, and climate change adaptation strategies.
Probabilistic Flood Loss Risk Analysis under Climate Change Scenario
Jun-Jih Liou1, Yi-Hua Hsiao, Hsin-Chi Li1
1 National Science and Technology Center for Disaster Reduction. Taiwan.
Semi quantitative climate change flood risk indicators can identify areas and hotspots with relatively high flood risk under current and future conditions. However, determining appropriate risk reduction or adaptation strategies for high-risk areas, while simultaneously evaluating the feasibility and effectiveness of different adaptation portfolios, requires more advanced quantitative risk assessment approaches. These include, for example, the monetization of flood damage outcomes to enable cost–benefit analyses of alternative adaptation options. To achieve this objective, this study conducts a probabilistic flood loss risk analysis under climate change by integrating flood impact results from the SOBEK model with flood damage assessments from the Taiwan Loss Assessment System (TLAS). A flood event loss database is established, and Monte Carlo simulation techniques commonly used in probabilistic catastrophe risk analysis are applied to generate flood loss exceedance probability curves. This approach quantifies flood loss risk under warming scenarios and enables the examination of residual losses with and without adaptation measures, thereby providing a basis for assessing the effectiveness of adaptation strategies.