5:15 PM - 7:15 PM
[HTT15-P04] Integrating climate projections and impact mapping to evaluate future landslide risks in the Dahan River watershed, Taiwan
★Invited Papers
Keywords:Climate change, Impact map, Probability of landslide, Slope disasters
Landslides rank among the world’s deadliest natural hazards, and their frequency and severity are projected to increase under climate change. In Taiwan, where over 70% of the land consists of hillsides and steep terrains, the combination of fragile geology and intensified extreme rainfall from typhoons poses a significant threat of slope failures and subsequent disasters. This study evaluates future changes in landslide probability in the Dahan River watershed by integrating downscaled climate projections with a grid-based slope-stability analysis, ultimately providing a quantitative basis for community adaptation strategies.
Typhoon rainfall data were obtained from the Meteorological Research Institute of Japan (MRI) and dynamically downscaled using the Weather Research and Forecasting (WRF) model. The dataset encompasses 335 events, including 166 from the base period (1979–2003) and 169 projected events for the end of the 21st century (2075–2099). These data were incorporated into the Transient Rainfall Infiltration and Grid-Based Regional Slope-Stability (TRIGRS) model to simulate spatial variations in slope stability by calculating the factor of safety (FS) on a grid basis. Landslide probability for each slope unit was then defined as the ratio of typhoon events during which FS fell below the critical threshold of 1.0. Results indicate an average landslide probability of approximately 14.0% during the base period, which is projected to rise to 22.4% by the end of the century, particularly in areas upstream of the Shimen Reservoir.
To bridge scientific analysis with practical disaster risk management, the simulation outputs were further processed into an impact mapping framework. This tool categorizes slope units according to both current and future landslide probabilities, thereby highlighting hotspots and facilitating stakeholder engagement. Field interviews and discussions with local sediment management agencies and community representatives (e.g., in the Xiuluan Tribe area) underscored the utility of the impact map in promoting consensus on adaptation measures. The study concludes that employing such quantitative impact mapping is critical for informing both immediate and long-term adaptation strategies, including early warning systems and educational initiatives, aimed at mitigating the enhanced landslide risk driven by future climate change.
Typhoon rainfall data were obtained from the Meteorological Research Institute of Japan (MRI) and dynamically downscaled using the Weather Research and Forecasting (WRF) model. The dataset encompasses 335 events, including 166 from the base period (1979–2003) and 169 projected events for the end of the 21st century (2075–2099). These data were incorporated into the Transient Rainfall Infiltration and Grid-Based Regional Slope-Stability (TRIGRS) model to simulate spatial variations in slope stability by calculating the factor of safety (FS) on a grid basis. Landslide probability for each slope unit was then defined as the ratio of typhoon events during which FS fell below the critical threshold of 1.0. Results indicate an average landslide probability of approximately 14.0% during the base period, which is projected to rise to 22.4% by the end of the century, particularly in areas upstream of the Shimen Reservoir.
To bridge scientific analysis with practical disaster risk management, the simulation outputs were further processed into an impact mapping framework. This tool categorizes slope units according to both current and future landslide probabilities, thereby highlighting hotspots and facilitating stakeholder engagement. Field interviews and discussions with local sediment management agencies and community representatives (e.g., in the Xiuluan Tribe area) underscored the utility of the impact map in promoting consensus on adaptation measures. The study concludes that employing such quantitative impact mapping is critical for informing both immediate and long-term adaptation strategies, including early warning systems and educational initiatives, aimed at mitigating the enhanced landslide risk driven by future climate change.