5:15 PM - 7:15 PM
[HDS09-P11] Development of The Unstable Sediment Transport Model for Watersheds and Impact Assessment in Taiwan
Keywords:unstable sediment, RAMMS simulation, DS-InSAR , sub-Pixel Offset Tracking, Influenced area, landslide
In 2024, Typhoons Gaemi, Krathon, and Kong-rey successively impacted Taiwan, triggering landslides and debris flows within mountainous watershed regions and posing substantial risks to downstream villages and transportation infrastructure. While large-scale landslides and debris flows have been extensively studied, the behaviour and hazards associated with unstable sediment remain relatively unexplored. This study aims to develop a hazard assessment model for unstable sediment by integrating remote sensing technologies, a meteorological-rainfall-runoff model, and numerical simulations of sediment transport within six sub-watersheds of the Laonong River Basin in southern Taiwan.
The research methodology comprises the collection of historical disaster data, numerical analyses of terrain erosion and sedimentation, as well as soil sampling and mechanical analysis of riverbed materials. Given the extensive spatial coverage of the study area, a novel InSAR assessment approach is introduced alongside satellite imagery to monitor sediment dynamics on unstable slopes. Furthermore, six 24-hour cumulative rainfall scenarios (ranging from 200 mm to 900 mm) and an extreme rainfall scenario (1,500 mm) are employed. A distributed rainfall-runoff model is utilized to estimate flow distribution within the watersheds, while the RAMMS hydrograph method is applied to simulate the transport and deposition of unstable sediment.
Preliminary findings from InSAR and PIV analyses indicate that watersheds exhibiting higher slope displacement tendencies are associated with significantly increased sediment-related hazards for downstream villages and infrastructure. RAMMS simulations further demonstrate that greater cumulative rainfall exacerbates the impact of unstable sediment on these areas, with high-risk zones identified along riverbanks and at bridge and culvert crossings. By integrating remote sensing data with an unstable sediment transport assessment model, this study contributes to the development of a localized spatial distribution and hazard assessment framework for sediment-related disasters in Taiwan. The findings provide a scientific basis for evidence-based policy-making in disaster prevention and mitigation planning.
The research methodology comprises the collection of historical disaster data, numerical analyses of terrain erosion and sedimentation, as well as soil sampling and mechanical analysis of riverbed materials. Given the extensive spatial coverage of the study area, a novel InSAR assessment approach is introduced alongside satellite imagery to monitor sediment dynamics on unstable slopes. Furthermore, six 24-hour cumulative rainfall scenarios (ranging from 200 mm to 900 mm) and an extreme rainfall scenario (1,500 mm) are employed. A distributed rainfall-runoff model is utilized to estimate flow distribution within the watersheds, while the RAMMS hydrograph method is applied to simulate the transport and deposition of unstable sediment.
Preliminary findings from InSAR and PIV analyses indicate that watersheds exhibiting higher slope displacement tendencies are associated with significantly increased sediment-related hazards for downstream villages and infrastructure. RAMMS simulations further demonstrate that greater cumulative rainfall exacerbates the impact of unstable sediment on these areas, with high-risk zones identified along riverbanks and at bridge and culvert crossings. By integrating remote sensing data with an unstable sediment transport assessment model, this study contributes to the development of a localized spatial distribution and hazard assessment framework for sediment-related disasters in Taiwan. The findings provide a scientific basis for evidence-based policy-making in disaster prevention and mitigation planning.