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Modeling of Water-Sediment Inundation Process Incorporating with a Rainfall- Sediment Runoff Model

Author(s): Menglu Qin; Daisuke Harada; Shinji Egashira

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Keywords: Water-sediment inundation prediction; Landslides and debris flows; Multi-hazards; Rainfall and sediment runoff; Sediment transport process

Abstract: Water-sediment inundation, often observed in plain areas during torrential rainfall, is caused by the rapid deposition of large amounts of sediment carried by floodwaters from mountain streams. This sediment is typically supplied by landslides and debris flows. This study aims to improve the prediction accuracy of water- sediment inundation hazard by integrating a catchment-scale rainfall and sediment runoff model, which includes slope stability analysis for landslide prediction and a point mass system for debris flow runout, with a depth-integrated two-dimensional flow and sediment transport model. This approach allows the proposed method to predict the real-time updates of upstream boundary conditions for the 2-D water-sediment inundation analysis in plain areas. The method was applied to simulate such multi-hazards in the Uchi River Basin (89km2) Japan, during Typhoon Hagibis in October 2019. The simulation results, validated against observed data, included predictions of landslide and debris flow occurrence and distribution, sediment budgets within the catchment, and the deposition depth, and sediment size resulting from the drastic sedimentation of inundation flows. The results show that sediment produced by landslides and debris flows is partly stored in the riverbed and remains on the mountain slopes, indicating that these event-based hazards can have long-term effects. The results also reveal that water-sediment inundation risk is particularly high in small tributaries, where sediment inflows during torrential rainfall events often significantly exceed the channel capacity. These results demonstrate the effectiveness of our method in predicting multi-sediment-flood hazards across the catchment and provide detailed insights into the characteristics of these hazards.

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Year: 2024

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