Changes in Runout Distances of Debris Flows over Time in the Wenchuan Earthquake Zone

A large number of debris flows occurred in the Wenchuan earthquake zone after the 12 May 2008 earthquake.The risks posed by these debris flows were rather high.An appropriate model is required to predict the possible runout distance and impacted area.This paper describes a study on the runout characteristics of the debris flows that occurred in the Wenchuan earthquake zone over the past four years.A total of 120 debris flows are analyzed.Separate multivariate regression models are established for the runout distances of hill-slope debris flows and channelized debris flows.The control variables include type of debris flow,debris flow volume,and elevation difference.Comparison of the debris flows occurring before and after the earthquake shows that the runout distance increased after the earthquake due to sufficient material supply and increased mobility of the source materials.In addition,the runout distances of annual debris flow events in 2008,2010 and 2011 are analyzed and compared.There is a tendency that the runout distance decreases over time due to the decreasing source material volume and possible changes of debris flow type.Comparison between the debris flows in the earthquake zone and the debris flows in Swiss Alps,Canada,Austria,and Japan shows that the former have a smaller mobility.

Hybrid Simulation of the Initiation and Runout Characteristics of a Catastrophic Debris Flow

On 13 August 2010, a catastrophic debris flow with a volume of 1.17 million m3 occurred in Xiaojiagou Ravine near Yingxiu town of Wenchuan county in Sichuan Province, China. The main source material was the landslide deposits retained in the ravine during the 2008 Wenchuan earthquake. This paper describes a two-dimensional hybrid numerical method that simulates the entire process of the debris flow from initiation to transportation and finally to deposition. The study area is discretized into a grid of square zones. A two dimensional finite difference method is then applied to simulate the rainfall-runoff and debris flow runout processes. The analysis is divided into three steps; namely, rainfall-runoff simulation, mixing water and solid materials, and debris flow runout simulation. The rainfall-runoff simulation is firstly conducted to obtain the cumulative runoff near the location of main source material and at the outlet of the first branch. The water and solid materials are then mixed to create an inflow hydrograph for the debris flow runout simulation. The occurrence time and volume of the debris flow can be estimated in this step. Finally the runout process of the debris flow is simulated. When the yield stress is high, it controls the deposition zone. When the yield stress is medium or low, both yield stress and viscosity influence the deposition zone. The flow velocity is largely influenced by the viscosity. The estimated yield stress by the equation, ty = pghsinO, and the estimated viscosity by the equation established by Bisantino et al. （2010） provide good estimates of the area of the debris flow fan and the distribution of deposition depth.

An AI‑Based Method for Estimating the Potential Runout Distance of Post‑Seismic Debris Flows

The widely distributed sediments following an earthquake presents a continuous threat to local residential areas and infrastructure. These materials become more easily mobilized due to reduced rainfall thresholds. Before establishing an effective management plan for debris flow hazards, it is crucial to determine the potential reach of these sediments. In this study, a deep learning-based method-Dual Attention Network(DAN)-was developed to predict the runout distance of potential debris flows after the 2022 Luding Earthquake, taking into account the topography and precipitation conditions. Given that the availability of reliable precipitation data remains a challenge, attributable to the scarcity of rain gauge stations and the relatively coarse resolution of satellite-based observations, our approach involved three key steps. First, we employed the DAN model to refine the Global Precipitation Measurement(GPM) data, enhancing its spatial and temporal resolution. This refinement was achieved by leveraging the correlation between precipitation and regional environment factors(REVs) at a seasonal scale. Second, the downscaled GPM underwent calibration using observations from rain gauge stations. Third,mean absolute error(MAE), mean square error(MSE), and root mean square error(RMSE) were employed to evaluate the performance of both the downscaling and calibration processes. Then the calibrated precipitation, catchment area, channel length, average channel gradient, and sediment volume were selected to develop a prediction model based on debris flows following the Wenchuan Earthquake. This model was applied to estimate the runout distance of potential debris flows after the Luding Earthquake. The results show that:(1) The calibrated GPM achieves an average MAE of 1.56 mm, surpassing the MAEs of original GPM(4.25 mm) and downscaled GPM(3.83 mm);(2) The developed prediction model reduces the prediction error by 40 m in comparison to an empirical equation;(3) The potential runout distance of debris flows after the Luding Earthquake reaches 0.77 km when intraday rainfall is 100 mm, while the minimum distance value is only 0.06 km.Overall, the developed model offers a scientific support for decision makers in taking reasonable measurements for loss reduction caused by post-seismic debris flows.

Rapid prediction models for 3D geometry of landslide dam considering the damming process

The geometry of a landslide dam plays a critical role in its stability and failure mode,and is influenced by the damming process.However,there is a lack of understanding of the factors that affect the 3D geometry of a landslide dam.To address this gap,we conducted a study using the smoothed particle hydrodynamics numerical method to investigate the evolution of landslide dams.Our study included 17 numerical simulations to examine the effects of several factors on the geometry of landslide dams,including valley inclination,sliding angle,landslide velocity,and landslide mass repose angle.Based on this,three rapid prediction models were established for calculating the maximum height,the minimum height,and the maximum width of a landslide dam.The results show that the downstream width of a landslide dam remarkably increases with the valley inclination.The position of the maximum dam height along the valley direction is independent of external factors and is always located in the middle of the landslide width area.In contrast,that position of the maximum dam height across the valley direction is significantly influenced by the sliding angle and landslide velocity.To validate our models,we applied them to three typical landslide dams and found that the calculated values of the landslide dam geometry were in good agreement with the actual values.The findings of the current study provide a better understanding of the evolution and geometry of landslide dams,giving crucial guidance for the prediction and early warning of landslide dam disasters.

Numerical analysis of submarine landslides using a smoothed particle hydrodynamics depth integral model

Submarine landslides can cause severe damage to marine engineering structures. Their sliding velocity and runout distance are two major parameters for quantifying and analyzing the risk of submarine landslides.Currently, commercial calculation programs such as BING have limitations in simulating underwater soil movements. All of these processes can be consistently simulated through a smoothed particle hydrodynamics（SPH） depth integrated model. The basis of the model is a control equation that was developed to take into account the effects of soil consolidation and erosion. In this work, the frictional rheological mode has been used to perform a simulation study of submarine landslides. Time-history curves of the sliding body＇s velocity, height,and length under various conditions of water depth, slope gradient, contact friction coefficient, and erosion rate are compared; the maximum sliding distance and velocity are calculated; and patterns of variation are discussed.The findings of this study can provide a reference for disaster warnings and pipeline route selection.