Economic Risk Assessment of Future Debris Flows by Machine Learning Method

A reliable economic risk map is critical for effective debris-flow mitigation.However,the uncertainties surrounding future scenarios in debris-flow frequency and magnitude restrict its application.To estimate the economic risks caused by future debris flows,a machine learning-based method was proposed to generate an economic risk map by multiplying a debris-flow hazard map and an economic vulnerability map.We selected the Gyirong Zangbo Basin as the study area because frequent severe debris flows impact the area every year.The debris-flow hazard map was developed through the multiplication of the annual probability of spatial impact,temporal probability,and annual susceptibility.We employed a hybrid machine learning model-certainty factor-genetic algorithm-support vector classification-to calculate susceptibilities.Simultaneously,a Poisson model was applied for temporal probabilities,while the determination of annual probability of spatial impact relied on statistical results.Additionally,four major elements at risk were selected for the generation of an economic loss map:roads,vegetation-covered land,residential buildings,and farmland.The economic loss of elements at risk was calculated based on physical vulnerabilities and their economic values.Therefore,we proposed a physical vulnerability matrix for residential buildings,factoring in impact pressure on buildings and their horizontal distance and vertical distance to debrisflow channels.In this context,an ensemble model(XGBoost) was used to predict debris-flow volumes to calculate impact pressures on buildings.The results show that residential buildings occupy 76.7% of the total economic risk,while roadcovered areas contribute approximately 6.85%.Vegetation-covered land and farmland collectively represent 16.45% of the entire risk.These findings can provide a scientific support for the effective mitigation of future debris flows.

Risk Assessment of Debris Flows Along the Karakoram Highway (Kashgar‑Khunjerab Section) in the Context of Climate Change

The Karakoram highway(KKH)is renowned for its complex natural environment and geological conditions.The climate changes drastically and directly infuences the frequency and magnitude of debris fows in this region,resulting in signifcant casualties and economic losses.However,the risk assessment of debris fows along the KKH in the context of climate change has been rarely explored.Therefore,in this study we used the debris fow data,historical meteorological data and future climate prediction data to assess the debris fow risk of the study region during the baseline period(2009–2018),2025s(2021–2030),2035s(2031–2040)and 2045s(2041–2050)under the Representative Concentration Pathway 8.5 scenario.The results show that the risk of debris fows increases with climate change,with the highest risk level in the 2025s.Among diferent parts of this highway,the upper reaches of the Ghez River and the second half of Tashkorgan-Khunjerab are the sections with the highest risk.These fndings are helpful for debris fow prevention and can ofer coping strategies for the existing line of the KKH.They also provide some reference for the renovation,improvement,operation,and maintenance of the KKH.

Assessment of Building Physical Vulnerability in Earthquake‑Debris Flow Disaster Chain

Large earthquakes not only directly damage buildings but also trigger debris fows,which cause secondary damage to buildings,forming a more destructive earthquake-debris fow disaster chain.A quantitative assessment of building vulnerability is essential for damage assessment after a disaster and for pre-disaster prevention.Using mechanical analysis based on pushover,a physical vulnerability assessment model of buildings in the earthquake-debris fow disaster chain is proposed to assess the vulnerability of buildings in Beichuan County,China.Based on the specifc sequence of events in the earthquake-debris fow disaster chain,the seismic vulnerability of buildings is 79%,the fow impact and burial vulnerabilities of damaged buildings to debris fow are 92%and 28%respectively,and the holistic vulnerability of buildings under the disaster chain is 57%.By comparing diferent vulnerability assessment methods,we observed that the physical vulnerability of buildings under the disaster chain process is not equal to the statistical summation of the vulnerabilities to independent hazards,which implies that the structural properties and vulnerability of buildings have changed during the disaster chain process.Our results provide an integrated explanation of building vulnerability,which is essential for understanding building vulnerability in earthquake-debris fow disaster chain and building vulnerability under other disaster chains.

Efects of Tectonic Setting and Hydraulic Properties on Silent Large‑Scale Landslides: A Case Study of the Zhaobishan Landslide,China

Unlike strong earthquake-triggered or heavy rainfall-triggered landslides,silent large-scale landslides(SLL)occur without signifcant triggering factors and cause unexpected signifcant disaster risks and mass casualties.Understanding the initiation mechanism of SLLs is crucial for risk reduction.In this study,the mechanism of the Zhaobishan SLL was investigated,and the SLL was jointly controlled by weak-soil(fractured rock mass)and strong-water(abundant water replenishment)conditions under the impact of active tectonism and complex hydraulic properties.Strong tectonic uplift,high fault density,and historical earthquakes led to weak-soil conditions conducive to the Zhaobishan SLL.The combined efect of unique lithology,antiform,and cultivated land contributed to the water replenishment characteristics of extensive runof confuence(3.16 times that of the landslide body)and supported long-distance groundwater replenishment,thereby forming strongwater conditions for the landslide.The amplifed seepage amount caused the strength of the soil mass on the sliding surface to decrease to 0.4 times its initial strength,eventually triggering the Zhaobishan SLL,which occurred 4.6 days after the peak rainfall.Moreover,the landslide deposits have accumulated on the semi-diagenetic clay rock,thereby controlling the subsequent recurring debris fows in the Lengzi Gully.To reduce disaster risk of SLL in vulnerable mountainous regions,the water confuence area behind the main scarp of the landslides and the hysteresis characteristics between landslides and peak rainfall should be further considered,and recurring debris fows following massive landslides also should be focused.