Characteristics and dynamic analysis of the February 2021 long-runout disaster chain triggered by massive rock and ice avalanche at Chamoli, Indian Himalaya

A massive rock and ice avalanche occurred on the western slope of the Ronti Gad valley in the northern part of Chamoli,Indian Himalaya,on 7 February 7,2021.The avalanche on the high mountain slope at an elevation of 5600 m above sea level triggered a long runout disaster chain,including rock mass avalanche,debris avalanche,and flood.The disaster chain had a horizontal travel distance of larger than 17,600 m and an elevation difference of 4300 m.In this study,the disaster characteristics and dynamic process were analyzed by multitemporal satellite imagery.The results show that the massive rock and ice avalanche was caused by four large expanding discontinuity planes.The disaster chain was divided into five zones by satellite images and field observation,including source zone,transition zone,dynamic entrainment zone,flow deposition zone,and flood zone.The entrainment effect and melting water were recognized as the main causes of the long-runout distance.Based on the seismic wave records and field videos,the time progress of the disaster was analyzed and the velocity of frontal debris at different stages was calculated.The total analyzed disaster duration was 1247 s,and the frontal debris velocity colliding with the second hydropower station was approximately 23 m/s.This study also carried out the numerical simulation of the disaster by rapid mass movement simulation(RAMMS).The numerical results reproduced the dynamic process of the debris avalanche,and the mechanism of long-runout avalanche was further verified by parametric study.Furthermore,this study discussed the potential causes of disaster and flood and the roles of satellite images and seismic networks in the monitoring and early-warning.

A catastrophic natural disaster chain of typhoon-rainstorm-landslide-barrier lake-flooding in Zhejiang Province, China

On August 10,2019,due to the effect of a rainstorm caused by Super Typhoon Lekima,a landslide occurred in Shanzao Village,China.It blocked the Shanzao stream,forming a barrier lake,and then the barrier lake burst.This is a rare natural disaster chain of typhoon-rainstorm-landslide-barrier lake-flooding.This study was built on field surveys,satellite image interpretation,the digital elevation model(DEM),engineering geological analysis and empirical regression.The purpose was to reveal the characteristics and causes of the landslide,the features and formation process of the barrier lake and the dam break flooding discharge.The results show that the volume of the landslide deposit is approximately 2.4×105 m3.The burst mode of the landslide dam is overtopping,which took only 22 minutes from the formation of the landslide dam to its overtopping.The dam-break peak flow was 1353 m3/s,and the average velocity was 2.8–3.0 m/s.This study shows that the strongly weathered rock and soil slope has low strength and high permeability under the condition of heavy rainfall,which reminds us the high risk of landslides and the importance of accurate early warning of landslides under heavy rainfalls in densely populated areas of Southeast China,as well as the severity of the disaster chain of typhoon-rainstorm-landslide-barrier lake-flooding.

A TPDP-MPM-based approach to understanding the evolution mechanism of landslide-induced disaster chain

With complex topographic and hydrological characteristics,the landslide-induced surge disaster chain readily develops in mountainous and gorge areas,posing a huge challenge for infrastructure construction.This landslide-induced surge disaster chain involves a complex fluid-solid coupling between the landslide mass and a water body and exhibits complex energy conversion and dissipation characteristics,which is challenging to deal with using traditional finite element analysis.In this study,the energy evolution characteristics in the whole process of the disaster chain were first investigated,and the momentum-conservation equations for different stages were established.Then,the two-phase doublepoint material point method(TPDP-MPM)was used to model the landslide-induced surge disaster chain,and an experiment involving block-induced surge was modeled and simulated to validate this method.Finally,three generalized models were established for the landslide-induced surge process in a U-shaped valley,including subaerial,partly submerged,and submarine scenarios.The interaction mechanism between the landslide mass and the water body in the disaster chain was revealed by defining the system energy conversion ratio and the mechanism of evolution of the disaster chain from the perspective of energy.The results help further evaluate the secondary disasters,given the submerged position of the landslide mass.

Interaction Mechanism between Formation Process of Bank Collapse Disaster Chain and Territorial Space Utilization of Large Reservoirs

Number of reservoirs in China ranks the first in the world. Due to the complex geology, and superimposing rainfall and reservoir water fluctuation, the bank collapse chain is prone to disasters. The Yangtze River Reservoir is key geological disaster prevention area. Studying the process of reservoir disaster is significant because of the limited territorial space utilization. Scientific and technological issues, i.e., the mechanism of bank collapse disaster chain of large reservoirs, the interaction mechanism of bank collapse disaster chain and territorial space utilization, the early identification, monitoring technology and ecological prevention and control technology system of disaster chain, and the territorial space geological safety and control technology system are focused. We consider the material transformation, energy transfer and information transmission in disaster chain;adopt the survey, Space-Air-Ground integrated monitoring, theoretical analysis, numerical simulation and the multidisciplinary research methods;reveal the chain source development, evolution process of secondary and derivative disasters;explore the interaction mechanism of disaster chain and territorial space utilization;construct the system of early identification, monitoring, early warning, control and ecological preven-tion to achieve Emission Peak and Carbon Neutrality;provide theoretical and technical support for the territorial space geological safety, regulation and utilization of large reservoirs.

Characteristics of loess landslides triggered by different factors in the Chinese Loess Plateau

Loess landslides are one of the most serious geological disasters in the Chinese Loess Plateau.Research has revealed that earthquake,rainfall,and human activities are common triggers for loess landslides.In order to study the relationship and characteristics of these landslides triggered by different factors,the paper uses historic landslide data to expound the basic motion indices of landslides triggered by different factors.More than half of loess landslides occurred on concave surface slopes,while nearly 40%of the loess landslides occurred on convex surface slopes.Human activities have a great effect on the occurrence of landslides,and the distribution density of landslides on residential land was almost five times that of bare land.Additionally,earthquakeinduced loess landslides had the largest sliding volume,whereas the excavation-induced loess landslide had the smallest sliding volume.The sliding volume of irrigation-induced and rainfall-induced loess landslides were between earthquake-induced loess landslides and excavation-induced loess landslide.Many of loess landslides were induced by a combination of these factors,such as rainfall and excavation,irrigation and excavation.Then a model that described the impact of these factors on the loess landslides was proposed.

Reasoning Disaster Chains with Bayesian Network Estimated Under Expert Prior Knowledge

With the acceleration of global climate change and urbanization,disaster chains are always connected to artificial systems like critical infrastructure.The complexity and uncertainty of the disaster chain development process and the severity of the consequences have brought great challenges to emergency decision makers.The Bayesian network(BN)was applied in this study to reason about disaster chain scenarios to support the choice of appropriate response strategies.To capture the interacting relationships among different factors,a scenario representation model of disaster chains was developed,followed by the determination of the BN structure.In deriving the conditional probability tables of the BN model,we found that,due to the lack of data and the significant uncertainty of disaster chains,parameter learning methodologies based on data or expert knowledge alone are insufficient.By integrating both sample data and expert knowledge with the maximum entropy principle,we proposed a parameter estimation algorithm under expert prior knowledge(PEUK).Taking the rainstorm disaster chain as an example,we demonstrated the superiority of the PEUK-built BN model over the traditional maximum a posterior(MAP)algorithm and the direct expert opinion elicitation method.The results also demonstrate the potential of our BN scenario reasoning paradigm to assist real-world disaster decisions.

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.

Discovering the relationship of disasters from big scholar and social media news datasets

The construction method for chains of disasters or events is still one of the core scientific questions in studying the common rules of disaster’s evolution.Especially when dealing with the complexity and diversity of disasters,it is critical to make a further investigation on reducing the dependency of prior knowledge and supporting the comprehensive chains of disasters.This paper tries to propose a novel approach,through collecting the big scholar and social news data with disasterrelated keywords,analysing the strength of their relationships with the co-word analysis method,and constructing a complex network of all defined disaster types,in order to finally intelligently extract the unique disaster chain of a specific disaster type.Google Scholar,Baidu Scholar and Sina News search engines are employed to acquire the needed data,and the respectively obtained disaster chains are compared with each other to show the robustness of our proposed approach.The achieved disaster chains are also compared with the ones concluded from existing research methods,and the very reasonable result is demonstrated.There is a great potential to apply this novel method in disaster management domain to find more secrets about disasters.

Toward Interoperable Multi‑hazard Modeling: A Disaster Management System for Disaster Model Service Chain

A natural hazard-related disaster event often causes a series of secondary disasters, forming a disaster chain. Modeling the evolution of disaster chains in multihazard scenarios is crucial for risk governance and urban resilience. However, existing multi-hazard models are limited by complex model design and fixed disaster types, making it impossible to ensure flexible reactions to complex and diverse scenarios. This study presents a disaster management system for disaster model service chain(DMSC) to implement interoperable multi-hazard modeling. To achieve efficient model interaction in the DMSC, a management module is designed to normalize heterogeneous single-hazard models based on disaster system theory and the Open Geospatial Consortium standards, enabling them to be accessible,reusable, and interoperable. The normalized models are then adaptively orchestrated through an orchestration module to establish optimal executable DMSCs for different multihazard scenarios. Taking an earthquake disaster chain as a case study, we demonstrate that the disaster management system shows stable and flexible performance for multihazard modeling.

Risk assessment of large-scale winter sports sites in the context of a natural disaster

Accidents induced by natural disasters at sports sites may cause catastrophic loss of great concern.However,previous studies on risk assessments of sports sites have only focused on operational risk and equipment failure.With the frequent occurrence of extreme disasters,the risk of domino chains caused by natural disasters at large-scale events,such as large-scale winter sports sites,cannot be ignored.In this study,a natural disaster-induced accident-chain evolution analysis model(NAEA model)is proposed.Based on the results of the NAEA model,a fuzzy Bayesian network for domino accidents triggered by an earthquake at large-scale winter sports sites was established.Through sensitivity analysis and scenario analysis,it was found that fire and explosion accidents and crowded stampede accidents are the main causes of serious loss in domino disaster chains in large-scale sports sites.Simultaneously,improving the early warning capability,reliability of electrical equipment,and automatic sprinkler systems are the most effective ways to prevent and control major accidents.In addition,an optimal safety strategy improvement analysis was performed to facilitate the decision-making of safety managers to prevent serious accidents and reduce accident loss.