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Emergency decision-making is vital for nations or communities because it increases emergency management's effectiveness and legitimacy, which in turn greatly minimizes environmental damage, fatalities, and economic loss. The evaluation of emergency judgements must take into account significant inaccuracy, fuzzyness, and ambiguity. While high risk and uncertainty are frequently characteristics of emergency decision-making (EDM) circumstances. The current EDM methodologies do not take into account the psychological behavior of the decision makers in addition to the various emergency situations and the various responses. In this paper, we presented a new method based on a Complex Probabilistic Hesitant Fuzzy Soft Set (CPHFSS) as represented by membership in 2-D with hesitant probability. The idea that is being put forth captures the ambiguity and takes into account emergency situations while also taking into account the psychological state of the decision-makers involved in the EDM procedure. The introduction of a new score function for the CPHFSS serves as the second objective of this paper, which is to address a number of comparability issues. We examine a novel family of hybrid operators for CPHFSS that utilize numerous independent variables as a solution to these unforeseen issues. The group decision-making strategy and EDAS technique are then suggested employing these operators. Later, an emergency decision-making situation involving a major fire in China is used to demonstrate the validity of the algorithms. • Concept of complex probabilistic hesitant fuzzy soft set is presented. • Introduce a new score function for the CPHFSS. • Group decision-making strategy and EDAS technique presented. • Emergency decision-making problems discussed in the study. • Case study related to industrial disaster emergency decision-making discuss. [ABSTRACT FROM AUTHOR]

Emergency supplies pre-positioning is crucial to improve the speed of response and mitigate the effects of disasters. According to the requirements of emergency preparedness for both civilian and military operations in China, the paper presents a problem of integrated civilian–military emergency supplies pre-positioning, the aim of which is to maximize both the expected military operational efficiency and the expected civilian operational efficiency while minimizing the overall cost of pre-positioning. To solve the problem, the paper proposes a solution method that uses a multiobjective algorithm to evolve a population of main location solutions and uses another single-objective algorithm to search optimal allocation sub-solutions for each main solution. Among different heuristics, we select water wave optimization (WWO) to design a multiobjective algorithm for the main problem and select biogeography-based optimization (BBO) for the subproblem, and demonstrate that they have competitive performance advantage in comparison with a set of well-known algorithms. [ABSTRACT FROM AUTHOR]

In China, the occurrence of a series of disasters and the tremendous loss in human lives expose the vulnerability the emergency system and the incomplete of the methodology. Faced with the needs of the practice, this paper conducted a comprehensive review both from the system and the methodology prospective. From the system prospective, this paper aims at analyzing the existing problems and the solution finding. From the methodology prospective, emergency facility location problem, emergency resource allocation problem, and emergency management technical support problem are examined. [ABSTRACT FROM AUTHOR]

Steel lattice towers are commonly used as supporting structures for overhead transmission lines. Extreme wind conditions like typhoons can cause significant damage on those steel towers and consequently jeopardize the safe operation of transmission lines. In the line sections where a river crossing is unavoidable, the steel lattice towers are designed to be much taller and stronger than regular towers owing to safety and operation considerations. In previous typhoon events in Hainan Province of China, none of the installed river-crossing towers have collapsed or experienced significant damages, except in the aftermath of super typhoon Rammasun in 2014, when two 95-m tall river-crossing suspension towers collapsed. This paper presents the structural failure analysis of these two collapsed lattice steel transmission towers: The improved genetic algorithm (IGA) was applied to solve the typhoon wind field model for improved resolution of wind records measured during the Rammasun event and based on of 10-min average wind speeds. The IGA used the field measurement data to generate time-varying typhoon key parameters that lead to a more accurate prediction of the wind field than the conventional method. Then a systematic procedure was developed to investigate the failure mechanism of steel lattice towers under fluctuating wind loads combined with rain loads with consideration of the aerodynamic characteristics of the transmission tower-line system. The results show that the root-cause of the structural failure of the two transmission towers was overstressing of the tower main leg members in the second panel above the ground. Based on the numerical simulation of typhoon wind loads and the structural failure analysis procedure applied in this study, a general reinforcement method of river-crossing towers is proposed and the implementation of a typhoon warning method is recommended to identify the potential risks in transmission lines and formulate corresponding typhoon emergency plans to reduce the losses caused by typhoons. • The failure of a river-crossing transmission line damaged by typhoon is analyzed. • Improved genetic algorithm (IGA) method was innovatively introduced to solve the typhoon wind filed. • Fluctuating characteristic and strong rainfall led to the tower collapse. • A new transmission line typhoon warning method is proposed. [ABSTRACT FROM AUTHOR]

Floods pose significant threats to farmers, and engaging in effective disaster avoidance behaviors can mitigate some of these risks for farmers in flood risk areas (FRA). However, due to farmers' bounded rationality characteristics, they often have a cognitive bias of blindly overestimating or underestimating flood risk, thus failing to perform correct disaster avoidance behaviors. Based on survey data from 180 farmers in FRA in southwest China, this study constructs an assessment method for farmers' subjective and objective flood risk and analyzes the characteristics of farmers' subjective and objective flood risk. A probit regression model explores the correlation between subjective and objective flood risk consistency and farmers' willingness to purchase natural disaster insurance (WPNDI). Results showed that of the 180 farmers surveyed, 63.89% had inconsistent subjective and objective flood risks, mainly reflected in an underestimation of objective flood risk. Farmers' subjective and objective flood risk consistency was found to be positively and significantly correlated with their WPNDI. When other conditions remain unchanged, for every unit increase in the consistency of farmers' subjective and objective flood risk, their WPNDI increased by 0.601 units on average. This paper originally proposed the hypothesis that the consistency of farmers' subjective and objective flood risk is positively and significantly correlated with their WPNDI, and proved the reliability of this hypothesis through research. These findings can provide policy references for disaster risk management and resilient disaster prevention system construction in FRA. [Display omitted] • The subjective and objective flood risk of farmers in FRA is assessed. • The correlation between farmers' subjective and objective flood risk consistency and WPNDI is analyzed by probit model. • Inconsistency of farmers' subjective and objective flood risk mainly reflected in underestimating the objective flood risk. • Farmers' subjective and objective flood risk consistency is positively and significantly correlated with their WPNDI. [ABSTRACT FROM AUTHOR]

• Built the storm surge disaster dataset with 50 indicators and 132 events. • Scientific data preprocessing methods ensure the reliability of the model. • Rank the importance of 50 indicators; hazard indicators are more important. • The indicator screening renders model simplification and workload reduction. • Satisfy machine learning models of storm surge disaster loss estimation are obtained. Storm surge is the most severe marine disaster in China, affecting the whole coastal area. Estimating storm surge disaster loss (SSDL) is significant to disaster prevention, sustainability and decision-making. Taking 11 provincial administrative regions in the coastal areas of China as the study area, this paper estimated SSDL grades based on four machine learning (ML) algorithms. A total of 132 pieces of official open-source data of storm surge disasters were collected and divided into a cross-validation set (CV set) and a test set. First, a comprehensive indicator system was constructed from three perspectives, covering the hazard (16) of disaster-causing factors, the vulnerability (22) and resilience (12) of disaster-bearing bodies, including 50 indicators. A few data preprocessing methods are implemented to improve the model performance such as normalization, SMOTE, etc. Then, Random Forest (RF), eXtreme Gradient Boosting (XGBoost), Logistic model tree (LMT), and K-star were applied to construct the estimation model of SSDL grades. Principal component analysis (PCA) and recursive feature elimination (RFE) are adopted for an intelligent screening of the indicators. Finally, the models' performance is compared through Precision, Recall, F1 score and Kappa metrics. The results show that scientific and efficient data preparation is a strong guarantee for the reliability and stability of the models. RFE is verified more suitable for indicator selection in this paper compared with PCA. The importance ranking of RFE enhances the interpretability of the ML model, which shows that the hazard indicator is the most important, the vulnerability indicator is the second, and the resilience indicator is the least. The 27-indicator K-star model, with advantages of accurate estimation, strong generalization, and less workload, is the optimal SSDL estimation model. The number of input indicators of the optimal SSDL estimation model is 27, its CV Precision, Recall, F1 score, and Kappa are 0.838, 0.832, 0.827, and 0.776, and its Precision, Recall, F1 score, and Kappa for test set are 0.819, 0.786, 0.781, and 0.714, respectively. This paper provides a scientific basis for the government's decision-making and risk management, and it can be used as a typical demonstration case of SSDL research. [ABSTRACT FROM AUTHOR]

Abstract: In China, the land availability for urban development is reducing progressively. The trend of construction of inter-city railway stations is moving towards underground structures in order to save space. This paper has posed a discussion on means of egress in an underground railway station. Due to the lack of specific guidance on design of underground inter-city railway (UIR) station, current design in China mainly refers to the Code for design of metro (GB50157-2003). The design Code provides an approach for calculation of the platform evacuation time in case of an emergency; especially it requires a safe egress from the most remote point on the platform in 6minutes or even less. As the differences between metro station and UIR station, including the type of trains, passenger flow, waiting mode, etc., this paper also discusses the validity of the approaches for calculating the egress time provided by Metro Design Code.In the meantimerecommendations are given on equation for calculating the platform evacuation time when considering design of egress in an UIR station. A feasibility analysis on this engineering approach has been carried out in accordance of an under construction project, the UIR stations on an intercity express rail link in Hunan province together with STEPS evacuation model. [Copyright &y& Elsevier]

Abstract: With the urban rail transit network in Beijing becoming gradually intensive, the passenger flow organization also develops towards the type of the network mode. This paper analyzes the development trend of the urban rail transit network in Beijing. On the basis of a reasonable classification of emergencies occurred in urban rail transit, this paper puts forward the passenger organization model of rail transit network under emergency conditions, and then set a certain train accident of Beijing Metro Line 1 as an example to illustrate the practical application of the passenger emergency organization mode. [Copyright &y& Elsevier]

Abstract: This paper first defines the term “urban fire risk” by referring to both the definition of “risk” in U.N.’s “International Strategy for Disaster Reduction” which was enacted in 2004 and the features of urban fire. Secondly, this paper presents a comprehensive analysis on the urban fire risk from the respects of risk of fire accidents in urban areas, urban vulnerability and urban anti-fire capability. Based on the analysis, the Analytic Hierarchy Process (AHP) is employed in this paper to establish an urban fire risk assessment system, which includes 3 first-level indicators, 13 second-level indicators and 48 third-level indicators. With the data on fire accidents and fire statistics in the past as the basis, this paper applies the Gray Correlation Degree Method to set up the Weight Coefficient of the system and quantify the indicators mentioned above, and finally, this paper applies what has been discussed above to the case of Haikou, capital city of Hainan province, P.R. China. In the city''s chosen 17 sub-districts and 1 town, fire risk assessments are conducted, and the values of risk of fire accidents in urban areas, urban vulnerability, anti-fire capability and comprehensive fire risk in the mentioned selected areas are computed and identified. [Copyright &y& Elsevier]

The JRODOS ( J ava-based R eal-time O nline D ecisi O n S upport) is a decision support system for off-site emergency management for releases of radioactive material into the environment. This paper documents the application of JRODOS by the Hong Kong Observatory in accident consequence assessment and emergency preparedness studies. For operational considerations, the most computational efficient dispersion model in JRODOS, ATSTEP, is adopted. Verification studies for JRODOS's ATSTEP model have been conducted. Comparison with tracer experiment results showed that under neutral atmospheric conditions and distances up to 50 km, the JRODOS simulation outputs were in general of the same order of magnitude with the tracer data. To further evaluate the capability of JRODOS in short-range simulation, a case study on the Fukushima nuclear power plant accident was also carried out. JRODOS was able to produce realistic simulation results which were comparable to the actual airborne monitoring data of the Cs-137 ground deposition from the Fukushima accident. Furthermore, the results of a comprehensive study to assess the potential consequences of accidents at a nearby nuclear power station are presented. Simulation using the French S3 source term for the Guangdong Nuclear Power Station at Daya Bay showed that the projected effective doses within Hong Kong remain far below the IAEA generic criteria of projected dose for urgent protective actions in sheltering/evacuation, while the projected equivalent dose in thyroid may meet the IAEA generic criteria for use of thyroid blocking agent at some areas in the northeastern part of Hong Kong, at distances of up to about 40 km from Daya Bay depending on the prevailing weather conditions in different seasons. [ABSTRACT FROM AUTHOR]

• Develop a complete problem-solving approach for group decision making. • Orient complex large-scale groups and time-sensitive emergency decision scenarios. • Design a feasible mechanism of group consensus strategies under time pressure. • Propose feedback recommendation strategies with a subgroup identification method. • A real case study of China's fight against the COVID-19 epidemic. Group Decision Making (GDM) has been well studied in the last two decades. Yet, two challenges exist: (a) how to resolve large-scale groups in GDM and achieve the consensus of preferences and (b) how to conduct GDM under risk and emergency conditions. In this paper, we develop a complete problem-solving approach for GDM that orients twofold settings of the complex large-scale group and the time-sensitive emergency decision scenarios. The crux of the matter is to design a feasible mechanism of group consensus strategies in the environment of time pressure and natural language preferences. To solve this problem, we propose a closed-loop mechanism of feedback recommendation strategies accompanied with a new subgroup identification method. This mechanism is underlain by a fourfold decomposition of complex large-scale groups, which entails multiple thresholds of group consensus, group hesitation, and time-related iteration of loops. Our mechanism and the whole GDM approach thoroughly orient the most intuitive representation of preferences - human natural language, which can be elicited and quantitatively formulated in probability linguistic preference systems. We illustrate the proposed approach through a real case study of China's fight against the COVID-19 epidemic. We verify that our mechanism can perfectly tradeoff between the effectiveness and the efficiency of complex large-scale GDM under risk and emergency. The results of this research provide proposals for mechanisms on large-scale GDM and are expected to contribute to emergency management such as epidemic controls, anti-terrorism, and other man-made or natural hazards. [ABSTRACT FROM AUTHOR]

• A new method for evaluating the failure of roof and floor strata under dynamic load impact is proposed. • The Energy Variation Coefficient (CV E) and Two Spatial Factors (S and α) are introduced to study the energy difference and aggregation characteristics of microseismic events respectively. • The vulnerability index model is established based on the principal component - entropy method, and the risk zoning map is determined by ArcGIS. • The different microseismic response characteristics of roof and floor are distinguished, which can be used for targeted disaster prevention and control. The disaster induced by dynamic loads in the coal mining process seriously affects the safe production of coal mines. A new method for failure evaluation of roof and floor strata under dynamic load impact is proposed in this paper. The key roof strata breaking and periodic weighting experienced by the 9212 working face of the Dongpang Coal Mine in China while passing through the abandoned roadway is taken as the research background. Firstly, the research stages are divided through theoretical analysis and microseismic monitoring, and then the plane, profile distribution and spatial position relationship of microseismic events in different stages are analyzed. After that, the energy variation coefficient ( CV E) and two spatial factors (S and α) are introduced to analyse the difference in the migration characteristics and damage degree of roof and floor strata under dynamic load impact. Then, the comprehensive weight is determined by principal component analysis and entropy weight method, and the failure evaluation model is established based on vulnerability index method; Finally, the risk grade zoning map of three stages is drawn by using ArcGIS technology. The research shows that the angle factor α can better describe the development direction of roof and floor fissures. The area factor S combined with the energy variation coefficient CV E can explain the development speed of fissures and the damage degree of coal and rock mass. According to the failure evaluation model, the corresponding risk degree of roof and floor in different stages can be comprehensively evaluated. The research results can be used as a reference for targeted disaster prevention and control in similar situations, such as large-area roof collapse and floor water inrush. [ABSTRACT FROM AUTHOR]

Rapid urbanization and exacerbated natural hazards, for example, floods, have been the big challenges for the sustainable development of many countries. Understanding the coupling coordination between urbanization and flood is important for promoting the sustainable development. However, there are few quantitative studies on the interaction between these two in China which is experiencing accelerated urbanization and climate change. In this paper, we developed an improved coupling coordination degree (CCD) model, applied Moran's I and projection pursuit model based on genetic algorithm to analyze the spatiotemporal distribution and spatial clustering effects of coupling coordination in urbanization–flood disasters system under the context of China's Five-Year Plan for National Economic and Social Development. Our results showed an upward trend of the comprehensive level of urbanization subsystem and a decreasing first and rising later trend of flood disaster subsystem in China from 2001 to 2018. There was a U-shaped relationship between the two subsystems during the research period. From 2001 to 2018, provinces with the moderate and slight uncoordinated development decreased by 9.68% and 16.13%, respectively, while provinces with the barely coordinated development increased by 16.21%. Spatially, there was a remarkable spatial dependency on CCD. The CCD between two subsystems in Northwestern China was higher than that in Southeastern China. Due to the effects of geographic position, rainfall, human activities, and economic development, the low-low (L-L) clusters concentrated in Southeastern China, and the high-high (H–H) clusters appeared in Northwestern China. Our results show that the improved CCD model, along with Moran's I analysis, can provide theoretical basis for policy makers to formulate reasonable measures for promoting the coupling coordination between urbanization and flood disasters. • Spatiotemporal distribution and dynamic evolution of nexus between urbanization and flood disasters were investigated. • Improved CCD model, Moran's I and projection pursuit model based on genetic algorithm were developed. • There was a U-shaped relationship in comprehensive level between urbanization and flood disasters. • CCD between two subsystems in Northwestern China was higher than that in Southeastern China. • There was a remarkable spatial clustering effects in CCD. [ABSTRACT FROM AUTHOR]

• We propose a new forest prediction model and use actual deforestation data for optimization and verification. • Use the XGBoost method to reconstruct deforestation intensity data. • Deforestation hotspots in China are mainly concentrated in the southern and southeastern regions. • Our model provides certain reference information for forest disaster prevention and forest management. Forests are important for the global carbon cycle, hydrothermal balance, and climate change. Human activities can exert a significant impact on forest ecosystems, thereby having the potential to alter their physical and chemical properties and thus affecting carbon, water, and heat budgets, and climate change. The historical reconstruction of the disturbance of global forests can help us understand the processes and patterns of human activities and global change. In this paper, we construct a deforestation prediction model using a Spearman correlation coefficient and implement the XGBoost method, using Python 3.6, for the reconstruction of deforestation intensity data from 2000 to 2019. Secondly, the selection of the driver indicators is done by using extreme difference regularization to unify the magnitude, and the potential deforestation area risk index is calculated in the form of equal weights. Finally, the actual deforestation data were used for optimization and validation. The model shows that the deforestation hotspots are mainly concentrated in the southern and southeastern regions of China and that there are large differences in deforestation in different provinces. In the future, the fine spatial and temporal patterns of deforestation in China during the historical period can be quantitatively reconstructed, which can provide some reference information for forest disaster prevention and forest management in China. [ABSTRACT FROM AUTHOR]

Abstract: Based on the characters of wholesale and retail market, it owns larger amount of inventory, bigger fire load, larger crowds and bigger daily trading volume of the wholesale market, and lager size of the mall. Through investing the occupant density of Wuhan Financing Brand Square which used normal population mean and variance of interval estimation principle, the paper drew the occupant density interval of the wholesale and retail market, and it provided the basis for formulation and revision of the future specification. [Copyright &y& Elsevier]

Abstract: It has been found that many systems are characterized by scaling behavior. Time-scaling scale-invariant approaches are used to analyze the temporal distribution of urban fire sequences recorded in the city of Wuhan (China) in present paper. The results of the coefficient of variation show that there is a clustering distribution in the occurrence sequence of urban fire in Wuhan. And with the study of Fano factor and Allan factor for the urban fire sequences in Wuhan, it is found that the urban fire sequences have obviously time-scaling behaviors. These reveal that the point process of urban fires is a fractal process with a high degree of time-clusterization of the events. The results will be helpful to estimate urban fire risk. [Copyright &y& Elsevier]

Upon the occurrence of a disaster, emergency supplies should arrive at disaster areas with different severities in the shortest time. Therefore, it is of pivotal importance to plan and schedule appropriate processes. This paper first elaborates on the principle of ordered arrival of emergency supplies. Then, it establishes a multi-objective multi-constraint emergency material scheduling (EMS) model based on the principle of ordered arrival. Subsequently, a hybrid ant colony optimization (HACO) is proposed to solve EMS. The computational results for 15 multi-depot benchmark instances are reported and the average error between HACO and the best known solution (BKS) is only 0.16% Then, real geological disasters from Hubei province in China are examined as a case study. Experimental results show that HACO performs better than non-dominated sorting genetic algorithm II (NSGA-II) and multi-objective ant colony algorithm (MOACO) in the case study and benchmark instances. • Study a large-scale real landslide disaster. • Establish a multi-objective multi-constraint EMS model. • Propose a HACO to solve the EMS model. • The HACO is tested on benchmarks and disaster network. [ABSTRACT FROM AUTHOR]

Abstract: At present, railway emergency plan management system has become the important support to maintain the normal operation of railway transport system in the foreign developed countries. But our country was far behind in emergency management system, and the emergency system is still not perfect. It''s already cannot satisfy the current railway transport development needs. This paper analyzes the present situation of China railway emergency plan, and puts forward China''s railway emergency plan standardization management strategic thinking in view of the existing problems. [Copyright &y& Elsevier]

Abstract: How to handle emergencies is the core of government emergency management. This paper reformed emergency management business process base on Qinzhou government''s emergency management work. A city integrated emergency response system (CIERS) was also designed according to this business process and the actual situations of the city''s emergency were also considered. The new structure applies an innovative idea that was centralization and authorization emergency management mode (CAEMM). To perform this idea, the government will set up a city integrated emergency response center (CIERC), and authorize the emergency platform to deal with the basic routines; the significant events are disposed by emergency decision-making platform with an overall consideration. [Copyright &y& Elsevier]

Abstract: To meet the relief demands caused by frequent natural disasters and unusual emergencies, the government should utilize the power of society fully and establish a complete system of emergency relief reserves. Thus, this is a complicated task of system engineering. In this paper, we build the system of China relief reserve at first. On this basis, the application of various methods of emergency relief reserve is analyzed through bargaining model in game theory. We conclude that the emergency supplies reserve strategy in the form of ex-ante government and enterprise co-reserve is superior to the strategy in the form of ex-post emergency procurement and emergency production with fund limitation and high social cost. The comparison embodies in three aspects including quantity requirements, quality requirements and structural requirements. [Copyright &y& Elsevier]

Abstract: This paper aims to establish a classification system of mine disaster in order to develop the emergency response management. The study divides the mine disaster into three emergency levels and builds an evaluation model with three core factors, including information scarcity, time urgency and situation complexity. In addition, the study introduces catastrophe progression method to evaluate the seriousness level of mine disaster and takes a case study of mine disaster in Shanxi Province. The results show that the evaluation model has strong operability and practical value to emergency manager and rescuers. [Copyright &y& Elsevier]

Abstract: Keep in pace with the 2008 Beijing Olympics and the 2010 Shanghai Expo, engineering events of different types and sizes are coming to China more than it had ever happened during years. Obviously, these could all cause safety problems. To organize the event perfectly, a lot of questions occur: How to provide the best safety to everyone participate in our event? How to deal with the emergencies during the event? These questions are the most important element of holding a successful event. This paper discusses the necessity of engineering risk management during events. [Copyright &y& Elsevier]

Abstract: Floods are indeed one of the most serious natural hazards for human societies, especially in China. In this paper, we firstly introduce the interior-outer-set model (IOSM) based on information diffusion theory in detail. Then taking consideration its deficiencies, we represent the diffused-interior-outer-set model (DIOSM) to obtain the possibility–probability distribution (PPD). Based on the PPD, we analyze and calculate the risk results. To illustrate the procedure of the proposed method, we apply DIOSM to describe the flood disaster risk quantitatively in China by using statistical data respectively, such as the time of floods, the number of the deaths as well as the economic losses each year from 1990 to 2009. The outcomes of this research offer new insights and moreover new possibility to carry out an efficient way for various future flood disaster prevention and mitigation. [Copyright &y& Elsevier]

Abstract: As crises happen more frequently and in bigger magnitudes in urban communities, disaster prevention and disaster mitigation become increasingly more important. One useful preventive measure is for community members to report relevant risk information before an actual crisis occurs. This paper presents a Public Participation GIS (PPGIS) system called Collaborative Risk Map System (CRMS), which is community based and through which local residents can report risk information of crisis events and share the information in disaster mitigation. Although the Internet and mobile phones are the preferred methods for public participation due to their convenience and ease of use, the feedback information needs to be filtered before usage, so we designed a credibility model to filter out the mendacious information. A risk model of crisis events is also proposed which transformed the static pre-planning to dynamic and timely risk map as a result of public participation. The risk state of the community and reliable risk feedback is displayed on the map using Oracle Spatial technology so that public can see the risk information visually. Through the analysis of risk information, the community can directly access reliable risk information easily and can prepare for it immediately. Most importantly, decision-makers can get the most up-to-date risk information and do more accurate risk analysis so as to make better informed decisions. We demonstrate the prototype system by selecting 20 places to be a community in Chengguan district in Lanzhou, the capital city in Gansu Province, China and selecting fire risk to evaluate its effectiveness and efficiency. [Copyright &y& Elsevier]

Abstract: The earthquake emergency ability of counties is directly related to the successful or not for the whole earthquake emergency response (abbr. EER) of China. Based on the field survey of EER ability of counties after Wen Chuan earthquake, this paper firstly analyzes the definition of EER ability from the two layers of the absolute and relative EER ability of counties. Then deconstructs the evaluation index system of the absolute EER ability of counties and the comprehensive assessment method of the two EER abilities. Finally, taking Sichuan province for example assesses EER ability of Sichuan''s counties. This method will help to quantificationally assess the EER ability of counties, which will not only strengthen their abilities, but also help the high-level government to give more scientific decision-making for the configuration of its limited EER resources. [Copyright &y& Elsevier]

Abstract: High-speed railway digital system on the information in real time, security, accuracy requirements are higher, which is the key point of Chinese railway information. Digital system is facing unprecedented security threats in the 21st century. How to ensure the safety of digital systems is an important issue which is studied by experts around the world. High-speed railway digital system is the importance of the social security system related to national security and safety of the people. This paper introduces the main line of digital high- speed railway information system security according to the emergency management systems of customer service system. PETRI nets and semisupervised learning theory are used to analyze the digital high-speed railway information system security. There are three contributions: first, from the theoretical point of view, high-speed railway digital system security threats, esp. a customer service system security management, are analyzed, a number of high-speed rail system security of the relevant standards and the theoretical system are set up; second is to establish a complete security operation center (SOC) to digital high-speed rail system security protection according to this theoretical system and safety standards; third the operating parameters and performance of SOC running in real system is described and analyzed according to security standards and indicators. Through proven, that the proposed number of high-speed railway system security standards, theories and the overall security framework are consistent with high-speed rail security and ensure the security of High-speed railway digital system in the future. [Copyright &y& Elsevier]

Abstract: This paper reviews the present development of environmental emergency in China that involves legislative framework, regulations and technical support system. Through the analysis of actual case, these deficiencies and problems existing in action of environmental emergency are pointed out. In the countermeasures, the punishment and fine ceiling for environmental violations should be raised by revising clauses, and fees about handling, inspection, restoring and compensation for pollution incidents should be put into the law system, and environmental protection departments should be the leadership to improve emergency response efficiency, and the technical support system should be established to build a series of technical guidelines, norms and work manuals around three procedures that include prevention and monitoring before incident, response and handling in incident and assessment and restore after incident. [Copyright &y& Elsevier]

More than 5000 landslides have been identified in the Three Gorges Reservoir (TGR) area since the impoundment in 2003, which posed great threats to the residential houses, transportation on the Yangtze, and dam stability. This paper focuses on the evaluation of the coupled influence of rainfall and reservoir water on deformation characteristics and failure evolution of the Outang landslide (in China) based on field investigations, a statistical Pearson cross-correlation coefficient analysis, multi-technique monitoring data, and a numerical model. This instability is a reactivated ancient landslide with a volume of approximately 90 Mm3 located in the Three Gorges Reservoir. The slope behavior is featured with a short period of fast displacement and a relatively long period of semi-constant displacement rates per hydrological year, and displacements velocities quicken gradually upslope. Rainfall and reservoir water level are the main triggering factors of slope movement existing in the upper and the lower parts of the landslide, respectively. Based on the numerical results, the failure evolution of this landslide is a compounded push-retrogression-type failure process involving: a) a first rupture at the toe caused by the reservoir water level that will rapidly mobilize a second and subsequent collapses upwards (retrogression type); and b) the rock mass at the upper part will be pushed out and failed downslope (push type) due to precipitation. These results provide a comprehensive analysis of the Outang landslide, which is critical for its management, as well as for disaster prevention and mitigation of analogous reservoir-induced landslides. • About 6-year monitoring data of deformations and hydrological factors were analyzed. • The slope deformation characteristics were addressed. • The primarily hydrological factors for the landslide movement were revealed. • A possible slope instability evolution was proposed. [ABSTRACT FROM AUTHOR]

• Ill-considered urban planning around Niwan gully may multiply the human and economic losses caused by debris flows. • A depth-integrated model was adopted to determine the hazard zones of debris flows with different recurrence intervals. • The debris flow inundation and evolutionary trajectory are shown to be reasonably comparable with historical debris flows. • This study established a relatively complete system to implement hazard and risk assessment in the study area. The highly geologically active, structurally complex Bailongjiang river basin, Longnan City, Gansu Province hosts many debris-flow gullies. The recent Wenchuan and Jiuzhaigou earthquakes have increased the amount of source material available in these debris flow gullies, and the disturbed nature of the slopes makes them prone to failure under high rainfall, increasing the risk of large-scale debris flows. Moreover, poor urban planning in the region may multiply the human and economic losses caused by debris flows. Therefore, it is necessary to determine the potential hazard zones associated with such debris flows and to implement debris flow hazard and risk assessment. In this paper, Niwan gully is chosen as the study object, as it is characterized by repeated debris flow outbreaks and an ill-considered urban planning at the outlet of the gully. A depth-integrated continuum method is adopted to determine the potential hazard zones of debris flows with different recurrence intervals. The debris flow inundation and evolutionary trajectory are shown to be reasonably comparable with historical debris flows. A two-factor model that couples maximum flow depth with momentum is used to better classify the hazard zones. This study also provides a complete and efficient means to determine the values of debris flow parameters and to implement a hazard and risk assessment based on the solid material reserve method and a probabilistic method. This proposed approach efficiently generated a debris flow risk distribution map that can be used for effective disaster prevention in the Bailongjiang River basin. [ABSTRACT FROM AUTHOR]

The Datong Basin is part of the regionally extensive Fenwei Graben System, a major tectonic zone impacted by active tectonics and the resulting damage to life and infrastructure. The basin also contains the Shizhuang ground fissure system. In this study, the likely origin, surface extent, and fissure subsurface characteristics are explored by traditional methods: surveying, mapping, trenching, drilling, and seismic exploration. The Shizhuang ground fissure is located at the intersection of the Xiaoshikou fault and the southern Liuleng margin fault in Yingxian County. It has a length of 2.1 km, excellent continuity, and semi-elliptical surface morphology. The dislocation of strata induced by the fissure increases significantly as the depth increases. The strata bend downward and form typical traction structures near the fissure plane, indicating that the fissure has prominent synsedimentary fault characteristics. The fissure causes serious damage to houses, farmlands, roads, and public facilities, featuring large tensile cracks and vertical dislocations. The resulting data and interpretations indicate that: (1) the ground fissures connect to two major subsurface active faults, which lay the tectonic foundation for the fissure; (2) accelerated groundwater extraction has reactivated the underlying faults and exacerbated fissure development; and (3) mitigation is best achieved by cessation of excessive groundwater pumping, appropriate engineering design, and local avoidance for placement of critical structures. This paper provides a heretofore generally unknown example, promotes research on the mechanisms of fissures, and has guiding significance for disaster prevention and reduction in this area. • Various characteristics of the Shizhuang ground fissure were determined. • Trenching, drilling, and geophysical prospecting were used to examine the fissure. • Tectonic and non-tectonic factors were used to analyze the formation mechanisms. • Regional stress and fault activity controlled the development of the fissure. • Groundwater pumping and a settlement funnel accelerated the fissure extension. [ABSTRACT FROM AUTHOR]