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In this paper, the Multi-Temporal Interferometric Synthetic Aperture Radar (MT-InSAR) technology is adopted to monitor the Line of Sight (LOS) displacement of Fushun West Opencast Coal Mine (FWOCM) and its surrounding areas in northeast China using Sentinel-1 Synthetic Aperture Radar (SAR) images acquired from 2018 to 2022. The spatial-temporal evolution of urban subsidence and the south-slope landslide are both analyzed in detail. Comparison with ground measurements and cross-correlation analysis via cross wavelet transform with monthly precipitation data are also conducted, to analyze the influence factors of displacements in FWOCM. The monitoring results show that a subsidence basin appeared in the urban area near the eastern part of the north slope in 2018, with settlement center located at the intersection of E3000 and fault F1. The Qian Tai Shan (QTS) landslide on the south slope, which experienced rapid sliding during 2014 to 2016, presents seasonal deceleration and acceleration with precipitation, with the maximum displacement in vicinity of the Liushan paleochannel. The results of this paper have fully taken in account for the complications of large topographic relief, geological conditions, spatial distribution and temporal evolution characteristics of surface displacements in opencast mining area. The wide range and long time series dynamic monitoring of opencast mine are of great significance to ensure mine safety production and geological disaster prevention in the investigated mining area. [ABSTRACT FROM AUTHOR]

Energy is known as the lifeline of national development, and from the last decade or so, the security of human energy supply has been frequently disturbed by natural disasters due to global warming and frequent geological activities. In this paper, by combing the literature, we found that the past literature on the relationship between energy and natural disasters mainly focused on measuring energy consumption under natural disasters, but less on the integrated evaluation of human economic activities, energy security and natural disasters, and less on the evaluation of the energy governance efficiency of each provincial, municipal, and autonomous region government in preventing and managing exposure to natural disasters from the perspective of Chinese provinces. Therefore, in order to fill the gap in the literature in this field, this paper collects panel data of energy consumption efficiency stages and natural disaster treatment stages from 2013 to 2017 for 30 provinces in China (excluding Hong Kong, Macao and Taiwan as well as Tibet Autonomous Region) and uses the two-stage undesirable dynamic DDF model as a framework to study the relationship between economic, environmental pollution and natural disasters for the sample data and to analyze the phase-by-phase evaluation of energy and natural disaster efficiency and make corresponding policy recommendations. The following conclusions are drawn: (1) The overall efficiency of China's eastern coastal provinces is higher than that of the central and western provinces. (2) The first-stage efficiency of Chinese provinces is better than the second stage, and the difference in efficiency of the first stage of each province is smaller than that of the second stage. (3) In terms of the efficiency of disaster prevention and relief inputs, the efficiency values are generally lower in most regions of China. (4) Finally, the annual efficiency of natural disaster losses is not high in all regions, and the efficiency values are higher in the eastern coastal regions than in the central and western regions. Accordingly, this paper proposes that each province should formulate relevant disaster prevention and economic development strategies according to regional characteristics, while the central government should also propose locally appropriate coordinated governance policies to effectively control carbon dioxide emissions and air pollution, as well as increase disaster prevention publicity and incorporate disaster prevention education-related work into the performance assessment mechanism of local governments to promote the interactive development of the two. [ABSTRACT FROM AUTHOR]

With the increasing penetration of renewable energy resources, their variable, intermittent and unpredictable characteristics bring new challenges to the power system. These challenges require micro-meteorological data and techniques to provide more support for the power systems, including planning, dispatching, operation, and so on. This paper aims to provide readers with insights into the effects of micro-meteorology on power systems, as well as the actual improvement brought by micro-meteorology in some power system scenarios. This paper provides a review including the relevant micro-meteorological techniques such as observation, assimilation and numerical techniques, as well as artificial intelligence, presenting a relatively complete overview of the most recent and relevant micro-meteorology-related literature associated with power systems. The impact of micro-meteorology on power systems is analyzed in six different forms of power generation and three typical scenarios of different stages in the power system, as well as integrated energy systems and disaster prevention and reduction. Finally, a case study in China is provided. This case takes wind power prediction as an example in a power system to compare the performance when applying micro-meteorological data or not. The experimental results demonstrated that using the micro-meteorological reanalysis dataset with high spatial--temporal resolution for wind power prediction performed better, verifying the improvement of micro-meteorology to the power system to some extent. [ABSTRACT FROM AUTHOR]

With the development of earthquake disaster reduction efforts in China, the content of earthquake disaster reduction policies has become increasingly enriched and improved. Particularly, multiple provincial governments have proposed earthquake disaster reduction planning policies. It is important to explore whether these policies can affect disaster mitigation. Therefore, this paper summarizes the earthquake disaster reduction plans and factors influencing seismic resilience. Panel data from 24 provinces between 2012 and 2021 were collected, and a difference-in-differences approach was used to construct an econometric model to evaluate the policy effects and analyze the enhancement of seismic resilience. The results show that the implementation of earthquake disaster reduction policies has a positive impact on earthquake monitoring, evacuation, and emergency relief capabilities, and the estimated policy effects are statistically significant. Moreover, a series of tests were conducted. The conclusions are as follows: (1) Earthquake disaster reduction policies have a positive impact on the improvement of seismic resilience in provinces. (2) Provinces with a higher number of earthquakes experience more significant effects from earthquake disaster reduction policies. (3) Provinces with higher seismic peak ground acceleration values exhibit more pronounced improvements in seismic resilience. [ABSTRACT FROM AUTHOR]

Emergency management bears the important responsibility of preventing and resolving security risks and responding to disasters and accidents in time. At the same time, it shoulders the important mission of protecting people's lives and property and maintaining social stability. However, there is little research on the forecast of the huge gap and demand for talent. To strengthen the emergency management ability and modernization, improve the ability of emergency management personnel training and solve the shortage of emergency management personnel at this stage, this paper studied the positioning of emergency management personnel in China and the demand for various emergency management personnel. By means of field interviews, questionnaire surveys, participatory research and expert meetings, this research analyzed the characteristics of emergency management talents in China, defined its classification and forecasted its demand. The results showed that emergency management talents in China could be divided into four categories: administrative management talents, practical talents, expert talents and support talents. According to the data calculation results of five representative provinces, Guangdong Province (area with relatively developed economy), Beijing (administrative centre and economically developed area), Sichuan Province (natural disaster‐prone area), Shanxi Province (developed area of energy industry such as coal) and Jiangsu Province (industrially developed areas), it is concluded that the total demand for emergency management talents in China at this stage is about 794,900, and the gap is about 411,200. At present, China's emergency management talents are in short supply. The research results of this paper can provide sufficient data support for the training of emergency management talents. [ABSTRACT FROM AUTHOR]

Ministry of Emergency Management of the People's Republic of China was established on the basis of the original Work Safety Supervision and Management Department. In addition to assuming the responsibilities of the two committees and four departments, it also administers the four major industries such as non-coal mines, metallurgical industry and trade, hazardous chemicals, fireworks, and firecrackers. The comprehensive coordination quality of the emergency management personnel, and professional quality are constantly improved. This paper conducts a study on the Professionalization of China's Emergency Management Team, and provides a research basis for further developing the Emergency Management. [ABSTRACT FROM AUTHOR]

In light of the challenges posed by climate change and rural revitalization, high-quality construction in rural areas is facing significant obstacles from rainstorm flooding. This study adopts a regional disaster system analysis framework and examines the characteristics of rural rainstorm flooding disasters, including the instability of the breeding environment, the hazard characteristics, and the vulnerability of the exposure. Using this framework, we explore the various causes of rainstorm flooding in rural China, assess the effectiveness of responses to these disasters, and examine the differences between urban and rural responses. Our analysis reveals that the increase in rainstorm flooding in rural China is a complex result of multiple factors, including increased risk, instability, and vulnerability. While rural areas have made some progress in monitoring and responding to rainstorm flooding disasters, they remain weaker than cities in terms of governance and disaster management systems. To address these challenges, we recommend increased attention to rural flood control and disaster reduction, stronger preparation for disaster prevention and reduction plans, enhanced rural disaster infrastructure defense, increased financial support for water conservancy projects, and stronger professional emergency response teams, disaster relief equipment, and materials. Additionally, we recommend strengthening disaster prevention and reduction education and publicity among rural residents to promote the ability to self-rescue and mutual rescue. The disastrous impact of climate change and resulting extreme weather events on rural areas has become increasingly evident in recent years. China's vast rural areas have been particularly affected by frequent rainstorm flooding disasters. This paper identifies the increase in rainstorms, the instability of the disaster breeding environment in rural areas, and the increased vulnerability of exposures in these areas as the main reasons behind the intensification of rural rainstorm flooding. To mitigate the impact of these disasters, attention should be paid to natural disaster risk management, normalized flood control, and disaster reduction in rural areas. This requires overall coordination of rural disaster prevention and reduction planning, emphasis on improving the defense capacity of rural areas, increasing financial support for defensive water conservancy projects, promoting the construction of professional emergency rescue teams in rural areas, scientifically distributing flood prevention and disaster relief equipment and materials, strengthening publicity and education on disaster prevention and reduction, and enhancing rural disaster prevention awareness and self-rescue and mutual rescue capabilities. [ABSTRACT FROM AUTHOR]

Advanced geological prediction plays an essential role in disaster prevention and safety guarantee. In this paper, by combining multiwavelet analysis with modified evidence reasoning, a new geological prediction method for surrounding rock in a tunnel considering the parameters' coupling effect was proposed. Based on the key drilling parameters' curves that were denoised in the No. 1 hole of the Xiaochuan tunnel in Gansu Province, China, the coupling effect of these parameters were analyzed and the power–speed ratio (PSR) concept was thereby proposed to deal with the denoised curves and obtain a PSR curve. Through continuous wavelet transform (CWT) of the PSR curve, the lithology and structure were preliminarily determined by sectional matching and optimization of multiple wavelet coefficient curves under the optimal scales and PSR curve. Further, the evidence reasoning was introduced to solve the uncertainty parts in the preceding result. To avoid misjudgment caused by the limitation of Dempster Shafer (D-S) theory in the case of complete conflict, it was modified, in which the basic probability assignment (BPA) was determined by the interval number, and a binary group was then defined by combining the traditional conflict coefficient with pignistic probability distance to measure the degree of conflict. The division result that settled by this method showed greater accuracy than tunnel seismic prediction (TSP) and the drilling core, also could give a clear division for both lithology and structure. Importantly, by applying the established method to Chengzhou tunnel, the result fitted the real condition well. This approach provides references for rock prediction in tunnels. [ABSTRACT FROM AUTHOR]

Ulva prolifera (U. prolifera) green tide outbreaks have occurred in the Yellow Sea of China for many years, causing serious losses to marine ecology and the marine economy. The monitoring and tracking of U. prolifera green tide is a crucial aspect of marine ecological disaster prevention and control management. This paper aims to investigate the spatiotemporal distribution changes in U. prolifera green tide in the Yellow Sea throughout its life cycle. A survey of the Yellow Sea from 2008 to 2023 was conducted using multi-source remote sensing images. Long-term monitoring and analysis of U. prolifera revealed the evolution process of the green tide, including the early development, outbreak, decline, and extinction stages, considering time, space, and frequency of occurrence. Additionally, this study examined peak coverage change patterns over the past 16 years and analyzed the influence of environmental factors such as sea surface temperature and sea surface wind field on the development of U. prolifera. The research results serve as a valuable reference for the monitoring, early warning, and scientific prevention and control of U. prolifera green tide in the Yellow Sea, as well as other similar marine disaster areas. [ABSTRACT FROM AUTHOR]

In this paper, we explore what the travel restrictions during the COVID-19 pandemic reveal about the changing geographies of mobilities and the making of homo sacer, the latter constituted through differentiated control of mobilities. Implemented to protect U.S. public health, travel restrictions imposed on travelers from Mainland China during the early days of the pandemic exemplify how sovereign power that declares a state of emergency and creates bare life can be readily applied to groups of people who previously had privileged access to global mobility. In this sense, bare life does not refer to fixed and disadvantaged social categories but is rather contingently and contextually constituted, through the works of hybrid sovereign regimes. At the same time, however, these travelers are not reduced to a state of zero-agency but reside within a liminal space between soft and hard cosmopolitanisms, as they can still deploy agency and cosmopolitan capital to achieve certain degrees of mobility. By examining how Chinese travelers navigated various travel restrictions and the constantly changing policies to travel to the U.S., this paper explores new spaces of exception and forms of bare life, and argues that homo sacer is dynamically, relationally and recursively constructed, both through apparatus of control and the agency of travelers. [ABSTRACT FROM AUTHOR]

The Anton Paar MCR 52 intelligent high-speed rheometer was utilized in this paper to conduct rheological tests on the Jiangjiagou debris flow slurry via linear loading. The relationship curves between shear rate and shear stress at different solid volume concentrations were obtained, and predictive formulas for yield stress and viscosity coefficient variations with the shear rate are proposed. Furthermore, the evolution mechanisms of yield stress and viscosity coefficient with changes in solid volume concentration of the debris flow were thoroughly analyzed. The results indicated that the rheological curves of the Jiangjiagou debris flow conformed to the Bingham fluid model. An increase in solid volume concentration continuously promoted the upward trend of the rheological curves, with significant increments observed only at high volume concentrations. A predictive model for debris flow rheological parameters was established based on the linear relationship between the rheological parameters and the solid volume concentration. The rise in solid volume concentration inhibited turbulence in the debris flow, while clay minerals enhanced the debris flow slurry's ability to capture pore water. Significant shear-thinning effects were observed within the debris flow, which were particularly more pronounced at lower shear rates. The study outcomes hold crucial engineering significance for a better understanding of debris flow rheological properties, the calculation of debris flow dynamic parameters, and disaster prevention and control. [ABSTRACT FROM AUTHOR]

High-altitude rockfalls, as one of the major geological disasters in mountains, is highly concerned about the study of failure mechanisms and disaster prevention and mitigation. In August 2020, the Babaoshan cliff in Yanhe County, Guizhou collapsed and falling rocks hit agricultural vehicles on the road and damaged residents' houses below. Based on on-site investigation, three rockfall types of tension-rotating, tension-shear-falling, compression-shear exist in the study area, and the compression-shear rockfall can conform to the chain law of rockfall. The paper used the dynamic analysis software Rocpro-3D to simulate and invert the movement characteristics and impact range of rockfall at Babaoshan cliff. The results show that: 1) the hazardous zone, which is about 95 m wide and 175 m long, was formed by the rockfall at R1 and covered localized roads and houses below, with the covered probability of 20%, 17% respectively; 2) the terrains on the rockfall paths in two rockfall disaster events are mainly characterized by stepped shape and overall flat angle respectively, and the behaviors are mainly characterized by ejection and rolling respectively, meanwhile, the times to reach the road and houses were 17 s and 24.3 s, respectively, in addition, the protruding rock mass below the rockfall location gives the falling rock horizontal velocity and good movement space, which will make the falling rock move further away; 3) the different rockfall directions reflect different terrain combinations, simulation inversions reveal that different terrain combinations have significant control over the distance and shape of the rockfall trajectories. And, it was found that the more times a falling rock is rebounded, the greater the energy obtained; 4) the probabilities of falling rocks at H1, H2, H3 invading residential areas are respectively 8.67%, 20%, 19.33%, meanwhile invading road zone are respectively 10.67%, 15.33%, 9.33%. At least one point or several points stopped within the zone of the affected houses in the rockfall disaster event 2 in three prediction of the rockfall impact range, which indicates that there is a great risk that this house will continue to be affected by disasters after rockfalls occur within the steep cliff area above. [ABSTRACT FROM AUTHOR]

Mining-induced disturbance to stress fields can lead to many engineering disasters such as rock bursts, roadway collapses, and coal and gas outbursts. The evolution characteristic of abutment pressure during the mining process is of great significance for prevention of engineering disasters. Based on a case study of No.12526E Panel in Xieqiao coalmine of Huainan mining area in China, this paper investigated the evolution characteristic of abutment pressure during the retreat mining process. A field measurement was performed using three-dimensional (3D) pressure sensor, and the abutment pressure was continuously monitored during the mining process. The monitoring results indicate that the abutment pressure curve can be divided into strong interference area and weak interference area. Further, the evolution characteristics of abutment pressure during the retreat mining process were simulated using a 3D discrete-element program. Periodic caving characteristics of rock strata were obtained, and the major causes of stress concentration and the bearing stress inflection point were analyzed. With the periodic caving of the overlying strata, the stress inflection point appears, and fracture cracks are generated and hinder stress recovery. Finally, the detailed dynamic evolution process of the abutment pressure as well as the deformation and caving characteristics of the overlying strata of the No.12526E Panel were analyzed. The coal and rock near the mined-out area undergo a sharp stress concentration and reduction, which would lead to damage to the rock mass near the mined-out area. [ABSTRACT FROM AUTHOR]

Typhoons are recurring meteorological phenomena in the southeastern coastal area of China, frequently triggering debris flows and other forms of slope failures that result in significant economic damage and loss of life in densely populated and economically active regions. Accurate prediction of typhoon-triggered debris flows and identification of high-risk zones are imperative for effective risk management. Surprisingly, little attention has been devoted to the construction of physical vulnerability curves in typhoon-affected areas, as a basis for risk assessment. To address this deficiency, this paper presents a quantitative method for developing physical vulnerability curves for buildings by modeling debris flow intensity and building damage characteristics. In this study, we selected the Wangzhuangwu watershed, in Zhejiang Province of China, which was impacted by a debris flow induced by Typhoon Lekima on August 10, 2019. We conducted detailed field surveys after interpreting remote sensing imagery to analyze the geological features and the mechanism of the debris flow and constructed a comprehensive database of building damage characteristics. To model the 2019 debris flow initiation, entrainment, and deposition processes, we applied the Soil Conservation Service-Curve Number (SCS-CN) approach and a two-dimensional debris flow model (FLO-2D). The reconstructed debris flow depth and extent were validated using observed debris flow data. We generated physical vulnerability curves for different types of building structures, taking into account both the degree of building damage and the modeled debris flow intensity, including flow depth and impact pressure. Based on calibrated rheological parameters, we modeled the potential intensity of future debris flows while considering various recurrence frequencies of triggering rainfall events. Subsequently, we calculated the vulnerability index and economic risk associated with buildings for different frequencies of debris flow events, employing diverse vulnerability functions that factored in uncertainty in both intensity indicators and building structures. We observed that the vulnerability function utilizing impact pressure as the intensity indicator tends to be more conservative than the one employing flow depth as a parameter. This comprehensive approach efficiently generated physical vulnerability curves and a debris flow risk map, providing valuable insights for effective disaster prevention in areas prone to debris flows. [ABSTRACT FROM AUTHOR]

Landslides, widespread and highly dangerous geological disasters, pose significant risks to humankind and the ecological environment. Consequently, predicting landslides is vital for disaster prevention and mitigation strategies. At present, the predominant methods for predicting landslide susceptibility are evolving from conventional machine learning techniques to deep learning approaches. At present, the predominant methods for predicting landslide susceptibility are evolving from conventional machine learning techniques to deep learning approaches. Prior studies have shown that in the context of landslide susceptibility, these models frequently underperform relative to tree-based machine learning algorithms. This shortcoming has restricted the application of deep learning in this domain. To overcome this challenge, this study presents the TabNet algorithm, which combines the interpretability and selective feature extraction of tree models with the representation learning and comprehensive training capabilities of neural network models. This paper explores the potential of employing the TabNet algorithm for landslide susceptibility analysis in China's WanZhou region and evaluates its performance against traditional machine learning techniques. The experimental data indicate that the TabNet algorithm achieves a recall score of 0.898 and an AUC of 0.915, demonstrating a generalization capability that is comparable to that of classical machine learning algorithms. [ABSTRACT FROM AUTHOR]

This paper aims to provide a design basis for engineering disaster prevention and mitigation by accurately describing the spatial distribution of soil liquefaction. A group of in-situ Cone Penetration Tests (CPT) was conducted to evaluate the seabed soil properties and liquefaction potential of the Yellow River Subaquatic Delta. The factor of safety against liquefaction (FSL) and liquefaction potential index (LPI) were utilized to investigate the liquefaction characteristics of seabed soils. The findings are as follows: (1) The delta is "near coarse and far fine," with sand and silt dominating the onshore direction and silt and silty clay dominating the offshore direction; (2) Silt, as a structured soil, has a maximum sensitivity of 10, and there are local liquefaction phenomena. The size of a Soil behavior type index can be used as the limit value of liquefaction discrimination in the region; (3) The FSL of the shallow layer is smaller, while that of the deep layer is generally larger. The FSL near the coast is smaller than that far from the coast, but its variation range is large, indicating that the shallow soil layer near the coast is more prone to liquefaction; (4) The LPI of the delta is less than 5, which is significantly affected by the wave cycle loads and geographical environment. Liquefaction can occur, but the probability of large-scale liquefaction is low. [ABSTRACT FROM AUTHOR]

This study investigates the foundational elements that contribute to effective emergency management in urban settings, with a particular focus on experiences from Chinese municipalities. Drawing on resource dependence theory and attention allocation theory, this research develops an analytical framework encompassing four pivotal factors: environmental resources, information sharing, social participation, and leadership attention allocation. Utilizing Qualitative Comparative Analysis (QCA), we examine these factors across sixteen critical incidents of urban accidents and disaster responses in China. Our findings reveal that a high degree of leadership attention allocation is an essential prerequisite for municipal governments to exhibit robust emergency management capabilities during crises. Furthermore, two primary pathways affecting emergency management capacity were identified: the "resource–leadership attention type" and the "social participation–resource coordination type". These findings contribute to a nuanced understanding of the complexities of emergency management and enlighten the local governments to take some effective measures to enhance emergency management capacities to mitigate disaster losses. [ABSTRACT FROM AUTHOR]

The dynamic effect is a very important issue widely debated by scholars when studying the genetic and disaster-causing mechanisms of earthquake-triggered landslides. First, the dynamic effect mechanism and phenomena of earthquake-triggered landslides were summarized in this paper. Then, the primary types of dynamic effects were further used to interpret the Mogangling landslide in Moxi Town of Luding County, China. A field investigation, remote sensing, numerical calculation and theoretical analysis were carried out to illustrate the failure mechanism of slope rock masses affected by earthquakes. The interaction between seismic waves and slope rock masses and the induced dynamic effect of slope rock masses were primarily accounted for in the analysis. The slope topography, rock mass weathering and unloading characteristics, river erosion, regional seismogenic structure, and rock mass structure characteristics were also discussed. The results showed that the formation of the Mogangling landslide was mainly related to the high amplification effect of seismic acceleration and back slope effects, interface dynamic stress effects, and double-sided slope effects of seismic waves caused by the catastrophic Ms 7.75 Moxi Earthquake in 1786. The principles for the site and route selection of large-scale infrastructure in the planning stage and the scientific prevention of seismic geological disasters were proposed on the basis of the dynamic effect of earthquake-induced landslides. [ABSTRACT FROM AUTHOR]

Storm surge is a common nature disaster in China southern coastal area, which usually causes heavy human life and economic losses. With the economic development and population concentration of coastal cities, the storm surges may result in more impacts and damage in the future. Therefore, it is of vital importance to conduct risk assessment to identify high-risk areas and evaluate economic losses. However, quantitative study of storm surge risk assessment in undeveloped areas of China is difficult, since there is a lack of building characters and damage assessment data. Aiming at the problem of data missing in undeveloped areas of China, this paper proposes a methodology for conducting storm surge risk assessment quantitatively based on deep learning and geographic information system (GIS) techniques. Five defined storm surge inundation scenarios with different typhoon return periods are simulated by coupled FVCOM-SWAN model, the reliability of which is validated using official measurements. Building footprints of the study area are extracted through TransUNet deep learning model and Remote Sensing Image (RSI), while building heights are obtained through Unmanned Aerial Vehicle (UAV) measurement. Subsequently, economic losses are quantitatively calculated by combing the adjusted depth-damage functions and overlay analysis of the buildings exposed to storm surge inundation. Zonation maps of the study area are illustrated to display the risk levels according to the economic losses. The quantitative risk assessment and zonation maps can help the government to make storm surge disaster prevention measures and optimize land use planning, and thus to reduce the potential economic losses of the coastal area. [ABSTRACT FROM AUTHOR]

The grotto temple, carved into cliffs and widely distributed, is a significant cultural heritage in China. However, it faces severe damage and collapse threats due to natural disaster risks in its environment. Nearly seventy percent of grotto temples are located in regions prone to earthquakes and water hazards, leading to varying degrees of damage to cultural artifacts. Therefore, preventive measures are necessary to reduce the impact of natural disasters on grotto temples. A knowledge graph, a structured semantic knowledge base describing concepts and their relationships in the physical world, plays a crucial role in knowledge organization and content representation. Entity relationships are the core of knowledge, serving as both foundational data and a key task in constructing knowledge graphs and processing unstructured text. In the field of grotto temple disease monitoring, while data continues to grow, research on the correlation between textual data remains underexplored. This paper adopts the BiLSTM-CRF method to extract entity relationships, matching them with the grotto temple monitoring knowledge graph. Finally, the Neo4j software is utilized to program and display the knowledge graph, aiming to enhance the efficiency of natural disaster risk management and cultural heritage protection for grotto temples. [ABSTRACT FROM AUTHOR]

Currently, the whole world is still suffering from the COVID-19 (variants) pandemic that has been lasting for over three years and resulted in countless losses. Since its outbreak at the end of 2019, China has first suffered, but quickly gained the upper hand through strict epidemic control and emergency management. Despite several recurrences of regional epidemics in 2022, both economic growth and people's livelihoods have been effectively safeguarded in China, with a regular prevention system established and social life recovery accomplished orderly. How does China deal with this pandemic? What practical measures taken and decisions made could be adopted and shared with other countries? In this paper, these issues are summarized and discussed as progressive lessons for the rest of the world. Though there's a major shift of pandemic policy in late 2022 and early 2023 in China, this study still provides insightful and beneficial implications to support decision- and policy-makings in future fights against any possible COVID-19 variants until the end of the pandemic. [ABSTRACT FROM AUTHOR]

The coastal regions of Southeast China frequently experience unusual positive storm surges on the left side of landfalling typhoons, a phenomenon historically overlooked and inadequately explained by conventional circular wind field models. In this study, a high resolution, two-dimensional storm surge model based on ADCIRC along with tide gauge data were used to investigate the spatiotemporal distribution of these surges and proposes underlying mechanisms, informed by a comparative analysis of circular and ERA5 reanalysis wind fields during typical typhoon event 9711 Winnie. Analyzing tide gauge data spanning from 1986 to 2016, the study uncovers a distinct pattern of left-side positive storm surges along the southeastern coast, notably on the Fujian coast and within the Taiwan Strait, which are found to be comparable to those on the cyclone’s right side. The research also documents a significant escalation in both the frequency and intensity of these left-side surges over the past three decades. Simulation results highlights the inadequacies of circular wind field models in operational forecasting and emphasizes the necessity of accounting for topographic influences and the structural complexity of wind fields in storm surge predictions. This is particularly pertinent in semi-enclosed seas with intricate hydrodynamics, such as the Taiwan Strait. The insights gleaned from this study are pivotal for enhancing the real-time simulation and prediction of storm surges, which are vital for coastal safety and disaster prevention measures. [ABSTRACT FROM AUTHOR]

Frequent mountain torrent disasters have caused significant losses to human life and wealth security and restricted the economic and social development of mountain areas. Therefore, accurate identification of mountain torrent hazards is crucial for disaster prevention and reduction. In this study, based on historical mountain torrent hazards, a mountain torrent hazard prediction model was established by using Bayesian Model Average (BMA) and three classic machine learning algorithms (gradient-boosted decision tree (GBDT), backpropagation neural network (BP), and random forest (RF)). The mountain torrent hazard condition factors used in modeling were distance to river, elevation, precipitation, slope, gross domestic product (GDP), population, and land use type. Based on the proposed BMA model, flood risk maps were produced using GIS. The results demonstrated that the BMA model significantly improved upon the accuracy and stability of single models in identifying mountain torrent hazards. The F1-values (comprehensively displays the Precision and Recall) of the BMA model under three sets of test samples at different locations were 3.31–24.61% higher than those of single models. The risk assessment results of mountain torrents found that high-risk areas were mainly concentrated in the northern border and southern valleys of Yuanyang County, China. In addition, the feature importance analysis result demonstrated that distance to river and elevation were the most important factors affecting mountain torrent hazards. The construction of projects in mountainous areas should be as far away from rivers and low-lying areas as possible. The results of this study can provide a scientific basis for improving the identification methods of mountain torrent hazards and assisting decision-makers in the implementation of appropriate measures for mountain torrent hazard prevention and reduction. [ABSTRACT FROM AUTHOR]

Introduction: With global warming, the disaster losses caused by extreme precipitation events are increasing. The poor natural conditions and climate change make the arid and semi-arid mountainous grassland area a sensitive region of climate change. The study on the spatio-temporal variation characteristics of extreme precipitation events in this region is helpful to improve the ability of climate prediction and disaster prevention and reduction in grassland. Methods: Based on the daily precipitation data of four meteorological monitoring stations in the Yinshanbeilu from 1970 to 2020, the trend analysis, M-K test and wavelet analysis were used to select seven typical extreme precipitation indicators to analyze the temporal and spatial characteristics of extreme precipitation. Results and Discussion: The results showed that the precipitation in the Yinshanbeilu increased in the past 51a, and the number of heavy rain days increased significantly. The significance test of CDD and CWD showed that the number of continuous dry days and continuous wet days decreased abruptly. The spatial analysis showed that the high value areas of R95p, R95d and PRCRTOT were all located in Siziwang Banner, and it could be concluded that the extreme precipitation risk was the highest in Siziwang Banner, while the low value areas of SDII, Rx1day, R95p and PRCRTOT were all located in Sonid Right Banner, which could be inferred that the Sonid Right Banner was relatively dry. The first main cycle of the seven indexes of extreme precipitation almost runs through the whole time series, and the starting point of the minimum main cycle changes inconsistent. In addition to the number of consecutive dry days, the other indices have a good correlation with annual precipitation, flood season and monthly precipitation from June to September, and July is the peak period of extreme precipitation events. [ABSTRACT FROM AUTHOR]

Hancheng is located in the eastern part of China's Shaanxi Province, near the west bank of the Yellow River. It is located at the junction of the active geological structure area. The rock layer is relatively fragmented, and landslide disasters are frequent. The occurrence of landslide disasters often causes a large number of casualties along with economic losses in the local area, seriously restricting local economic development. Although risk assessment and deformation mechanism analysis for single landslides have been performed for landslide disasters in the Hancheng area, this area lacks a landslide traces database. A complete landslide database comprises the basic data required for the study of landslide disasters and is an important requirement for subsequent landslide-related research. Therefore, this study used multi-temporal high-resolution optical images and human-computer interaction visual interpretation methods of the Google Earth platform to construct a landslide traces database in Hancheng County. The results showed that at least 6785 landslides had occurred in the study area. The total area of the landslides was about 95.38 km2, accounting for 5.88% of the study area. The average landslide area was 1406.04 m2, the largest landslide area was 377,841 m2, and the smallest landslide area was 202.96 m2. The results of this study provides an important basis for understanding the spatial distribution of landslides in Hancheng County, the evaluation of landslide susceptibility, and local disaster prevention and mitigation work. [ABSTRACT FROM AUTHOR]

Frequent occurrence of natural disasters has become one of the most serious challenges to human society. As rural communities are the forefront of disasters, enhancing the resilience of rural community is crucial to mitigate the impact of natural disasters and seek rapid recovery. This paper provides an analytical framework for changing trajectories of the resilience of rural communities after disasters. Taking the disaster area affected by the catastrophic debris flow in China as an example, we analyze the changing trajectories of rural community resilience after disaster in three villages with different damage levels from 2010 to 2020 based on the data from key person interviews, the disaster situation and development reports, village work records and farmers' questionnaires. We found that the changes of community resilience after disaster show obvious stages due to the difference in the intensity of effects of government intervention and community self-organization ability during disaster relief reconstruction period and self-recovery period. The resilience of communities with different disaster losses showed an increasing trend. However, during the disaster relief and reconstruction period, the resilience of the severely affected community was improved faster, followed by the most severely affected community, while the resilience of generally affected community was improved more slowly. During the self-recovery period, the resilience of the affected general community was improved faster than that of the other two communities. The evolution process of community resilience reflects the increasing role of self-organizational capacity in post-disaster community development, aligning with the overall global trend in rural community governance. In addition, there is a significant sequence in the improvement speed of different dimensions of community resilience at different stages after disasters. During the disaster relief and reconstruction period, the resilience of community management was improved faster and the resilience of environment was slower. During the self-recovery period, the economic resilience of community was improved faster and the social resilience was improved slower. Finally, some suggestions were put forward to strengthen natural disasters prevention and community resilience in disaster-prone areas. [Display omitted] • Provide an analytical framework for the changing trajectories of the resilience of rural communities after disaster. • Community self-organization ability play an important role in improving community resilience. • There are significant differences in resilience of communities with different disaster losses. • There is an obvious sequence in the improvement speed of different dimensions of community resilience after disaster. [ABSTRACT FROM AUTHOR]

Background: As the largest group of healthcare professionals, nurses play an indispensable and crucial role in disaster response. The enhancement of nurses' disaster literacy is imperative for effective disaster emergency management. However, there is currently a lack of knowledge regarding nurses' disaster literacy. This study represents the first attempt to explore the key components and characteristics of disaster literacy among nurses. Methods: A qualitative descriptive design was employed, and the reporting followed the Consolidated Criteria for Reporting Qualitative Research (COREQ) guidelines (refer to File S1). The purposive sampling method was utilized. Thirty-one rescue nurses from 31 medical institutions across 25 provinces and regions in China were recruited to participate in the study. The respondents were requested to share their experiences and insights regarding disaster rescue operations. Inductive content analysis was employed for data examination. Results: The results indicated that rescue nurses universally recognized that there was a pressing need to enhance the level of disaster literacy among nurses. The disaster literacy of nurses encompasses nine dimensions: physical and mental quality, disaster rescue general knowledge, professional and technical competence, professional ethics, teamwork, emotional ability, information literacy, leadership, and knowledge transformation. Conclusions: To ensure national sustainability, government departments, healthcare organizations, and hospital administrators can accurately evaluate the disaster literacy of individual clinical nurses, groups, and the workforce as a whole through nine dimensions, which also can provide evidence to support the development of precision strategies to strengthen the disaster literacy of nurses. [ABSTRACT FROM AUTHOR]

Background: Colleges and universities face an increased risk of public health emergencies. Among them, medical colleges and universities deserve more attention as they serve as the play a fundamental role in providing public health emergency services and in cultivating medical professionals. Effectively managing infectious disease prevention and control, as well as responding to public health emergencies in medical colleges and universities, is of great importance for enhancing the capacity of social emergency governance and improving the completeness of the public health system. This study aims to understand the management of public health emergencies in medical colleges in a city in southwest China, explore the factors associated with medical college students' evaluations, and provide recommendations for emergency management mechanisms in colleges and universities. Methods: In total, 781 medical college students were selected through stratified random sampling and surveyed using a questionnaire. The main factors affecting students' evaluation of emergency management were analyzed using multiple linear regression and structural equation modeling. Results: The overall emergency management situation in medical colleges was relatively complete, with satisfactory results. Medical college students' satisfaction with the timeliness of prevention measures was the highest, while the publicity and education were the lowest. Multiple linear regression analysis showed that grades, emergency education, -simulation training, -information reporting, and dynamic adjustment measures were associated with the evaluation of emergency management by medical students. Conclusions: Although the evaluation of emergency management in medical colleges was generally positive, certain limitations still existed. To improve the development of the public health system, colleges and universities should constantly reform and innovate emergency management mechanisms according to the important links in the prevention and control processes. [ABSTRACT FROM AUTHOR]

Held every four years, the International Workshop on Tropical Cyclone (IWTC) organized by the World Meteorological Organization has been a global leading conference in the field of tropical cyclone. In preparation for the 10th IWTC (IWTC-10) in December 2022, a summary of research advances of landfalling tropical cyclone (LTC) rainfall during past four years of 2019-2022 has been prepared. Some of the latest research advances has been summarized in Lamers et al. (2023), which reviewed the latest forecast and disaster prevention methods related to TC precipitation. As a supplement, this article mainly focuses on the recent advances in LTC asymmetric rainfall evolution mechanisms and forecast verification results over China. Some new findings have been made in the LTC inner-core size relationship with the asymmetric rainfall distribution. Some major advances focused on asymmetric microphysical characteristics in the TC rainbands. Current simulation and forecast performances of LTC precipitation have been analyzed, and different forecast error sources for rainfall during different landfall stages of TC were compared. To estimate the risk of TC rainfall hazards in China, a parameterized Tropical Cyclone Precipitation Model was reviewed as well in this article. [ABSTRACT FROM AUTHOR]

In the context of land relocation, poverty alleviation resettlement (PAR) is considered an effective approach to improve the man–land relationship and development issues. However, current studies pay little attention to PAR and its spillover effects within developed regions. Furthermore, the complete mechanism chain has received little research concentration. Thus, employing a qualitative survey, this study aims to investigate the overall mechanisms of developed regions' PAR in the context of land relocation. The study will deal with the following questions: Why does PAR occur in developed regions? How does the resettlement approach to poverty alleviation (i.e., paths)? What are the effects of resettlement on poverty alleviation, including its own effects and spillover effects? Through answering these questions, this study will highlight PAR in developed regions and investigate the spillovers from social, economic and ecological perspectives. Particularly, a comprehensive mechanism analysis framework for PAR will be presented to motivate future studies. Results indicate that PAR is generally caused by ecological poverty alleviation, geological disaster prevention and county town urbanisation promotion and that emigration and resettlement are the paths to PAR. In addition, the direct outcome is the overall rise in the number of resettlers over time, and the spillovers show the sustainable collaboration of economic, social and ecological dimensions. These findings will influence future land reform and housing initiatives. [ABSTRACT FROM AUTHOR]

High-spatial-resolution urban buildings play a crucial role in urban planning, emergency response, and disaster management. However, challenges such as missing building contours due to occlusion problems (occlusion between buildings of different heights and buildings obscured by trees), uneven contour extraction due to mixing of building edges with other feature elements (roads, vehicles, and trees), and slow training speed in high-resolution image data hinder efficient and accurate building extraction. To address these issues, we propose a semantic segmentation model composed of a lightweight backbone, coordinate attention module, and pooling fusion module, which achieves lightweight building extraction and adaptive recovery of spatial contours. Comparative experiments were conducted on datasets featuring typical urban building instances in China and the Mapchallenge dataset, comparing our method with several classical and mainstream semantic segmentation algorithms. The results demonstrate the effectiveness of our approach, achieving excellent mean intersection over union (mIoU) and frames per second (FPS) scores on both datasets (China dataset: 85.11% and 110.67 FPS; Mapchallenge dataset: 90.27% and 117.68 FPS). Quantitative evaluations indicate that our model not only significantly improves computational speed but also ensures high accuracy in the extraction of urban buildings from high-resolution imagery. Specifically, on a typical urban building dataset from China, our model shows an accuracy improvement of 0.64% and a speed increase of 70.03 FPS compared to the baseline model. On the Mapchallenge dataset, our model achieves an accuracy improvement of 0.54% and a speed increase of 42.39 FPS compared to the baseline model. Our research indicates that lightweight networks show significant potential in urban building extraction tasks. In the future, the segmentation accuracy and prediction speed can be further balanced on the basis of adjusting the deep learning model or introducing remote sensing indices, which can be applied to research scenarios such as greenfield extraction or multi-class target extraction. [ABSTRACT FROM AUTHOR]

Disaster information content is an objective mapping of disaster situations, social response, and public opinions. Social response to emergency is an important mechanism for implementing and guaranteeing emergency management of major natural hazard-related disasters. Understanding how disaster information content affects social response to emergencies is helpful for managing risk communication and efficient disaster response. Based on the 2008 freezing-rain and snowstorm disasters in southern China, this study used Python to extract 7,857 case-related media reports and applied natural language processing for text analysis. It used three typical cases to identify and analyze disaster media report content and the relationship between these reports and the social response to the emergency. Eight categories of disaster response—such as prewarning and forecasting, announcements by the authorities, and social mobilization—appeared in the disaster information in the media, along with disaster impact information, that is, real-time disaster status. Disaster response information and an appropriate amount of disaster impact information played important roles in prewarning, disaster relief, public opinion guidance, and social stability maintenance and can serve important functions in communicating with all stakeholders of emergency management, assisting or influencing emergency departments or individuals in decision making, and eliminating "information islands." Empathy caused the general public to become "disaster responders" through receiving information. Rumors and an excess of negative information may have a perverse amplification effect on public opinion and increase the unpredictability of the disaster situation and the risk of social crisis. [ABSTRACT FROM AUTHOR]

Monitoring and assessing coastal subsidence is crucial to mitigating potential disaster risks associated with rising sea levels. Nansha District in Guangzhou City, representing global coastal soft-soil urban areas, faces significant challenges related to ground subsidence. However, the current understanding of the status, causative factors, and risk (includes subsidence susceptibility and vulnerability) assessment of ground subsidence in Nansha District is unclear. To address this gap, we utilized the SBAS-InSAR technique, analyzing 49 Sentinel-1A images from December 2015 to June 2019, for systematic ground subsidence monitoring. Subsequently, we assessed subsidence risk using a comprehensive index method and a risk matrix. Our findings indicate that subsidence velocity primarily ranged from −40 to −5 mm/a, with a spatial pattern of increasing subsidence from inland to coastal areas. The cumulative subsidence process unfolded in four distinct stages. The genesis of land subsidence was linked to an endogenous geological context dominated by soft-soil deposition, influenced by external factors such as surface loading and groundwater extraction. High-risk zones were concentrated in key engineering development areas, transportation pipeline trunk lines, and densely populated regions, demanding special attention. This study provides a foundational resource for disaster prevention and control strategies in Nansha District and similar coastal cities. [ABSTRACT FROM AUTHOR]

Background: Health security is a critical issue which involves multiple dimensions. It has received increasing attention in recent years, especially in China. In order to improve the national health level, China has made many efforts, such as the "Healthy China 2030" plan proposed several years ago. However, due to the complexity of its national conditions and the difficulty of index design, the results of these efforts are not significant. Therefore, it is necessary to construct a new measurement index system. Methods: Based on the questionnaire of "Health China 2030", we have collected a total of 3,000 participants from all 31 provinces, autonomous regions, and municipalities in China. We used statistical methods such as multiple correspondence analysis and rank-ordered effect analysis to process the data. The balance index is constructed by a series of actions such as weight division, order calculation and ranking. Results: Through multiple correspondence analysis, we can find that there was a close relation in the correspondence space between the satisfaction degrees 1, 2, and 3, while a far distance from satisfaction degrees 4 and 5. There were four positive and four negative indices separately based on the average expected level and four clusters after ordinal rank cluster analysis. Generally speaking, there are no prominent discrepancies across gender and residential areas. Conclusions: We created and examined balanced indicators for health security in China based on the "Health China 2030" questionnaire. The findings of this study give insight into the overall situation of health security in China and indicate opportunities for improvement. [ABSTRACT FROM AUTHOR]