The modern world remains vulnerable to natural disasters,including floods,earthquakes,wildfires,and others.These events remain unpredictable and inevitable,and recovering quickly and effectively requires significant e...The modern world remains vulnerable to natural disasters,including floods,earthquakes,wildfires,and others.These events remain unpredictable and inevitable,and recovering quickly and effectively requires significant effort and expense.Monitoring is becoming more efficient thanks to technologies such as Unmanned Aerial Vehicles(UAVs),which can access hard-to-reach areas and provide real-time data.However,in disaster-affected areas,these monitoring systems may encounter many obstacles when communicating with servers or transmitting monitored data.This paper proposes an adaptive communication model to overcome the challenges faced in disaster-affected areas.A base station is responsible for collecting data(such as images and videos)captured by UAVs performing surveillance within its communication range.This station is typically a tower providing fixed cellular network service.However,in the absence of such a tower,a selected UAV may serve as the station,depending on the situation.If surveillance needs to be performed outside the coverage area,it can continue to communicate via nearby UAVs through cooperative communication.UAVs with internet support,known as the Internet of Flying Things(IoFT),will also be utilized to enhance communication capacity and efficiency.The proposed communication model is validated through experiments,showing superior data transmission performance and higher throughput.Analysis indicates it outperforms traditional systems,even in rural areas,with or without internet access.展开更多
On December 18,2023,a magnitude 6.2 earthquake struck Jishishan County,Gansu Province,triggering a liquefaction-induced flow slide along the loess-mudstone contact zone and causing significant casualties and property ...On December 18,2023,a magnitude 6.2 earthquake struck Jishishan County,Gansu Province,triggering a liquefaction-induced flow slide along the loess-mudstone contact zone and causing significant casualties and property losses.The event featured low-slope,large-scale,runout distance sliding and exhibited a clear cascading disaster chain.Its characteristics closely resemble the catastrophic mudflow at the nearby Lajia Ruins approximately 4,000 years ago.Using high-resolution oblique photogrammetry,cone penetration testing,surface wave analysis,and horizontal-to-vertical spectral ratio methods,this study examines the stratigraphy,groundwater conditions,and geomechanical properties of the affected zone.Results indicate that saturated loess overlying impermeable mudstone formed a high-moisture mass vulnerable to seismic disturbance.Seismic resonance triggered the liquefaction of weakly structured loess,which slide along the contact interface and evolved into a runout distance mudflow.Underground water and terrain modification created a composite weak zone of saturated loess and softened mudstone,which intensified the disaster chain-from earthquake to liquefaction,flow slide,and mudflow.This study contributes to the understanding of deep-seated liquefaction-flow slide disasters,thereby advancing more effective risk mitigation strategies in the Loess Plateau and comparable loess-covered seismic regions.展开更多
In this study,tropical cyclone(TC)translation speed was introduced as a new similarity factor within the generalized initial value(GIV)framework,enhancing the disaster preassessment capability of the dynamical statist...In this study,tropical cyclone(TC)translation speed was introduced as a new similarity factor within the generalized initial value(GIV)framework,enhancing the disaster preassessment capability of the dynamical statistical analog ensemble forecast model for landfalling TC disasters(DSAEF_LTD model).Three TC translation speed indicators most relevant to TC precipitation were incorporated:the maximum speed on Day 1(the first day of TC-induced precipitation and wind occurring on land)and the average and minimum speeds over All Days(all days of TC-induced precipitation and wind occurring on land),all classified using the Kmeans clustering algorithm.Simulation experiments showed that integrating TC translation speed enhanced the model's performance.The model provided a better optimal common scheme,with the TSS UM(sum of threat scores for severe and above and extremely severe and above disasters)increasing by 2.66%(from 0.5117 to 0.5253)compared with the original model.More importantly,its preassessment ability improved significantly,with the average TSS UM for independent samples increasing by 6.43%(from 0.6488 to0.6905).The modified model demonstrated greater accuracy in capturing disaster severity and distribution of TCs with significant speed characteristics or with regular tracks.This improvement stemmed from reduced false alarms due to the selection of analogs that are more similar to the target TC.The enhanced preassessment ability can be attributed to the key role of TC translation speed,which significantly influences TC precipitation patterns and improves TC precipitation forecasting.Since precipitation is one of the most crucial disaster-causing factors,better TC precipitation forecasting leads to improved disaster preassessment outcomes.These findings emphasize the promising potential of the DSAEF_LTD model for future TC disaster research and management,contributing to the achievement of the Sustainable Development Goals set by the United Nations 2030 Agenda by strengthening coastal resilience.展开更多
Water-sand gushing(WSG)disasters in confinedaquifers pose significantchallenges to the utilization of deep underground spaces in soft soil areas.Since few studies have considered the impact of confined aquifer thickne...Water-sand gushing(WSG)disasters in confinedaquifers pose significantchallenges to the utilization of deep underground spaces in soft soil areas.Since few studies have considered the impact of confined aquifer thickness and confinedwater pressure on WSG disasters,a novel visual model test system was developed to investigate the influencingcharacteristics and mechanisms of the two aforementioned factors.The test results showed that the WSG process in clay aquiclude-confinedaquifer composite strata exhibits two prominent stages.First,the sand loss zone expands vertically in an ellipsoid shape.Then,it expands horizontally once the ellipsoid reaches the boundary of the clay layer.The sand loss continues until the overlying clay sinks to the bottom to clog the gushing crack,creating a large sinkhole at the surface.Increasing the confinedaquifer thickness can increase the vertical expansion of the ellipsoid and delay the clay-clogging effects,thereby considerably increasing the severity of sand loss,stratum deformation,and surface settlement.An increase in the confinedwater pressure markedly increases the hydraulic gradient along the seepage path,which contributes to increasing the gushing rates of water and sand.As a result,substantial sand loss occurs before the clay clogs the gushing crack,inducing more cracks and deeper sinkholes at the surface.All the aforementioned results provide insights into the effects of confinedaquifer on WSG disasters in clay aquiclude-confinedaquifer composite strata.展开更多
At first glance(一瞥),10-year-old B.Kenit from the coastal town of Visakhapatnam in India looks like any other school-going child,but there is more than meets the eye.Inspired by a tsunami drill conducted in his schoo...At first glance(一瞥),10-year-old B.Kenit from the coastal town of Visakhapatnam in India looks like any other school-going child,but there is more than meets the eye.Inspired by a tsunami drill conducted in his school when he was eight,the third grader be-came a Disaster Risk Reduction(DRR)advocate,educating his fel-low students and community members on early warning,evacua-tion,and search and rescue.展开更多
As centers of human activity,cities concentrate populations,resources,and wealth in limited areas.According to the United Nations,55%of the global population now lives in urban areas[1].Moreover,the World Economic Fo...As centers of human activity,cities concentrate populations,resources,and wealth in limited areas.According to the United Nations,55%of the global population now lives in urban areas[1].Moreover,the World Economic Forum’s“Global Risks Report 2023”[2]highlights natural disasters as a major threat to sustainable development,especially for densely populated cities.展开更多
The China Meteorological Administration(CMA)said that in the last five years,China has made big improvements in its weather services.This includes better weather forecasts and ways to protect people from disasters.
The Hengduan Mountains region(HMR)is one of the most densely distributed and severe flash flood disaster-prone areas in southwest China.It is also a key area for major engineering projects and beautiful countryside co...The Hengduan Mountains region(HMR)is one of the most densely distributed and severe flash flood disaster-prone areas in southwest China.It is also a key area for major engineering projects and beautiful countryside construction in Southwest China.However,previous studies have not systematically summarized the development characteristics and formation modes of flash flood disasters in the HMR,which limits the development of theoretical and technical system for flood control.In this study,we focused on the physical processes of flash flood disasters in the HMR,including generation,movement,and disaster formation,and clarified the dominant disaster-inducing conditions(multiple humid monsoon circulation,high potential energy and high heterogenous underlying surface)and disaster development characteristics(high spatio-temporal heterogeneity,highly concentrated energy,chain and cascading effects,and clustered occurrence)of flash floods in the HMR.Based on the entire processes of flash flood disasters,three major formation modes have been summarized:the runoff generation mode of vegetation-hydrology-soil coupling dominated by high hydraulic gradient in mountainous areas,strong flow-sediment coupling movement,and serious disaster losses due to high exposure of disaster bearing objects.Finally,based on the issues in previous research,four future research challenges for flash flood disaster in the HMR were proposed.Our study provides insights into disaster prevention and reduction research,including fundamental theoretical system,precise risk assessment of regional disasters,and accurate early warning and forecasting of flash floods.展开更多
Snow and freezing disasters are recurrent weather and climate phenomena that affect the world annually.These events exert a significant influence on numerous aspects of life,including transportation,power supply,and d...Snow and freezing disasters are recurrent weather and climate phenomena that affect the world annually.These events exert a significant influence on numerous aspects of life,including transportation,power supply,and daily activities,and result in considerable economic losses.This study aims to provide a comprehensive analysis of the regions affected by these disasters,the preventive and responsive measures employed,recent advancements in key materials,and the challenges encountered.By doing so,we can gain a deeper understanding of the vital role,significant advantages,and untapped potential of key materials for effectively preventing and responding to snow and freezing disasters.Furthermore,promoting research and utilization of these materials not only contributes to the development of the safety and emergency equipment industry but also strengthens the supply of advanced and suitable safety and emergency equipment.展开更多
This study draws from detailed qualitative case studies of three schools that practise disaster risk reduction (DRR) education initiatives in their curriculum in Nepal. Using curriculum mapping and discourse analysis,...This study draws from detailed qualitative case studies of three schools that practise disaster risk reduction (DRR) education initiatives in their curriculum in Nepal. Using curriculum mapping and discourse analysis, it aims to elaborate the significance of relevant disaster risk reduction (DRR) content in school curriculum to prepare youths for disaster response and recovery. It elaborates the nature of the current DRR content covered in curricula and textbooks and provides suggestions to address the identified disaster-related issues in the school curriculum. It further elaborates that incorporation of local and contextualised DRR content in school curricula contributes to the establishment of the “culture of resilience” in disaster prone context like Nepal. It concludes that more organised and holistic approach is essential to develop disaster and management knowledge, skills and attitudes to youths.展开更多
Landslides represent a growing global challenge,particularly in mountainous and rapidly urbanising regions where environmental degradation and socio-economic vulnerabilities converge.This study investigates the interr...Landslides represent a growing global challenge,particularly in mountainous and rapidly urbanising regions where environmental degradation and socio-economic vulnerabilities converge.This study investigates the interrelationships between Integrated Landslide Disaster Risk Management(ILDRiM)and the United Nations Sustainable Development Goals(SDGs),advancing a systemsbased understanding of landslide risk as a socially constructed and development-driven phenomenon.Drawing on a narrative literature review and a Design Structure Matrix(DSM),the research identifies eight critical drivers of landslide disaster risk:deforestation,climate change,urbanisation,infrastructure development,community vulnerability,exposure to landslides,ineffective governance,and lack of scientific integration into policymaking.The DSM framework systematically maps these drivers against the 17 SDGs to evaluate the nature and strength of their interactions.The analysis reveals significant synergies,where addressing specific drivers supports multiple SDGs,and trade-offs,where risk reduction efforts may inadvertently hinder other development objectives if not implemented inclusively and strategically.Findings underscore the transformative potential of embedding ILDRiM within national and local development frameworks.Prioritising governance reform,scientific innovation,and resilient infrastructure(SDGs 16,17,and 9)is particularly effective for advancing landslide risk reduction while supporting broader sustainability outcomes.The study also highlights the need for anticipatory,cross-sectoral,and community-driven approaches to risk governance.This research offers actionable insights for policymakers,practitioners,and researchers seeking to align disaster risk management with sustainable development planning.It proposes a novel methodology for assessing systemic interlinkages between disaster risk drivers and the SDGs.It calls for further research to refine data integration,address context-specific risks,and strengthen the evidence base for risk-informed development.By operationalising ILDRiM through the SDG framework,this study supports creating more resilient,equitable,and sustainable communities in landslide-prone regions.展开更多
Located on the mountainous western edge of Beijing Municipality,Mentougou District is renowned for its breathtaking natural landscapes and rich cultural heritage.On 22 June,I had the opportunity to visit the district,...Located on the mountainous western edge of Beijing Municipality,Mentougou District is renowned for its breathtaking natural landscapes and rich cultural heritage.On 22 June,I had the opportunity to visit the district,nearly two years after it was struck by a catastrophic flood that left widespread destruction in its wake.My visit provided a unique opportunity to observe the ongoing recovery e!orts and evaluate how the district has leveraged coordinated planning,technology and the resilience of its people to rebuild.The purpose of the visit was to witness these recovery e!orts firsthand and gain insight into the strategies that have helped Mentougou overcome the lingering e!ects of this environmental disaster.展开更多
The increasing frequency and severity of natural disasters,exacerbated by global warming,necessitate novel solutions to strengthen the resilience of Critical Infrastructure Systems(CISs).Recent research reveals the si...The increasing frequency and severity of natural disasters,exacerbated by global warming,necessitate novel solutions to strengthen the resilience of Critical Infrastructure Systems(CISs).Recent research reveals the sig-nificant potential of natural language processing(NLP)to analyze unstructured human language during disasters,thereby facilitating the uncovering of disruptions and providing situational awareness supporting various aspects of resilience regarding CISs.Despite this potential,few studies have systematically mapped the global research on NLP applications with respect to supporting various aspects of resilience of CISs.This paper contributes to the body of knowledge by presenting a review of current knowledge using the scientometric review technique.Using 231 bibliographic records from the Scopus and Web of Science core collections,we identify five key research areas where researchers have used NLP to support the resilience of CISs during natural disasters,including sentiment analysis,crisis informatics,data and knowledge visualization,disaster impacts,and content analysis.Furthermore,we map the utility of NLP in the identified research focus with respect to four aspects of resilience(i.e.,preparedness,absorption,recovery,and adaptability)and present various common techniques used and potential future research directions.This review highlights that NLP has the potential to become a supplementary data source to support the resilience of CISs.The results of this study serve as an introductory-level guide designed to help scholars and practitioners unlock the potential of NLP for strengthening the resilience of CISs against natural disasters.展开更多
A terrible disaster struck our town last month,which brought heavy rain and strong winds all night.Many houses were damaged,and some even fell down,leaving hundreds of people homeless.However,what surprised us most wa...A terrible disaster struck our town last month,which brought heavy rain and strong winds all night.Many houses were damaged,and some even fell down,leaving hundreds of people homeless.However,what surprised us most was the great unity shown by everyone.Neighbors helped each other carry things,sharing food and warm clothes,while volunteers from other towns came to offer support.With everyone's efforts,we started the recovery work quickly,which made us believe that we could rebuild our home soon.展开更多
Background Efficient disaster victim detection(DVD)in urban areas after natural disasters is crucial for minimizing losses.However,conventional search and rescue(SAR)methods often experience delays,which can hinder th...Background Efficient disaster victim detection(DVD)in urban areas after natural disasters is crucial for minimizing losses.However,conventional search and rescue(SAR)methods often experience delays,which can hinder the timely detection of victims.SAR teams face various challenges,including limited access to debris and collapsed structures,safety risks due to unstable conditions,and disrupted communication networks.Methods In this paper,we present DeepSafe,a novel two-level deep learning approach for multilevel classification and object detection using a simulated disaster victim dataset.DeepSafe first employs YOLOv8 to classify images into victim and non-victim categories.Subsequently,Detectron2 is used to precisely locate and outline the victims.Results Experimental results demonstrate the promising performance of DeepSafe in both victim classification and detection.The model effectively identified and located victims under the challenging conditions presented in the dataset.Conclusion DeepSafe offers a practical tool for real-time disaster management and SAR operations,significantly improving conventional methods by reducing delays and enhancing victim detection accuracy in disaster-stricken urban areas.展开更多
In response to the three major contradictions,safety,cognition,and ability cultivation,existing in the practical teaching of geological hazard courses,this paper proposes a“virtual-real integration”teaching reform s...In response to the three major contradictions,safety,cognition,and ability cultivation,existing in the practical teaching of geological hazard courses,this paper proposes a“virtual-real integration”teaching reform scheme,using earthquake disasters as an example.By integrating digital twin technology and artificial intelligence technology,a four-layer teaching framework consisting of data layer,model layer,platform layer,and intelligent layer is constructed.Progressive teaching segments of“cognition-simulation-decision-making”are designed to establish a comprehensive training path from seismic geological survey to disaster early warning and decision-making.This scheme shifts the traditional field practice venue to a safe virtual environment,promotes students’understanding of geological hazards from static fragments to dynamic processes,enhances their comprehensive decision-making ability in geological disaster prevention and mitigation,and provides theoretical support and practical guidance for cultivating interdisciplinary talents in geological hazard prevention.展开更多
Artificial Intelligence is profoundly transforming innovation and development in healthcare and education.In this study,we developed an AI-empowered blended learning model for disaster medicine.Leveraging the Rain Cla...Artificial Intelligence is profoundly transforming innovation and development in healthcare and education.In this study,we developed an AI-empowered blended learning model for disaster medicine.Leveraging the Rain Classroom platform,we established a comprehensive intelligent teaching support system covering the entire learning cycle-pre-class,in-class,and post-class.Through AI-driven enhancements,the model enables intelligent resource allocation,personalized learning paths,and high-fidelity simulation of practical training scenarios.Moreover,it addresses key challenges in traditional disaster medicine education,including fragmented knowledge delivery,insufficient practical training environments,and limited evaluation methods.Ultimately,the model enhances both the efficiency and effectiveness of disaster medicine education.展开更多
Based on the site investigation of a lightning stroke accident in a coal mine in Weiyuan County during a strong thunderstorm process on the night of August 10,2024,combined with the investigation data of the accident ...Based on the site investigation of a lightning stroke accident in a coal mine in Weiyuan County during a strong thunderstorm process on the night of August 10,2024,combined with the investigation data of the accident site,the causes of the lightning stroke accident were analyzed,and the corresponding rectification suggestions were put forward.展开更多
Rainfall-induced landslides are often highly destructive.Reviewing and analyzing the causes,processes,impacts,and deficiencies in emergency response is critical for improving disaster prevention and management.From th...Rainfall-induced landslides are often highly destructive.Reviewing and analyzing the causes,processes,impacts,and deficiencies in emergency response is critical for improving disaster prevention and management.From the night of July 21 to the morning of July 22,2024,the Kencho Shacha Gozdi Village in Gezei Gofa,Southern Nations,Nationalities,and Peoples'Region,Ethiopia,suffered heavy rainfall that triggered two landslides.By July25,this event had claimed at least 257 lives.This study presents a detailed characterization of the landslides using multi-source data.By analyzing the landslide disaster process,this study summarizes key lessons and provides suggestions for preventing rainfall-induced geological hazards.The results indicate that rainfall has the greatest impact on the occurrence of landslides,while lithology and human activities have promoted and strengthened the landslide disaster.Despite the active disaster response in the local area,many problems were still exposed in the emergency response work.This analysis offers valuable insights for mitigating rainfall-induced geological hazards and enhancing emergency response capabilities.展开更多
Rainstorm-induced flood hazards in mountainous areas often result in complex cascading effects by interacting with environmental and human systems.However,traditional studies typically categorize them simply as clearw...Rainstorm-induced flood hazards in mountainous areas often result in complex cascading effects by interacting with environmental and human systems.However,traditional studies typically categorize them simply as clearwater floods or debris floods/flows,overlooking their evolutionary characteristics and compound impacts.This study presents a novel classification-based approach to investigate the formation and destructive mechanisms of a catastrophic composite disaster of flash flood and debris flow in the Dayao Gully(DYG)catchment in Hanyuan County,Sichuan Province,China.The event resulted in 14 fatalities,25 missing persons,and extensive infrastructure damage.Through comprehensive field investigations and multi-method analysis,three distinct disaster zones were identified with different magnitudes and impacts:(1)a clearwater flood disaster region with minimal geomorphological changes under a 5-year return period rainfall;(2)a debris flood disaster region triggered by a 30-year return period rainfall,leading to intense sediment transport with a total deposit volume of 52,511 m^(3);and(3)a sediment-induced flood disaster region characterized by significant riverbed aggradation and infrastructure destruction due to sediment-induced blockage effects.The results reveal that the cascading characteristics of this composite disaster were primarily driven by intense rainfall,enhanced sediment transport motivated by supracritical shear stress,and interactions with human infrastructure(e.g.,bridges and buildings).This classification-based approach provides a quantitative assessment of spatial characteristics of cascading flood disasters,offering new insights into their evolutionary characteristics and highlighting the necessity for targeted disaster mitigation strategies in sedimentprone mountainous regions.展开更多
文摘The modern world remains vulnerable to natural disasters,including floods,earthquakes,wildfires,and others.These events remain unpredictable and inevitable,and recovering quickly and effectively requires significant effort and expense.Monitoring is becoming more efficient thanks to technologies such as Unmanned Aerial Vehicles(UAVs),which can access hard-to-reach areas and provide real-time data.However,in disaster-affected areas,these monitoring systems may encounter many obstacles when communicating with servers or transmitting monitored data.This paper proposes an adaptive communication model to overcome the challenges faced in disaster-affected areas.A base station is responsible for collecting data(such as images and videos)captured by UAVs performing surveillance within its communication range.This station is typically a tower providing fixed cellular network service.However,in the absence of such a tower,a selected UAV may serve as the station,depending on the situation.If surveillance needs to be performed outside the coverage area,it can continue to communicate via nearby UAVs through cooperative communication.UAVs with internet support,known as the Internet of Flying Things(IoFT),will also be utilized to enhance communication capacity and efficiency.The proposed communication model is validated through experiments,showing superior data transmission performance and higher throughput.Analysis indicates it outperforms traditional systems,even in rural areas,with or without internet access.
基金National Natural Science Foundation of China Grant Nos.52378543,52378544 and 52408525the Natural Science Foundation of Heilongjiang Grant No.LH2024E119。
文摘On December 18,2023,a magnitude 6.2 earthquake struck Jishishan County,Gansu Province,triggering a liquefaction-induced flow slide along the loess-mudstone contact zone and causing significant casualties and property losses.The event featured low-slope,large-scale,runout distance sliding and exhibited a clear cascading disaster chain.Its characteristics closely resemble the catastrophic mudflow at the nearby Lajia Ruins approximately 4,000 years ago.Using high-resolution oblique photogrammetry,cone penetration testing,surface wave analysis,and horizontal-to-vertical spectral ratio methods,this study examines the stratigraphy,groundwater conditions,and geomechanical properties of the affected zone.Results indicate that saturated loess overlying impermeable mudstone formed a high-moisture mass vulnerable to seismic disturbance.Seismic resonance triggered the liquefaction of weakly structured loess,which slide along the contact interface and evolved into a runout distance mudflow.Underground water and terrain modification created a composite weak zone of saturated loess and softened mudstone,which intensified the disaster chain-from earthquake to liquefaction,flow slide,and mudflow.This study contributes to the understanding of deep-seated liquefaction-flow slide disasters,thereby advancing more effective risk mitigation strategies in the Loess Plateau and comparable loess-covered seismic regions.
基金supported by the Key Laboratory of South China Sea Meteorological Disaster Prevention and Mitigation of Hainan Province(No.SCSF202307)the Basic Research Fund of CAMS(No.2023Z016)+1 种基金the National Natural Scientific Foundation of China(No.42275037)the Jiangsu Collaborative Innovation Center for Climate Change。
文摘In this study,tropical cyclone(TC)translation speed was introduced as a new similarity factor within the generalized initial value(GIV)framework,enhancing the disaster preassessment capability of the dynamical statistical analog ensemble forecast model for landfalling TC disasters(DSAEF_LTD model).Three TC translation speed indicators most relevant to TC precipitation were incorporated:the maximum speed on Day 1(the first day of TC-induced precipitation and wind occurring on land)and the average and minimum speeds over All Days(all days of TC-induced precipitation and wind occurring on land),all classified using the Kmeans clustering algorithm.Simulation experiments showed that integrating TC translation speed enhanced the model's performance.The model provided a better optimal common scheme,with the TSS UM(sum of threat scores for severe and above and extremely severe and above disasters)increasing by 2.66%(from 0.5117 to 0.5253)compared with the original model.More importantly,its preassessment ability improved significantly,with the average TSS UM for independent samples increasing by 6.43%(from 0.6488 to0.6905).The modified model demonstrated greater accuracy in capturing disaster severity and distribution of TCs with significant speed characteristics or with regular tracks.This improvement stemmed from reduced false alarms due to the selection of analogs that are more similar to the target TC.The enhanced preassessment ability can be attributed to the key role of TC translation speed,which significantly influences TC precipitation patterns and improves TC precipitation forecasting.Since precipitation is one of the most crucial disaster-causing factors,better TC precipitation forecasting leads to improved disaster preassessment outcomes.These findings emphasize the promising potential of the DSAEF_LTD model for future TC disaster research and management,contributing to the achievement of the Sustainable Development Goals set by the United Nations 2030 Agenda by strengthening coastal resilience.
基金financedby the National Natural Science Foundation of China(Grant No.52090083)the Shanghai Rising-Star Program(Grant No.23QB1404800).
文摘Water-sand gushing(WSG)disasters in confinedaquifers pose significantchallenges to the utilization of deep underground spaces in soft soil areas.Since few studies have considered the impact of confined aquifer thickness and confinedwater pressure on WSG disasters,a novel visual model test system was developed to investigate the influencingcharacteristics and mechanisms of the two aforementioned factors.The test results showed that the WSG process in clay aquiclude-confinedaquifer composite strata exhibits two prominent stages.First,the sand loss zone expands vertically in an ellipsoid shape.Then,it expands horizontally once the ellipsoid reaches the boundary of the clay layer.The sand loss continues until the overlying clay sinks to the bottom to clog the gushing crack,creating a large sinkhole at the surface.Increasing the confinedaquifer thickness can increase the vertical expansion of the ellipsoid and delay the clay-clogging effects,thereby considerably increasing the severity of sand loss,stratum deformation,and surface settlement.An increase in the confinedwater pressure markedly increases the hydraulic gradient along the seepage path,which contributes to increasing the gushing rates of water and sand.As a result,substantial sand loss occurs before the clay clogs the gushing crack,inducing more cracks and deeper sinkholes at the surface.All the aforementioned results provide insights into the effects of confinedaquifer on WSG disasters in clay aquiclude-confinedaquifer composite strata.
文摘At first glance(一瞥),10-year-old B.Kenit from the coastal town of Visakhapatnam in India looks like any other school-going child,but there is more than meets the eye.Inspired by a tsunami drill conducted in his school when he was eight,the third grader be-came a Disaster Risk Reduction(DRR)advocate,educating his fel-low students and community members on early warning,evacua-tion,and search and rescue.
基金the Ministry of Science and Technology National Key Research and Development Program(2023YFC3805000)the National Natural Science Foundation of China(52025083 and 52208501)the Shanghai Science and Technology Innovation Action Plan(22dz1201400).
文摘As centers of human activity,cities concentrate populations,resources,and wealth in limited areas.According to the United Nations,55%of the global population now lives in urban areas[1].Moreover,the World Economic Forum’s“Global Risks Report 2023”[2]highlights natural disasters as a major threat to sustainable development,especially for densely populated cities.
文摘The China Meteorological Administration(CMA)said that in the last five years,China has made big improvements in its weather services.This includes better weather forecasts and ways to protect people from disasters.
基金The Second Tibetan Plateau Scientific Expedition and Research Program,No.2019QZKK0903-02National Key R&D Program of China,No.2022YFC3002902National Natural Science Foundation of China,No.42201086。
文摘The Hengduan Mountains region(HMR)is one of the most densely distributed and severe flash flood disaster-prone areas in southwest China.It is also a key area for major engineering projects and beautiful countryside construction in Southwest China.However,previous studies have not systematically summarized the development characteristics and formation modes of flash flood disasters in the HMR,which limits the development of theoretical and technical system for flood control.In this study,we focused on the physical processes of flash flood disasters in the HMR,including generation,movement,and disaster formation,and clarified the dominant disaster-inducing conditions(multiple humid monsoon circulation,high potential energy and high heterogenous underlying surface)and disaster development characteristics(high spatio-temporal heterogeneity,highly concentrated energy,chain and cascading effects,and clustered occurrence)of flash floods in the HMR.Based on the entire processes of flash flood disasters,three major formation modes have been summarized:the runoff generation mode of vegetation-hydrology-soil coupling dominated by high hydraulic gradient in mountainous areas,strong flow-sediment coupling movement,and serious disaster losses due to high exposure of disaster bearing objects.Finally,based on the issues in previous research,four future research challenges for flash flood disaster in the HMR were proposed.Our study provides insights into disaster prevention and reduction research,including fundamental theoretical system,precise risk assessment of regional disasters,and accurate early warning and forecasting of flash floods.
基金supported by the National Natural Science Foundation of China(Nos.52273220 and 22205243)。
文摘Snow and freezing disasters are recurrent weather and climate phenomena that affect the world annually.These events exert a significant influence on numerous aspects of life,including transportation,power supply,and daily activities,and result in considerable economic losses.This study aims to provide a comprehensive analysis of the regions affected by these disasters,the preventive and responsive measures employed,recent advancements in key materials,and the challenges encountered.By doing so,we can gain a deeper understanding of the vital role,significant advantages,and untapped potential of key materials for effectively preventing and responding to snow and freezing disasters.Furthermore,promoting research and utilization of these materials not only contributes to the development of the safety and emergency equipment industry but also strengthens the supply of advanced and suitable safety and emergency equipment.
文摘This study draws from detailed qualitative case studies of three schools that practise disaster risk reduction (DRR) education initiatives in their curriculum in Nepal. Using curriculum mapping and discourse analysis, it aims to elaborate the significance of relevant disaster risk reduction (DRR) content in school curriculum to prepare youths for disaster response and recovery. It elaborates the nature of the current DRR content covered in curricula and textbooks and provides suggestions to address the identified disaster-related issues in the school curriculum. It further elaborates that incorporation of local and contextualised DRR content in school curricula contributes to the establishment of the “culture of resilience” in disaster prone context like Nepal. It concludes that more organised and holistic approach is essential to develop disaster and management knowledge, skills and attitudes to youths.
基金DGAPA-UNAM for providing financial support to conduct landslide risk research through Project PAPIIT IN300823。
文摘Landslides represent a growing global challenge,particularly in mountainous and rapidly urbanising regions where environmental degradation and socio-economic vulnerabilities converge.This study investigates the interrelationships between Integrated Landslide Disaster Risk Management(ILDRiM)and the United Nations Sustainable Development Goals(SDGs),advancing a systemsbased understanding of landslide risk as a socially constructed and development-driven phenomenon.Drawing on a narrative literature review and a Design Structure Matrix(DSM),the research identifies eight critical drivers of landslide disaster risk:deforestation,climate change,urbanisation,infrastructure development,community vulnerability,exposure to landslides,ineffective governance,and lack of scientific integration into policymaking.The DSM framework systematically maps these drivers against the 17 SDGs to evaluate the nature and strength of their interactions.The analysis reveals significant synergies,where addressing specific drivers supports multiple SDGs,and trade-offs,where risk reduction efforts may inadvertently hinder other development objectives if not implemented inclusively and strategically.Findings underscore the transformative potential of embedding ILDRiM within national and local development frameworks.Prioritising governance reform,scientific innovation,and resilient infrastructure(SDGs 16,17,and 9)is particularly effective for advancing landslide risk reduction while supporting broader sustainability outcomes.The study also highlights the need for anticipatory,cross-sectoral,and community-driven approaches to risk governance.This research offers actionable insights for policymakers,practitioners,and researchers seeking to align disaster risk management with sustainable development planning.It proposes a novel methodology for assessing systemic interlinkages between disaster risk drivers and the SDGs.It calls for further research to refine data integration,address context-specific risks,and strengthen the evidence base for risk-informed development.By operationalising ILDRiM through the SDG framework,this study supports creating more resilient,equitable,and sustainable communities in landslide-prone regions.
文摘Located on the mountainous western edge of Beijing Municipality,Mentougou District is renowned for its breathtaking natural landscapes and rich cultural heritage.On 22 June,I had the opportunity to visit the district,nearly two years after it was struck by a catastrophic flood that left widespread destruction in its wake.My visit provided a unique opportunity to observe the ongoing recovery e!orts and evaluate how the district has leveraged coordinated planning,technology and the resilience of its people to rebuild.The purpose of the visit was to witness these recovery e!orts firsthand and gain insight into the strategies that have helped Mentougou overcome the lingering e!ects of this environmental disaster.
基金financial support from the National Science Foundation(NSF)EPSCoR R.I.I.Track-2 Program,awarded under the NSF grant number 2119691.
文摘The increasing frequency and severity of natural disasters,exacerbated by global warming,necessitate novel solutions to strengthen the resilience of Critical Infrastructure Systems(CISs).Recent research reveals the sig-nificant potential of natural language processing(NLP)to analyze unstructured human language during disasters,thereby facilitating the uncovering of disruptions and providing situational awareness supporting various aspects of resilience regarding CISs.Despite this potential,few studies have systematically mapped the global research on NLP applications with respect to supporting various aspects of resilience of CISs.This paper contributes to the body of knowledge by presenting a review of current knowledge using the scientometric review technique.Using 231 bibliographic records from the Scopus and Web of Science core collections,we identify five key research areas where researchers have used NLP to support the resilience of CISs during natural disasters,including sentiment analysis,crisis informatics,data and knowledge visualization,disaster impacts,and content analysis.Furthermore,we map the utility of NLP in the identified research focus with respect to four aspects of resilience(i.e.,preparedness,absorption,recovery,and adaptability)and present various common techniques used and potential future research directions.This review highlights that NLP has the potential to become a supplementary data source to support the resilience of CISs.The results of this study serve as an introductory-level guide designed to help scholars and practitioners unlock the potential of NLP for strengthening the resilience of CISs against natural disasters.
文摘A terrible disaster struck our town last month,which brought heavy rain and strong winds all night.Many houses were damaged,and some even fell down,leaving hundreds of people homeless.However,what surprised us most was the great unity shown by everyone.Neighbors helped each other carry things,sharing food and warm clothes,while volunteers from other towns came to offer support.With everyone's efforts,we started the recovery work quickly,which made us believe that we could rebuild our home soon.
基金Supported by European Union’s Horizon 2020 Research and Innovation Program(739578)the Government of the Republic of Cyprus through the Deputy Ministry of Research,Innovation,and Digital Policy.
文摘Background Efficient disaster victim detection(DVD)in urban areas after natural disasters is crucial for minimizing losses.However,conventional search and rescue(SAR)methods often experience delays,which can hinder the timely detection of victims.SAR teams face various challenges,including limited access to debris and collapsed structures,safety risks due to unstable conditions,and disrupted communication networks.Methods In this paper,we present DeepSafe,a novel two-level deep learning approach for multilevel classification and object detection using a simulated disaster victim dataset.DeepSafe first employs YOLOv8 to classify images into victim and non-victim categories.Subsequently,Detectron2 is used to precisely locate and outline the victims.Results Experimental results demonstrate the promising performance of DeepSafe in both victim classification and detection.The model effectively identified and located victims under the challenging conditions presented in the dataset.Conclusion DeepSafe offers a practical tool for real-time disaster management and SAR operations,significantly improving conventional methods by reducing delays and enhancing victim detection accuracy in disaster-stricken urban areas.
基金supported by Kunming University of Science and Technology 2024 graduate course ideological and political case construction project(109920240103)Case construction project of AI-enabled postgraduate talent training in Kunming University of Technology,the Yunnan Fundamental Research Projects(202501AT070358 and 202401AU070142)+1 种基金the Scientific Research Fund Program of Yunnan Provincial Department of Education(2024J0078)Talent Cultivation Fund Project of Kunming University of Science and Technology(KKZ3202467041 and KKZ3202467045).
文摘In response to the three major contradictions,safety,cognition,and ability cultivation,existing in the practical teaching of geological hazard courses,this paper proposes a“virtual-real integration”teaching reform scheme,using earthquake disasters as an example.By integrating digital twin technology and artificial intelligence technology,a four-layer teaching framework consisting of data layer,model layer,platform layer,and intelligent layer is constructed.Progressive teaching segments of“cognition-simulation-decision-making”are designed to establish a comprehensive training path from seismic geological survey to disaster early warning and decision-making.This scheme shifts the traditional field practice venue to a safe virtual environment,promotes students’understanding of geological hazards from static fragments to dynamic processes,enhances their comprehensive decision-making ability in geological disaster prevention and mitigation,and provides theoretical support and practical guidance for cultivating interdisciplinary talents in geological hazard prevention.
基金supported by the Anesthesiology Department Teaching Development Foundation of Naval Medical University(2024MZQN03)the Teaching Research and Reform Project of Naval Medical University(JYG2024B24).
文摘Artificial Intelligence is profoundly transforming innovation and development in healthcare and education.In this study,we developed an AI-empowered blended learning model for disaster medicine.Leveraging the Rain Classroom platform,we established a comprehensive intelligent teaching support system covering the entire learning cycle-pre-class,in-class,and post-class.Through AI-driven enhancements,the model enables intelligent resource allocation,personalized learning paths,and high-fidelity simulation of practical training scenarios.Moreover,it addresses key challenges in traditional disaster medicine education,including fragmented knowledge delivery,insufficient practical training environments,and limited evaluation methods.Ultimately,the model enhances both the efficiency and effectiveness of disaster medicine education.
文摘Based on the site investigation of a lightning stroke accident in a coal mine in Weiyuan County during a strong thunderstorm process on the night of August 10,2024,combined with the investigation data of the accident site,the causes of the lightning stroke accident were analyzed,and the corresponding rectification suggestions were put forward.
基金supported by the National Institute of Natural Hazards,Ministry of Emergency Management of China(2023-JBKY-57)the National Natural Science Foundation of China(42077259)。
文摘Rainfall-induced landslides are often highly destructive.Reviewing and analyzing the causes,processes,impacts,and deficiencies in emergency response is critical for improving disaster prevention and management.From the night of July 21 to the morning of July 22,2024,the Kencho Shacha Gozdi Village in Gezei Gofa,Southern Nations,Nationalities,and Peoples'Region,Ethiopia,suffered heavy rainfall that triggered two landslides.By July25,this event had claimed at least 257 lives.This study presents a detailed characterization of the landslides using multi-source data.By analyzing the landslide disaster process,this study summarizes key lessons and provides suggestions for preventing rainfall-induced geological hazards.The results indicate that rainfall has the greatest impact on the occurrence of landslides,while lithology and human activities have promoted and strengthened the landslide disaster.Despite the active disaster response in the local area,many problems were still exposed in the emergency response work.This analysis offers valuable insights for mitigating rainfall-induced geological hazards and enhancing emergency response capabilities.
基金supported by National Natural Science Foundation of Joint Fund for Changjiang River Water Science Research(U2340201)National Natural Science Foundation of China(52239006)Natural Science Foundation of Sichuan Province(2024NSFSC0005).
文摘Rainstorm-induced flood hazards in mountainous areas often result in complex cascading effects by interacting with environmental and human systems.However,traditional studies typically categorize them simply as clearwater floods or debris floods/flows,overlooking their evolutionary characteristics and compound impacts.This study presents a novel classification-based approach to investigate the formation and destructive mechanisms of a catastrophic composite disaster of flash flood and debris flow in the Dayao Gully(DYG)catchment in Hanyuan County,Sichuan Province,China.The event resulted in 14 fatalities,25 missing persons,and extensive infrastructure damage.Through comprehensive field investigations and multi-method analysis,three distinct disaster zones were identified with different magnitudes and impacts:(1)a clearwater flood disaster region with minimal geomorphological changes under a 5-year return period rainfall;(2)a debris flood disaster region triggered by a 30-year return period rainfall,leading to intense sediment transport with a total deposit volume of 52,511 m^(3);and(3)a sediment-induced flood disaster region characterized by significant riverbed aggradation and infrastructure destruction due to sediment-induced blockage effects.The results reveal that the cascading characteristics of this composite disaster were primarily driven by intense rainfall,enhanced sediment transport motivated by supracritical shear stress,and interactions with human infrastructure(e.g.,bridges and buildings).This classification-based approach provides a quantitative assessment of spatial characteristics of cascading flood disasters,offering new insights into their evolutionary characteristics and highlighting the necessity for targeted disaster mitigation strategies in sedimentprone mountainous regions.
