Economic losses and catastrophic casualties may occur once super high-rise structures are struck by low-probability but high-consequence scenarios of concurrent earthquakes and winds. Therefore, accurately predicting ...Economic losses and catastrophic casualties may occur once super high-rise structures are struck by low-probability but high-consequence scenarios of concurrent earthquakes and winds. Therefore, accurately predicting multi-hazard dynamic responses to super high-rise structures has significant engineering and scientific value. This study performed a parametric global sensitivity analysis (GSA) for multi-hazard dynamic response prediction of super high-rise structures using the multiple-degree-of-freedom shear (MFS) model. Polynomial chaos Kriging (PCK) was introduced to build a surrogate model that allowed GSA to be combined with Sobol’ indices. Monte Carlo simulation (MCS) is also conducted for the comparison to verify the accuracy and efficiency of the PCK method. Parametric sensitivity analysis is performed for a wide range of aleatory uncertainty (intensities of coupled multi-hazard), epistemic uncertainty (bending stiffness, k_(m);shear stiffness, kq;density, ρ;and damping ratio, ξ), probability distribution types, and coefficients of variation. The results indicate that epistemic uncertainty parameters, k_(m), ρ, and ξ dramatically affect the multi-hazard dynamic responses of super high-rise structures;in addition, Sobol’ indices between the normal and lognormal distributions are insignificant, while the variation levels have remarkably influenced the sensitivity indices.展开更多
Underground infrastructure(UI)plays a great important role in the urbanization and modernization of megacities in the world.However,the intensive development of the UI during the past decades has posed great risks to ...Underground infrastructure(UI)plays a great important role in the urbanization and modernization of megacities in the world.However,the intensive development of the UI during the past decades has posed great risks to the safety of city infrastructures under the impact of multi-hazards,especially with the condition of global climate change.In this paper,a general conceptualized framework to assess the resilience of UI in cities under multihazards impact is proposed.The urban tunnel system,e.g.,metro tunnel,road tunnel etc.,is selected as the typical underground infrastructure discussed with the emphasis both on the structural level in terms of mechanical behaviors and system level in terms of network efficiency.The hazards discussed in this paper include the natural hazards and human-related ones,with emphasis on earthquake,flood,and aggressive disturbances caused by human activities.After the general framework proposed for resilience of the structural and network behavior of the UI,two application examples are illustrated.The structural resilience of the shield tunnel under earthquake impact is analyzed by using the proposed resilience model,and the network resilience of the road tunnel system under the flood impact due to climate change is analyzed,respectively.The resilience enhancement by using the adaptive design strategy of real-time observational method is mathematically presented in this case.Some other practical engineering recovery measures are briefly discussed at the end of this application example.The findings in the application examples should be helpful to enhance the resilience-based design of the structural and network of tunnels from the component to the system level.展开更多
Storm surge events(SSEs)involve multiple hazard-causing factors,such as surges,extreme rainfall,strong winds,waves,and ocean currents,which have destructive impacts on coastal regions.For a quantitative multi-hazard a...Storm surge events(SSEs)involve multiple hazard-causing factors,such as surges,extreme rainfall,strong winds,waves,and ocean currents,which have destructive impacts on coastal regions.For a quantitative multi-hazard assessment of SSEs,this study introduced the concept of the storm surge event seawater-atmosphere system(SSE-SAS)and proposed the system energy equivalence(SEE)model from a systemic energy perspective.SEE was obtained by employing a parameterization approach,and the hazard index(HI)and the concept of most significant hazard(MSH)were adopted to evaluate the severity of SSE-SAS.SEE at five stations in the Shandong Peninsula was calculated from 2005 to 2019,and probability analysis and hazard assessment were further conducted.Results show that the SEE of SSE-SAS ranges from 0.029×10^(3) to 30.418×10^(3) J/m^(2),and it exhibits an insignificant decreasing trend from 2005 to 2019.The SEE of SSE-SAS in the west of the Shandong Peninsula is greater than that in the east.Moreover,storm waves,storm surges,and storm rainfall are the major contributors to SEE,which exhibit different spatial patterns and characters in different SSE-SAS types.The HI of SSE-SAS at five stations is no more than medium hazard level,with MSH at return periods of 2-to 4-year level.This study provides a new approach for quantifying multi-hazard SSEs,which offers scientific insights for regional multi-hazard risk reduction and mitigation efforts.展开更多
This study advances the DRASTIC groundwater vulnerability assessment framework by integrating a multi-hazard groundwater index(MHGI)to account for the dynamic impacts of diverse anthropogenic activities and natural fa...This study advances the DRASTIC groundwater vulnerability assessment framework by integrating a multi-hazard groundwater index(MHGI)to account for the dynamic impacts of diverse anthropogenic activities and natural factors on both groundwater quality and quantity.Incorporating factors such as population growth,agricultural practices,and groundwater extraction enhances the framework’s ability to capture multi-dimensional,spatiotemporal changes in groundwater vulnerability.Additional improvements include refined weighting and rating scales for thematic layers based on available observational data,and the inclusion of distributed recharge.We demonstrate the practical utility of this dynamic DRASTIC-based framework through its application to the agro-urban regions of the Irrigated Indus Basin,a major groundwater-dependent agricultural area in South Asia.Results indicate that between 2005 and 2020,54%of the study area became highly vulnerable to pollution.The MHGI revealed a 13%decline in potential groundwater storage and a 25%increase in groundwater-stressed zones,driven primarily by population growth and intensive agriculture.Groundwater vulnerability based on both groundwater quality and quantity dimensions showed a 19%decline in areas of low to very low vulnerability and a 6%reduction in medium vulnerability zones by 2020.Sensitivity analyses indicated that groundwater vulnerability in the region is most influenced by groundwater recharge(42%)and renewable groundwater stress(38%).Validation with in-situ data yielded area under the curve values of 0.71 for groundwater quality vulnerability and 0.63 for MHGI.The framework provides valuable insights to guide sustainable groundwater management,safeguarding both environmental integrity and human well-being.展开更多
Global climate change,climate extremes,and overuse of natural resources are all major contributors to the risk brought on by cyclones.In I West Bengal state of India,the Pathar Pratima Block frequently experiences a v...Global climate change,climate extremes,and overuse of natural resources are all major contributors to the risk brought on by cyclones.In I West Bengal state of India,the Pathar Pratima Block frequently experiences a variety of risks that result in significant loss of life and livelihood.In order to govern coastal society,it is crucial to measure and map the multi-hazards risk status.To depict the multi-hazards vulnerability and risk status,no cutting-edge models are currently being applied.Predicting distinct physical vulnerabilities is possible using a variety of cutting-edge machine learning techniques.This study set out to precisely describe multi-hazard risk using powerful machine learning methods.This study involved the use of Analytic Hierarchical Analysis and two cutting-edge machine-learning algorithms-Random Forest and Artificial Neural Network,which are yet underutilized in this area.The multi-hazards risk was determined by taking into account six criteria.The southern and eastern regions of the research area are clearly identified by the multi-hazards risk maps as having high to extremely high hazards risk levels.Cyclonic hazards and embankment breaching are the main dominant factors among the multi-hazards.The machine learning approach is the most accurate model for mapping the multi-hazards risk where the ROC result of Random forest and artificial neural network is more than the conventional method AHP.Here RF is the most validated model than the other two.The effectiveness,root mean square error,true skill statistics,Friedman and Wilcoxon rank test,and area under the curve of receiver operating characteristic tests were used to evaluate the prediction capacity of newly constructed models.The RMSE values of 0.24 and 0.26,TSS values of 0.82 and 0.73,and AUC values of 88.20%and 89.10%as produced by RF and ANN models,respectively,were all excellent.展开更多
With the implementation of significant national strategies and rapid socioeconomic development,many ultra-long deep tunnels are being constructed in the Qinghai–Xizang Plateau region.However,the extreme complexity an...With the implementation of significant national strategies and rapid socioeconomic development,many ultra-long deep tunnels are being constructed in the Qinghai–Xizang Plateau region.However,the extreme complexity and variability of the environment in this region pose significant challenges to the safe construction and long-term operation of the planned or under-construction ultra-long deep tunnels.To address these complex technical challenges,this paper provides a detailed analysis of the complex climate and geology features of the Qinghai–Xizang Plateau during tunnel construction.The climate characteristics of the Qinghai–Xizang Plateau include severe coldness,low oxygen,and unpredictable weather changes.The geological characteristics include complex stress distributions caused by the intense internal and external dynamic coupling of tectonic plates,widespread active tectonic structures,frequent high-intensity earthquakes,fractured rock masses,and numerous active fault zones.Based on the analysis,this paper elaborates on potential sources of major disasters resulting from the characteristics of ultra-long deep tunnel projects in the Qinghai–Xizang Plateau region.These potential disaster sources include the crossing of active fault zones,high geostress rockbursts,large deformation disasters,high-pressure water surges,geothermal hazards,inadequate long-distance ventilation and oxygen supply,and multi-hazard couplings.In response to these challenges,this paper systematically summarizes the latest research progress and technological achievements in the domestic and international literature,and proposes innovative ideas and future development prospects for disaster monitoring and early warning,mechanized intelligent construction,long-term safety services,and emergency security and rescue.These innovative measures are intended to address the challenges of tunnel disaster prevention and control in the complex environment of the Qinghai–Xizang Plateau,contributing to the safe construction and long-term operation of ultra-long deep tunnels in this region.展开更多
In the U.S., the current Load and Resistance Factor Design （LRFD） Specifications for highway bridges is a reliability-based formulation that considers failure probabilities of bridge components due to the actions of...In the U.S., the current Load and Resistance Factor Design （LRFD） Specifications for highway bridges is a reliability-based formulation that considers failure probabilities of bridge components due to the actions of typical dead load and frequent vehicular loads. Various extreme load effects, such as earthquake and vessel collision, are on the same reliability-based platform. Since these extreme loads are time variables, combining them with not considered frequent. non- extreme loads is a significant challenge. The number of design limit state equations based on these failure probabilities can be unrealistically large and unnecessary from the view point of practical applications. Based on the opinion of AASHTO State Bridge Engineers, many load combinations are insignificant in their states. This paper describes the formulation of a criterion to include only the necessary load combinations to establish the design limit states. This criterion is established by examining the total failure probabilities for all possible time-invariant and time varying load combinations and breaking them down into partial terms. Then, important load combinations can be readily determined quantitatively,展开更多
Multi-hazard susceptibility prediction is an important component of disasters risk management plan.An effective multi-hazard risk mitigation strategy includes assessing individual hazards as well as their interactions...Multi-hazard susceptibility prediction is an important component of disasters risk management plan.An effective multi-hazard risk mitigation strategy includes assessing individual hazards as well as their interactions.However,with the rapid development of artificial intelligence technology,multi-hazard susceptibility prediction techniques based on machine learning has encountered a huge bottleneck.In order to effectively solve this problem,this study proposes a multi-hazard susceptibility mapping framework using the classical deep learning algorithm of Convolutional Neural Networks(CNN).First,we use historical flash flood,debris flow and landslide locations based on Google Earth images,extensive field surveys,topography,hydrology,and environmental data sets to train and validate the proposed CNN method.Next,the proposed CNN method is assessed in comparison to conventional logistic regression and k-nearest neighbor methods using several objective criteria,i.e.,coefficient of determination,overall accuracy,mean absolute error and the root mean square error.Experimental results show that the CNN method outperforms the conventional machine learning algorithms in predicting probability of flash floods,debris flows and landslides.Finally,the susceptibility maps of the three hazards based on CNN are combined to create a multi-hazard susceptibility map.It can be observed from the map that 62.43%of the study area are prone to hazards,while 37.57%of the study area are harmless.In hazard-prone areas,16.14%,4.94%and 30.66%of the study area are susceptible to flash floods,debris flows and landslides,respectively.In terms of concurrent hazards,0.28%,7.11%and 3.13%of the study area are susceptible to the joint occurrence of flash floods and debris flow,debris flow and landslides,and flash floods and landslides,respectively,whereas,0.18%of the study area is subject to all the three hazards.The results of this study can benefit engineers,disaster managers and local government officials involved in sustainable land management and disaster risk mitigation.展开更多
Natural hazards are often studied in isolation.However,there is a great need to examine hazards holistically to better manage the complex of threats found in any region.Many regions of the world have complex hazard la...Natural hazards are often studied in isolation.However,there is a great need to examine hazards holistically to better manage the complex of threats found in any region.Many regions of the world have complex hazard landscapes wherein risk from individual and/or multiple extreme events is omnipresent.Extensive parts of Iran experience a complex array of natural hazards-floods,earthquakes,landslides,forest fires,subsidence,and drought.The effectiveness of risk mitigation is in part a function of whether the complex of hazards can be collectively considered,visualized,and evaluated.This study develops and tests individual and collective multihazard risk maps for floods,landslides,and forest fires to visualize the spatial distribution of risk in Fars Province,southern Iran.To do this,two well-known machine-learning algorithms-SVM and MARS-are used to predict the distribution of these events.Past floods,landslides,and forest fires were surveyed and mapped.The locations of occurrence of these events(individually and collectively) were randomly separated into training(70%) and testing(30%) data sets.The conditioning factors(for floods,landslides,and forest fires) employed to model the risk distributions are aspect,elevation,drainage density,distance from faults,geology,LULC,profile curvature,annual mean rainfall,plan curvature,distance from man-made residential structures,distance from nearest river,distance from nearest road,slope gradient,soil types,mean annual temperature,and TWI.The outputs of the two models were assessed using receiver-operating-characteristic(ROC) curves,true-skill statistics(TSS),and the correlation and deviance values from each models for each hazard.The areas-under-the-curves(AUC) for the MARS model prediction were 76.0%,91.2%,and 90.1% for floods,landslides,and forest fires,respectively.Similarly,the AUCs for the SVM model were 75.5%,89.0%,and 91.5%.The TSS reveals that the MARS model was better able to predict landslide risk,but was less able to predict flood-risk patterns and forest-fire risk.Finally,the combination of flood,forest fire,and landslide risk maps yielded a multi-hazard susceptibility map for the province.The better predictive model indicated that 52.3% of the province was at-risk for at least one of these hazards.This multi-hazard map may yield valuable insight for land-use planning,sustainable development of infrastructure,and also integrated watershed management in Fars Province.展开更多
Many urban areas are located in regions of moderate seismicity and are subjected to strong wind. Buildings in these regions are often designed without seismic provisions. As a result, in the event of an earthquake, th...Many urban areas are located in regions of moderate seismicity and are subjected to strong wind. Buildings in these regions are often designed without seismic provisions. As a result, in the event of an earthquake, the potential for damage and loss of lives may not be known. In this paper, the performance of a typical high-rise building with a thick transfer plate （TP）, which is one type of building structure commonly found in Hong Kong, is assessed against both earthquake and wind hazards. Seismic- and wind-resistant performance objectives are first reviewed based on relevant codes and design guidelines for high-rise buildings. After a brief introduction of wind-resistant design of the building, various methodologies, including equivalent static load analysis （ESLA）, response spectrum analysis （RSA）, pushover analysis （POA）, linear and nonlinear time-history analysis （LTHA and NTHA）, are employed to assess the seismic performance of the building when subjected to frequent earthquakes, design based earthquakes and maximum credible earthquakes. The effects of design wind and seismic action with a common 50-year return period are also compared. The results indicate that most performance objectives can be satisfied by the building, but there are some objectives, such as inter-story drift ratio, that cannot be achieved when subjected to the frequent earthquakes. It is concluded that in addition to wind, seismic action may need to be explicitly considered in the design of buildings in regions of moderate seismicity.展开更多
Yogyakarta is one of the large cities in Central Java,located on Java Island,Indonesia.The city,and the Pleret sub-district,where the study has taken place,is prone to earthquake hazards,because it is close to several...Yogyakarta is one of the large cities in Central Java,located on Java Island,Indonesia.The city,and the Pleret sub-district,where the study has taken place,is prone to earthquake hazards,because it is close to several seismically active zones,such as the Sunda Megathrust and the active fault known as the Opak Fault.Since a devastating earthquake of 2006,the population of the Pleret sub-district has increased significantly.Thus,the housing demand has increased,and so is the pace of low-cost housing that does not meet earthquake-safety requirements,and furthermore are often located on unstable slopes.The local alluvial material covering a jigsaw of unstable blocks and complex slope is conditions that can amplify the negative impacts of earthquakes.Within this context,this study is aiming to assess the multi-hazards and risks of earthquakes and related secondary hazards such as ground liquefaction,and coseismic landslides.To achieve this,we used geographic information systems and remote sensing methods supplemented with outcrop study and existing seismic data to derive shear-strain parameters.The results have revealed the presence of numerous uncharted active faults with movements visible from imagery and outcrops.show that the middle part of the study area has a complex geological structure,indicated by many unchartered faults in the outcrops.Using this newly mapped blocks combined with shear strain data,we reassessed the collapse probability of buildings that reach level>0.75 near the Opak River,in central Pleret sub-district.Classifying the buildings and from population distribution,we could determine that the highest risk was during nighttime as the buildings susceptible to fall are predominantly housing buildings.The secondary hazards follow a slightly different distribution with a concentration of risks in the West.展开更多
Digital elevation models(DEMs)are essential tools in environmental science,particularly for hazard assessments and landscape analyses.However,their application acrossmultiple environmental hazards simultaneously remai...Digital elevation models(DEMs)are essential tools in environmental science,particularly for hazard assessments and landscape analyses.However,their application acrossmultiple environmental hazards simultaneously remains in need for a multi-aspect critical assessment to promote their effectiveness in comprehensive risk management.This paper aims to review and critically assess the application of DEMs in mapping and managing specific environmental hazards,namely floods,landslides,and coastal erosion.In this regard,it seeks to promote their utility of hazard maps as key tools in disaster risk reduction and environmental planning by employing high-resolution DEMs integrated with advanced geographic information systems.The findings offer valuable insights into optimizing DEM technology for environmental management,contributing to safer and more resilient communities.The paper addresses an important gap in the geospatial analysis of natural hazards and serves as a foundational reference for future advancements in the field,emphasizing its importance to academic researchers and practical stakeholders in environmental and disaster management.展开更多
This study introduces an advanced community-level resilience analysis methodology integrating 3D fragility sur-faces for combined successive earthquake-tsunami hazard and analysis.The methodology facilitates comprehen...This study introduces an advanced community-level resilience analysis methodology integrating 3D fragility sur-faces for combined successive earthquake-tsunami hazard and analysis.The methodology facilitates comprehen-sive evaluations of spatial damage,economic loss,and risk under multi-hazard conditions.This study compares earthquake-only analysis results to the successive earthquake-tsunami analysis at the community level to reveal-and quantify-significant disparities in damage and loss estimations between the analyses,emphasizing the need to consider both hazards in community planning even at lower seismic intensities.Critical assessment of the FEMA combinational rule demonstrates its limitations in accurately predicting losses and damage patterns at higher hazard intensities,highlighting the necessity for refined models that accurately account for hazard inter-actions.This research advances multi-hazard community-level resilience analysis by offering a robust framework for earthquake and tsunami assessment,underscoring the need for integration of detailed multi-hazard analy-ses into resilience planning.Finally,it suggests future directions for enhancing framework applicability across diverse community settings and structural types,aiming to improve community resilience.展开更多
In many regions of the world, a bridge will experience multiple extreme hazards during its expected service life. The current American Association of State Highway and Transportation Officials （AASHTO） load and resi...In many regions of the world, a bridge will experience multiple extreme hazards during its expected service life. The current American Association of State Highway and Transportation Officials （AASHTO） load and resistance factor design （LRFD） specifications are formulated based on failure probabilities, which are fully calibrated for dead load and nonextreme live loads. Design against earthquake loads is established separately. Design against scour effect is also formulated separately by using the concept of capacity reduction （or increased scour depth）. Furthermore, scour effect cannot be linked directly to an LRFD limit state equation, because the latter is formulated using force-based analysis. This paper （in two parts） presents a probability-based procedure to estimate the combined hazard effects on bridges due to truck, earthquake and scour, by treating the effect of scour as an equivalent load effect so that it can be included in reliability-based bridge failure calculations. In Part I of this series, the general principle of treating the scour depth as an equivalent load effect is presented. The individual and combined partial failure probabilities due to truck, earthquake and scour effects are described. To explain the method of including non-force-based natural hazards effects, two types of common scour failures are considered. In Part 11, the corresponding bridge failure probability, the occurrence of scour as well as simultaneously having both truck load and equivalent scour load are quantitatively discussed.展开更多
In many regions of the world, a bridge will experience multiple extreme hazards during its expected service life. The current American Association of State Highway and Transportation Officials （AASHTO） load and resi...In many regions of the world, a bridge will experience multiple extreme hazards during its expected service life. The current American Association of State Highway and Transportation Officials （AASHTO） load and resistance factor design （LRFD） specifications are formulated based on failure probabilities, which are fully calibrated for dead load and non-extreme live loads. Design against earthquake load effect is established separately. Design against scour effect is also formulated separately by using the concept of capacity reduction （or increased scour depth）. Furthermore, scour effect cannot be linked directly to an LRFD limit state equation because the latter is formulated using force-based analysis. This paper （in two parts） presents a probability-based procedure to estimate the combined hazard effects on bridges due to truck, earthquake and scour, by treating the effect of scour as an equivalent load effect so that it can be included in reliability-based failure calculations. In Part I of this series, the general principle for treating the scour depth as an equivalent load effect is presented. In Part II, the corresponding bridge failure probability, the occurrence of scour as well as simultaneously having both truck load and equivalent scour load effect are quantitatively discussed. The key formulae of the conditional partial failure probabilities and the necessary conditions are established. In order to illustrate the methodology, an example of dead, truck, earthquake and scour effects on a simple bridge pile foundation is represented.展开更多
The increasing frequency and intensity of natural disasters necessitate advanced prediction techniques to mitigate potential damage.This study presents a comprehensive multi-hazard early warning framework by integrati...The increasing frequency and intensity of natural disasters necessitate advanced prediction techniques to mitigate potential damage.This study presents a comprehensive multi-hazard early warning framework by integrating the multi-source data fusion technique.A multi-source data extraction method was introduced by extracting pressure level and average precipitation data based on the hazard event from the Cooperative Open Online Landslide Repository(COOLR)dataset across multiple temporal intervals(12 h to 1 h prior to events).Feature engineering was performed using Choquet fuzzy integral-based importance scoring,which enables the model to account for interactions and uncertainty across multiple features.Three individual Long Short-Term Memory(LSTM)models were trained for hazard location,average precipitation,and hazard category(i.e.,to detect the potential of natural disasters).These models were trained on varying temporal scales from 12 to 1 h prior to the event.These individual models achieved the performance of Mean Absolute Error(MAE)2.2 and 3.2,respectively,for the hazard location and average precipitation models,and an F1-score of 0.825 for the hazard category model.The results also indicate that the LSTM model outperformed traditional Machine Learning(ML)models,and the use of the fuzzy integral enhanced the prediction capability by 8.12%,2.6%,and 6.37%,respectively,for all three individual models.Furthermore,a rule-based algorithm was developed to synthesize the outputs from the individual models into a 3×3 grid of multi-hazard warnings.These findings underscore the effectiveness of the proposed framework in advancing multi-hazard forecasting and situational awareness,offering valuable support for timely and data-driven emergency response planning.展开更多
The spatial distribution of the world population is uneven,with a density of about 40%living in coastal regions.The trend is expected to continue in both demographic indicators and urban development rate,being many co...The spatial distribution of the world population is uneven,with a density of about 40%living in coastal regions.The trend is expected to continue in both demographic indicators and urban development rate,being many coastal cities in seismic-and tsunami-prone regions and built through informal and unplanned settlements,exposing their population and assets to such hazards.Recent tectonic-triggered events raised awareness of the cascading earthquake and tsunami threat and highlighted the paucity of structural design criteria considering the cumulative effects of both.By being exposed to the ground-motion,the structures’resistance may decrease and become residual/non-existent to support the incoming tsunami,implying an underestimation of the risk.Risk management can benefit from reinforcing the ties between natural hazards and engineering practitioners,linking science and industry,and promoting dialogue between risk analysts and policy-makers.Motivated by the expansion plans of an internationally-sized deep-water port located in a tsunami-prone region,a reflection on the work needed to perform a multi-risk assessment and the challenges yet to overcome is introduced to emphasize the challenge of combining safety requirements with financial and ecologic concerns.A conceptual interdisciplinarybased methodology is proposed to support uncertainty-aware,systematic and informed decisions.展开更多
Directive 2022/2557 from the European Commission aims to enhance the resilience of critical entities in Europe by integrating with existing European legislation,but it lacks explicit guidance on addressing vulnerabili...Directive 2022/2557 from the European Commission aims to enhance the resilience of critical entities in Europe by integrating with existing European legislation,but it lacks explicit guidance on addressing vulnerabilities.Specifially,major hazard industries(MHls)are critical infrastructures that face unique risks arising from the interactions of natural and technological hazards(NaTech events);nevertheless,existing policies frequently overlook the potential vulnerabilities of process plants to these complex phenomena.The goal of this research was to systematically characterize the vulnerability of industrial critical infrastructures(ICIs)to various hazards in their territories.A multi-scale procedure was implemented in the Italian context as a case study,where spatial analyses were developed using open data.Starting from the Italian national inventory,the MHIs were clustered in industrial macro-sectors and represented nationally by regions,relating their distribution to meteorological or geophysical data of interest.At the regional scale,the MHIs of the Piedmont Region were represented as punctual elements,associating the population within potential damage zones by province.At the municipal scale,a previously validated multi-hazard tool for vulnerability assessment was then tailored to a reduced scale for specific applications in an industrial context.This adaptation,which considers the two-way interaction between an energetic critical infrastructure and various hazards in its surroundings,delivers a spatial vulnerability profile that may complement the probabilistic analysis of industrial incidental scenarios.In summary,this framework may raise the stakeholders awareness at various levels and with different interests within the industrial accident control decision making chain,from operators to competent authorities.展开更多
A compound disaster rumor is a special type of rumor that involves multiple public safety events.Its pattern of spread is distinct from that of a general disaster rumor,which involves one public safety event.This work...A compound disaster rumor is a special type of rumor that involves multiple public safety events.Its pattern of spread is distinct from that of a general disaster rumor,which involves one public safety event.This work examines and verifies the amplification effect of the spread of compound disaster rumors(relative to general disaster rumors).A new rumor spread model based on infectious disease dynamics is proposed for compound disaster rumors involving two simultaneously occurring public safety events.The new model considers a special group of people,termed“double-hazard sensitive ignorants.”Taking this group as the initial crowd,it adds a new spread chain to existing rumor spread models.This modeling method successfully captures the amplification effect of the spread of compound disaster rumors involving two public safety events.A real case is selected for empirical analysis:the spread of a compound disaster rumor in a double-hazard scenario,consisting of an earthquake and the pandemic,in Sichuan,China in 2022.The results confirm that the spread of a pandemicrelated natural disaster compound rumor has a higher peak than that of a general disaster rumor.The new model is applied in this real scenario and captures the amplification effect of the spread of compound rumors.Our study sheds light on the spreading pattern of compound disaster rumors,thereby providing guidance and assistance for future disaster rumor management.展开更多
The details of a multi-hazard and probabilistic risk assessment, developed for urban planning and emergency response activities in Manizales, Colombia, are presented in this article. This risk assessment effort was de...The details of a multi-hazard and probabilistic risk assessment, developed for urban planning and emergency response activities in Manizales, Colombia, are presented in this article. This risk assessment effort was developed under the framework of an integral disaster risk management project whose goal was to connect risk reduction activities by using open access and state-of-theart risk models. A probabilistic approach was used for the analysis of seismic, landslide, and volcanic hazards to obtain stochastic event sets suitable for probabilistic loss estimation and to generate risk results in different metrics after aggregating in a rigorous way the losses associated to the different hazards. Detailed and high resolution exposure databases were used for the building stock and infrastructure of the city together with a set of vulnerability functions for each of the perils considered. The urban and territorial ordering plan of the city was updated for socioeconomic development and land use using the hazard and risk inputs and determinants, which cover not only the current urban area but also those adjacent areas where the expansion of Manizales is expected to occur. The emergency response capabilities of the city were improved by taking into account risk scenarios and after updating anautomatic and real-time post-earthquake damage assessment.展开更多
基金Dalian Municipal Natural Science Foundation under Grant No.2019RD01。
文摘Economic losses and catastrophic casualties may occur once super high-rise structures are struck by low-probability but high-consequence scenarios of concurrent earthquakes and winds. Therefore, accurately predicting multi-hazard dynamic responses to super high-rise structures has significant engineering and scientific value. This study performed a parametric global sensitivity analysis (GSA) for multi-hazard dynamic response prediction of super high-rise structures using the multiple-degree-of-freedom shear (MFS) model. Polynomial chaos Kriging (PCK) was introduced to build a surrogate model that allowed GSA to be combined with Sobol’ indices. Monte Carlo simulation (MCS) is also conducted for the comparison to verify the accuracy and efficiency of the PCK method. Parametric sensitivity analysis is performed for a wide range of aleatory uncertainty (intensities of coupled multi-hazard), epistemic uncertainty (bending stiffness, k_(m);shear stiffness, kq;density, ρ;and damping ratio, ξ), probability distribution types, and coefficients of variation. The results indicate that epistemic uncertainty parameters, k_(m), ρ, and ξ dramatically affect the multi-hazard dynamic responses of super high-rise structures;in addition, Sobol’ indices between the normal and lognormal distributions are insignificant, while the variation levels have remarkably influenced the sensitivity indices.
基金substantially supported by the National Natural Science Foundation of China(No.52130805,51978516,52022070,52108381)the National Key R&D Program(No.2021YFF0502200 and 2021YFB2600804)。
文摘Underground infrastructure(UI)plays a great important role in the urbanization and modernization of megacities in the world.However,the intensive development of the UI during the past decades has posed great risks to the safety of city infrastructures under the impact of multi-hazards,especially with the condition of global climate change.In this paper,a general conceptualized framework to assess the resilience of UI in cities under multihazards impact is proposed.The urban tunnel system,e.g.,metro tunnel,road tunnel etc.,is selected as the typical underground infrastructure discussed with the emphasis both on the structural level in terms of mechanical behaviors and system level in terms of network efficiency.The hazards discussed in this paper include the natural hazards and human-related ones,with emphasis on earthquake,flood,and aggressive disturbances caused by human activities.After the general framework proposed for resilience of the structural and network behavior of the UI,two application examples are illustrated.The structural resilience of the shield tunnel under earthquake impact is analyzed by using the proposed resilience model,and the network resilience of the road tunnel system under the flood impact due to climate change is analyzed,respectively.The resilience enhancement by using the adaptive design strategy of real-time observational method is mathematically presented in this case.Some other practical engineering recovery measures are briefly discussed at the end of this application example.The findings in the application examples should be helpful to enhance the resilience-based design of the structural and network of tunnels from the component to the system level.
基金supported by the Key Laboratory of Coastal Science and Integrated Management,Ministry of Natural Resources(No.2022COSIMQ002)the Shandong Provincial Social Science Planning Research Project(No.22CXSXJ15)+1 种基金the Guangxi Key Laboratory of Marine Environmental Science,Guangxi Academy of Sciences(No.GXKLHY21-04)the Hainan Province Marxism Project General Program(No.2023HNMGC03).
文摘Storm surge events(SSEs)involve multiple hazard-causing factors,such as surges,extreme rainfall,strong winds,waves,and ocean currents,which have destructive impacts on coastal regions.For a quantitative multi-hazard assessment of SSEs,this study introduced the concept of the storm surge event seawater-atmosphere system(SSE-SAS)and proposed the system energy equivalence(SEE)model from a systemic energy perspective.SEE was obtained by employing a parameterization approach,and the hazard index(HI)and the concept of most significant hazard(MSH)were adopted to evaluate the severity of SSE-SAS.SEE at five stations in the Shandong Peninsula was calculated from 2005 to 2019,and probability analysis and hazard assessment were further conducted.Results show that the SEE of SSE-SAS ranges from 0.029×10^(3) to 30.418×10^(3) J/m^(2),and it exhibits an insignificant decreasing trend from 2005 to 2019.The SEE of SSE-SAS in the west of the Shandong Peninsula is greater than that in the east.Moreover,storm waves,storm surges,and storm rainfall are the major contributors to SEE,which exhibit different spatial patterns and characters in different SSE-SAS types.The HI of SSE-SAS at five stations is no more than medium hazard level,with MSH at return periods of 2-to 4-year level.This study provides a new approach for quantifying multi-hazard SSEs,which offers scientific insights for regional multi-hazard risk reduction and mitigation efforts.
基金funding from the National Science Foundation(NSF Award 2114701)of the United States.
文摘This study advances the DRASTIC groundwater vulnerability assessment framework by integrating a multi-hazard groundwater index(MHGI)to account for the dynamic impacts of diverse anthropogenic activities and natural factors on both groundwater quality and quantity.Incorporating factors such as population growth,agricultural practices,and groundwater extraction enhances the framework’s ability to capture multi-dimensional,spatiotemporal changes in groundwater vulnerability.Additional improvements include refined weighting and rating scales for thematic layers based on available observational data,and the inclusion of distributed recharge.We demonstrate the practical utility of this dynamic DRASTIC-based framework through its application to the agro-urban regions of the Irrigated Indus Basin,a major groundwater-dependent agricultural area in South Asia.Results indicate that between 2005 and 2020,54%of the study area became highly vulnerable to pollution.The MHGI revealed a 13%decline in potential groundwater storage and a 25%increase in groundwater-stressed zones,driven primarily by population growth and intensive agriculture.Groundwater vulnerability based on both groundwater quality and quantity dimensions showed a 19%decline in areas of low to very low vulnerability and a 6%reduction in medium vulnerability zones by 2020.Sensitivity analyses indicated that groundwater vulnerability in the region is most influenced by groundwater recharge(42%)and renewable groundwater stress(38%).Validation with in-situ data yielded area under the curve values of 0.71 for groundwater quality vulnerability and 0.63 for MHGI.The framework provides valuable insights to guide sustainable groundwater management,safeguarding both environmental integrity and human well-being.
文摘Global climate change,climate extremes,and overuse of natural resources are all major contributors to the risk brought on by cyclones.In I West Bengal state of India,the Pathar Pratima Block frequently experiences a variety of risks that result in significant loss of life and livelihood.In order to govern coastal society,it is crucial to measure and map the multi-hazards risk status.To depict the multi-hazards vulnerability and risk status,no cutting-edge models are currently being applied.Predicting distinct physical vulnerabilities is possible using a variety of cutting-edge machine learning techniques.This study set out to precisely describe multi-hazard risk using powerful machine learning methods.This study involved the use of Analytic Hierarchical Analysis and two cutting-edge machine-learning algorithms-Random Forest and Artificial Neural Network,which are yet underutilized in this area.The multi-hazards risk was determined by taking into account six criteria.The southern and eastern regions of the research area are clearly identified by the multi-hazards risk maps as having high to extremely high hazards risk levels.Cyclonic hazards and embankment breaching are the main dominant factors among the multi-hazards.The machine learning approach is the most accurate model for mapping the multi-hazards risk where the ROC result of Random forest and artificial neural network is more than the conventional method AHP.Here RF is the most validated model than the other two.The effectiveness,root mean square error,true skill statistics,Friedman and Wilcoxon rank test,and area under the curve of receiver operating characteristic tests were used to evaluate the prediction capacity of newly constructed models.The RMSE values of 0.24 and 0.26,TSS values of 0.82 and 0.73,and AUC values of 88.20%and 89.10%as produced by RF and ANN models,respectively,were all excellent.
文摘With the implementation of significant national strategies and rapid socioeconomic development,many ultra-long deep tunnels are being constructed in the Qinghai–Xizang Plateau region.However,the extreme complexity and variability of the environment in this region pose significant challenges to the safe construction and long-term operation of the planned or under-construction ultra-long deep tunnels.To address these complex technical challenges,this paper provides a detailed analysis of the complex climate and geology features of the Qinghai–Xizang Plateau during tunnel construction.The climate characteristics of the Qinghai–Xizang Plateau include severe coldness,low oxygen,and unpredictable weather changes.The geological characteristics include complex stress distributions caused by the intense internal and external dynamic coupling of tectonic plates,widespread active tectonic structures,frequent high-intensity earthquakes,fractured rock masses,and numerous active fault zones.Based on the analysis,this paper elaborates on potential sources of major disasters resulting from the characteristics of ultra-long deep tunnel projects in the Qinghai–Xizang Plateau region.These potential disaster sources include the crossing of active fault zones,high geostress rockbursts,large deformation disasters,high-pressure water surges,geothermal hazards,inadequate long-distance ventilation and oxygen supply,and multi-hazard couplings.In response to these challenges,this paper systematically summarizes the latest research progress and technological achievements in the domestic and international literature,and proposes innovative ideas and future development prospects for disaster monitoring and early warning,mechanized intelligent construction,long-term safety services,and emergency security and rescue.These innovative measures are intended to address the challenges of tunnel disaster prevention and control in the complex environment of the Qinghai–Xizang Plateau,contributing to the safe construction and long-term operation of ultra-long deep tunnels in this region.
基金Federal Highway Administration at the University at Buffalo under Contract No.DTFH61-08-C-00012
文摘In the U.S., the current Load and Resistance Factor Design （LRFD） Specifications for highway bridges is a reliability-based formulation that considers failure probabilities of bridge components due to the actions of typical dead load and frequent vehicular loads. Various extreme load effects, such as earthquake and vessel collision, are on the same reliability-based platform. Since these extreme loads are time variables, combining them with not considered frequent. non- extreme loads is a significant challenge. The number of design limit state equations based on these failure probabilities can be unrealistically large and unnecessary from the view point of practical applications. Based on the opinion of AASHTO State Bridge Engineers, many load combinations are insignificant in their states. This paper describes the formulation of a criterion to include only the necessary load combinations to establish the design limit states. This criterion is established by examining the total failure probabilities for all possible time-invariant and time varying load combinations and breaking them down into partial terms. Then, important load combinations can be readily determined quantitatively,
基金supported by the Joint Funds of the National Natural Science Foundation of China(U21A2013)the State Key Laboratory of Biogeology and Environmental Geology,China University of Geosciences(GBL12107)the National Natural Science Foundation of China(61271408)。
文摘Multi-hazard susceptibility prediction is an important component of disasters risk management plan.An effective multi-hazard risk mitigation strategy includes assessing individual hazards as well as their interactions.However,with the rapid development of artificial intelligence technology,multi-hazard susceptibility prediction techniques based on machine learning has encountered a huge bottleneck.In order to effectively solve this problem,this study proposes a multi-hazard susceptibility mapping framework using the classical deep learning algorithm of Convolutional Neural Networks(CNN).First,we use historical flash flood,debris flow and landslide locations based on Google Earth images,extensive field surveys,topography,hydrology,and environmental data sets to train and validate the proposed CNN method.Next,the proposed CNN method is assessed in comparison to conventional logistic regression and k-nearest neighbor methods using several objective criteria,i.e.,coefficient of determination,overall accuracy,mean absolute error and the root mean square error.Experimental results show that the CNN method outperforms the conventional machine learning algorithms in predicting probability of flash floods,debris flows and landslides.Finally,the susceptibility maps of the three hazards based on CNN are combined to create a multi-hazard susceptibility map.It can be observed from the map that 62.43%of the study area are prone to hazards,while 37.57%of the study area are harmless.In hazard-prone areas,16.14%,4.94%and 30.66%of the study area are susceptible to flash floods,debris flows and landslides,respectively.In terms of concurrent hazards,0.28%,7.11%and 3.13%of the study area are susceptible to the joint occurrence of flash floods and debris flow,debris flow and landslides,and flash floods and landslides,respectively,whereas,0.18%of the study area is subject to all the three hazards.The results of this study can benefit engineers,disaster managers and local government officials involved in sustainable land management and disaster risk mitigation.
基金The study was supported by College of Agriculture,Shiraz University(Grant No.96GRD1M271143).
文摘Natural hazards are often studied in isolation.However,there is a great need to examine hazards holistically to better manage the complex of threats found in any region.Many regions of the world have complex hazard landscapes wherein risk from individual and/or multiple extreme events is omnipresent.Extensive parts of Iran experience a complex array of natural hazards-floods,earthquakes,landslides,forest fires,subsidence,and drought.The effectiveness of risk mitigation is in part a function of whether the complex of hazards can be collectively considered,visualized,and evaluated.This study develops and tests individual and collective multihazard risk maps for floods,landslides,and forest fires to visualize the spatial distribution of risk in Fars Province,southern Iran.To do this,two well-known machine-learning algorithms-SVM and MARS-are used to predict the distribution of these events.Past floods,landslides,and forest fires were surveyed and mapped.The locations of occurrence of these events(individually and collectively) were randomly separated into training(70%) and testing(30%) data sets.The conditioning factors(for floods,landslides,and forest fires) employed to model the risk distributions are aspect,elevation,drainage density,distance from faults,geology,LULC,profile curvature,annual mean rainfall,plan curvature,distance from man-made residential structures,distance from nearest river,distance from nearest road,slope gradient,soil types,mean annual temperature,and TWI.The outputs of the two models were assessed using receiver-operating-characteristic(ROC) curves,true-skill statistics(TSS),and the correlation and deviance values from each models for each hazard.The areas-under-the-curves(AUC) for the MARS model prediction were 76.0%,91.2%,and 90.1% for floods,landslides,and forest fires,respectively.Similarly,the AUCs for the SVM model were 75.5%,89.0%,and 91.5%.The TSS reveals that the MARS model was better able to predict landslide risk,but was less able to predict flood-risk patterns and forest-fire risk.Finally,the combination of flood,forest fire,and landslide risk maps yielded a multi-hazard susceptibility map for the province.The better predictive model indicated that 52.3% of the province was at-risk for at least one of these hazards.This multi-hazard map may yield valuable insight for land-use planning,sustainable development of infrastructure,and also integrated watershed management in Fars Province.
基金Financial Support from Hong Kong PolytechnicUniversity Under Grant No. G-YX76
文摘Many urban areas are located in regions of moderate seismicity and are subjected to strong wind. Buildings in these regions are often designed without seismic provisions. As a result, in the event of an earthquake, the potential for damage and loss of lives may not be known. In this paper, the performance of a typical high-rise building with a thick transfer plate （TP）, which is one type of building structure commonly found in Hong Kong, is assessed against both earthquake and wind hazards. Seismic- and wind-resistant performance objectives are first reviewed based on relevant codes and design guidelines for high-rise buildings. After a brief introduction of wind-resistant design of the building, various methodologies, including equivalent static load analysis （ESLA）, response spectrum analysis （RSA）, pushover analysis （POA）, linear and nonlinear time-history analysis （LTHA and NTHA）, are employed to assess the seismic performance of the building when subjected to frequent earthquakes, design based earthquakes and maximum credible earthquakes. The effects of design wind and seismic action with a common 50-year return period are also compared. The results indicate that most performance objectives can be satisfied by the building, but there are some objectives, such as inter-story drift ratio, that cannot be achieved when subjected to the frequent earthquakes. It is concluded that in addition to wind, seismic action may need to be explicitly considered in the design of buildings in regions of moderate seismicity.
文摘Yogyakarta is one of the large cities in Central Java,located on Java Island,Indonesia.The city,and the Pleret sub-district,where the study has taken place,is prone to earthquake hazards,because it is close to several seismically active zones,such as the Sunda Megathrust and the active fault known as the Opak Fault.Since a devastating earthquake of 2006,the population of the Pleret sub-district has increased significantly.Thus,the housing demand has increased,and so is the pace of low-cost housing that does not meet earthquake-safety requirements,and furthermore are often located on unstable slopes.The local alluvial material covering a jigsaw of unstable blocks and complex slope is conditions that can amplify the negative impacts of earthquakes.Within this context,this study is aiming to assess the multi-hazards and risks of earthquakes and related secondary hazards such as ground liquefaction,and coseismic landslides.To achieve this,we used geographic information systems and remote sensing methods supplemented with outcrop study and existing seismic data to derive shear-strain parameters.The results have revealed the presence of numerous uncharted active faults with movements visible from imagery and outcrops.show that the middle part of the study area has a complex geological structure,indicated by many unchartered faults in the outcrops.Using this newly mapped blocks combined with shear strain data,we reassessed the collapse probability of buildings that reach level>0.75 near the Opak River,in central Pleret sub-district.Classifying the buildings and from population distribution,we could determine that the highest risk was during nighttime as the buildings susceptible to fall are predominantly housing buildings.The secondary hazards follow a slightly different distribution with a concentration of risks in the West.
文摘Digital elevation models(DEMs)are essential tools in environmental science,particularly for hazard assessments and landscape analyses.However,their application acrossmultiple environmental hazards simultaneously remains in need for a multi-aspect critical assessment to promote their effectiveness in comprehensive risk management.This paper aims to review and critically assess the application of DEMs in mapping and managing specific environmental hazards,namely floods,landslides,and coastal erosion.In this regard,it seeks to promote their utility of hazard maps as key tools in disaster risk reduction and environmental planning by employing high-resolution DEMs integrated with advanced geographic information systems.The findings offer valuable insights into optimizing DEM technology for environmental management,contributing to safer and more resilient communities.The paper addresses an important gap in the geospatial analysis of natural hazards and serves as a foundational reference for future advancements in the field,emphasizing its importance to academic researchers and practical stakeholders in environmental and disaster management.
基金funded through a cooperative agreement between the U.S.National Institute of Standards and Technology and Colorado State University(NIST Financial Assistance Award Numbers:70NANB15H044 and 70NANB20H008).
文摘This study introduces an advanced community-level resilience analysis methodology integrating 3D fragility sur-faces for combined successive earthquake-tsunami hazard and analysis.The methodology facilitates comprehen-sive evaluations of spatial damage,economic loss,and risk under multi-hazard conditions.This study compares earthquake-only analysis results to the successive earthquake-tsunami analysis at the community level to reveal-and quantify-significant disparities in damage and loss estimations between the analyses,emphasizing the need to consider both hazards in community planning even at lower seismic intensities.Critical assessment of the FEMA combinational rule demonstrates its limitations in accurately predicting losses and damage patterns at higher hazard intensities,highlighting the necessity for refined models that accurately account for hazard inter-actions.This research advances multi-hazard community-level resilience analysis by offering a robust framework for earthquake and tsunami assessment,underscoring the need for integration of detailed multi-hazard analy-ses into resilience planning.Finally,it suggests future directions for enhancing framework applicability across diverse community settings and structural types,aiming to improve community resilience.
基金Federal Highway Administration at the University at Buffalo under Contract No. DTFH61-08-C-00012
文摘In many regions of the world, a bridge will experience multiple extreme hazards during its expected service life. The current American Association of State Highway and Transportation Officials （AASHTO） load and resistance factor design （LRFD） specifications are formulated based on failure probabilities, which are fully calibrated for dead load and nonextreme live loads. Design against earthquake loads is established separately. Design against scour effect is also formulated separately by using the concept of capacity reduction （or increased scour depth）. Furthermore, scour effect cannot be linked directly to an LRFD limit state equation, because the latter is formulated using force-based analysis. This paper （in two parts） presents a probability-based procedure to estimate the combined hazard effects on bridges due to truck, earthquake and scour, by treating the effect of scour as an equivalent load effect so that it can be included in reliability-based bridge failure calculations. In Part I of this series, the general principle of treating the scour depth as an equivalent load effect is presented. The individual and combined partial failure probabilities due to truck, earthquake and scour effects are described. To explain the method of including non-force-based natural hazards effects, two types of common scour failures are considered. In Part 11, the corresponding bridge failure probability, the occurrence of scour as well as simultaneously having both truck load and equivalent scour load are quantitatively discussed.
基金Federal Highway Administration at the University at Buffalo under Contract Number DTFH61-08-C-00012
文摘In many regions of the world, a bridge will experience multiple extreme hazards during its expected service life. The current American Association of State Highway and Transportation Officials （AASHTO） load and resistance factor design （LRFD） specifications are formulated based on failure probabilities, which are fully calibrated for dead load and non-extreme live loads. Design against earthquake load effect is established separately. Design against scour effect is also formulated separately by using the concept of capacity reduction （or increased scour depth）. Furthermore, scour effect cannot be linked directly to an LRFD limit state equation because the latter is formulated using force-based analysis. This paper （in two parts） presents a probability-based procedure to estimate the combined hazard effects on bridges due to truck, earthquake and scour, by treating the effect of scour as an equivalent load effect so that it can be included in reliability-based failure calculations. In Part I of this series, the general principle for treating the scour depth as an equivalent load effect is presented. In Part II, the corresponding bridge failure probability, the occurrence of scour as well as simultaneously having both truck load and equivalent scour load effect are quantitatively discussed. The key formulae of the conditional partial failure probabilities and the necessary conditions are established. In order to illustrate the methodology, an example of dead, truck, earthquake and scour effects on a simple bridge pile foundation is represented.
文摘The increasing frequency and intensity of natural disasters necessitate advanced prediction techniques to mitigate potential damage.This study presents a comprehensive multi-hazard early warning framework by integrating the multi-source data fusion technique.A multi-source data extraction method was introduced by extracting pressure level and average precipitation data based on the hazard event from the Cooperative Open Online Landslide Repository(COOLR)dataset across multiple temporal intervals(12 h to 1 h prior to events).Feature engineering was performed using Choquet fuzzy integral-based importance scoring,which enables the model to account for interactions and uncertainty across multiple features.Three individual Long Short-Term Memory(LSTM)models were trained for hazard location,average precipitation,and hazard category(i.e.,to detect the potential of natural disasters).These models were trained on varying temporal scales from 12 to 1 h prior to the event.These individual models achieved the performance of Mean Absolute Error(MAE)2.2 and 3.2,respectively,for the hazard location and average precipitation models,and an F1-score of 0.825 for the hazard category model.The results also indicate that the LSTM model outperformed traditional Machine Learning(ML)models,and the use of the fuzzy integral enhanced the prediction capability by 8.12%,2.6%,and 6.37%,respectively,for all three individual models.Furthermore,a rule-based algorithm was developed to synthesize the outputs from the individual models into a 3×3 grid of multi-hazard warnings.These findings underscore the effectiveness of the proposed framework in advancing multi-hazard forecasting and situational awareness,offering valuable support for timely and data-driven emergency response planning.
基金supported by Fundacao para a Ciencia e Tecnologia,PhD grant no.SFRH/BD/137531/2018,ongoing at Lisbon University,Instituto Superior Tecnico,Civil Engineering Research and Innovation for Sustainability(CERIS)Lopes and Reis are grateful for the Foundation for Science and Technology’s support through funding UIDB/04625/2020 from the research unit CERIS+1 种基金finantial support by FEDER-Fundo Europeu de Desenvolvimento Regional,through COMPETE 2020-Programa Operacional Fatores de Competitividadethe National Funds through FCT-Fundacao para a Ciencia e Tecnologia,projects no.UID/FIS/04650/2019 and no.POCI-01-0145-FEDER-028118.
文摘The spatial distribution of the world population is uneven,with a density of about 40%living in coastal regions.The trend is expected to continue in both demographic indicators and urban development rate,being many coastal cities in seismic-and tsunami-prone regions and built through informal and unplanned settlements,exposing their population and assets to such hazards.Recent tectonic-triggered events raised awareness of the cascading earthquake and tsunami threat and highlighted the paucity of structural design criteria considering the cumulative effects of both.By being exposed to the ground-motion,the structures’resistance may decrease and become residual/non-existent to support the incoming tsunami,implying an underestimation of the risk.Risk management can benefit from reinforcing the ties between natural hazards and engineering practitioners,linking science and industry,and promoting dialogue between risk analysts and policy-makers.Motivated by the expansion plans of an internationally-sized deep-water port located in a tsunami-prone region,a reflection on the work needed to perform a multi-risk assessment and the challenges yet to overcome is introduced to emphasize the challenge of combining safety requirements with financial and ecologic concerns.A conceptual interdisciplinarybased methodology is proposed to support uncertainty-aware,systematic and informed decisions.
文摘Directive 2022/2557 from the European Commission aims to enhance the resilience of critical entities in Europe by integrating with existing European legislation,but it lacks explicit guidance on addressing vulnerabilities.Specifially,major hazard industries(MHls)are critical infrastructures that face unique risks arising from the interactions of natural and technological hazards(NaTech events);nevertheless,existing policies frequently overlook the potential vulnerabilities of process plants to these complex phenomena.The goal of this research was to systematically characterize the vulnerability of industrial critical infrastructures(ICIs)to various hazards in their territories.A multi-scale procedure was implemented in the Italian context as a case study,where spatial analyses were developed using open data.Starting from the Italian national inventory,the MHIs were clustered in industrial macro-sectors and represented nationally by regions,relating their distribution to meteorological or geophysical data of interest.At the regional scale,the MHIs of the Piedmont Region were represented as punctual elements,associating the population within potential damage zones by province.At the municipal scale,a previously validated multi-hazard tool for vulnerability assessment was then tailored to a reduced scale for specific applications in an industrial context.This adaptation,which considers the two-way interaction between an energetic critical infrastructure and various hazards in its surroundings,delivers a spatial vulnerability profile that may complement the probabilistic analysis of industrial incidental scenarios.In summary,this framework may raise the stakeholders awareness at various levels and with different interests within the industrial accident control decision making chain,from operators to competent authorities.
基金supported by National Natural Science Foundation of China(72034004)National Science Fund for Distinguished Young Scholars of China(71725006).
文摘A compound disaster rumor is a special type of rumor that involves multiple public safety events.Its pattern of spread is distinct from that of a general disaster rumor,which involves one public safety event.This work examines and verifies the amplification effect of the spread of compound disaster rumors(relative to general disaster rumors).A new rumor spread model based on infectious disease dynamics is proposed for compound disaster rumors involving two simultaneously occurring public safety events.The new model considers a special group of people,termed“double-hazard sensitive ignorants.”Taking this group as the initial crowd,it adds a new spread chain to existing rumor spread models.This modeling method successfully captures the amplification effect of the spread of compound disaster rumors involving two public safety events.A real case is selected for empirical analysis:the spread of a compound disaster rumor in a double-hazard scenario,consisting of an earthquake and the pandemic,in Sichuan,China in 2022.The results confirm that the spread of a pandemicrelated natural disaster compound rumor has a higher peak than that of a general disaster rumor.The new model is applied in this real scenario and captures the amplification effect of the spread of compound rumors.Our study sheds light on the spreading pattern of compound disaster rumors,thereby providing guidance and assistance for future disaster rumor management.
文摘The details of a multi-hazard and probabilistic risk assessment, developed for urban planning and emergency response activities in Manizales, Colombia, are presented in this article. This risk assessment effort was developed under the framework of an integral disaster risk management project whose goal was to connect risk reduction activities by using open access and state-of-theart risk models. A probabilistic approach was used for the analysis of seismic, landslide, and volcanic hazards to obtain stochastic event sets suitable for probabilistic loss estimation and to generate risk results in different metrics after aggregating in a rigorous way the losses associated to the different hazards. Detailed and high resolution exposure databases were used for the building stock and infrastructure of the city together with a set of vulnerability functions for each of the perils considered. The urban and territorial ordering plan of the city was updated for socioeconomic development and land use using the hazard and risk inputs and determinants, which cover not only the current urban area but also those adjacent areas where the expansion of Manizales is expected to occur. The emergency response capabilities of the city were improved by taking into account risk scenarios and after updating anautomatic and real-time post-earthquake damage assessment.
