Deep learning models are widely used for urban flood prediction, but current research lacks a clear explanation of how indicator weight changes affect model accuracy. This study incorporated the attention mechanism between the convolutional and fully connected layers of the convolutional neural network (CNN) to enable the model to focus on critical flood-inducing factors, and employed the particle swarm optimization (PSO) to optimize the key hyperparameters (for example, the number of filters and learning rate). Furthermore, we employed Shapley additive explanation (SHAP) to analyze how flood-inducing indicator weight changes affect prediction accuracy. The model was tested on Haidian Island, China. The Nash-Sutcliffe efficiency (NSE) coefficient of the CNN model is 0.9287. After incorporating the attention mechanism into the CNN and optimizing the hyperparameters using PSO, the NSE is improved to 0.9503. The model demonstrates higher accuracy in predicting larger inundations, with the NSE for the 100-year return-period flood reaching 0.9535, compared to 0.8341 for the 5-year return period. Interpretability analysis shows that elevation is the most important flood-inducing factor, accounting for 44% of the total importance, followed by tidal levels, which account for 33%. The attention mechanism increases the weights of important flood-inducing factors (for example, elevation, tide level); after hyperparameter optimization, the model achieves more comprehensive learning, increasing the weights of the rainfall indicators that are neglected by the unoptimized model, and these weight changes improve the accuracy of the model. The research revealed the impacts of different flood-inducing factors on flooding and the influence of indicator weight changes on model accuracy.

Climate change has intensified extreme rainfall events, challenging progress toward SDG 11's urban resilience targets. Current assessment methods often neglect dynamic recovery processes and regional precipitation disparities. We propose a three-phase framework combining interpretable machine learning (ML) and factorial experiments, using the Prep_shock index that integrates standardized rainfall intensity, capital exposure, and historical probability, to evaluate the dynamic resilience of 220+ Chinese cities from 2019 to 2022. Key findings reveal that: (1) The Prep_shock index effectively eliminates north-south precipitation biases, identifying Shandong coastal cities and Yangtze River Delta city clusters (36.2%) as high-resilience areas, in contrast to Henan Province. COVID-19 exacerbated systemic risks in megacities, undermining their capital protection capacities. (2) Spatial diagnostics classify 75.6% of the cities into Quadrant III (the balanced resilience category), with recovery times decreasing from the west to the east. Super-large cities like Zhengzhou (2021) exhibited critical recovery deficiencies (Quadrant IV). (3) Interpretable ML models (XGBoost/EBM) identify redundancy as the dominant resilience driver—robustness governs baseline resilience, while recovery relies on emergency support (for example, hospital beds density and fiscal inputs) and redundant infrastructure (for example, road network density). (4) Factorial experiments reveal optimization trade-offs: simultaneous enhancement of rapidity and redundancy diminishes their individual benefits, necessitating context-specific prioritization. The study advances dynamic resilience assessment methods and proposes quadrant-specific strategies for tailored urban adaptation.

Rural settlements have experienced a noticeable increase in extreme weather events and associated disasters in recent years. Pakistan is consistently ranked as one of the most affected regions globally, and the catastrophic floods of 2022 further underscored its vulnerability to floods, causing unprecedented human, economic, and environmental losses. This study conducted a multidimensional vulnerability assessment of flood-prone rural areas in Dera Ismail Khan, Pakistan, using a composite index approach informed by principal component analysis (PCA). Principal component analysis was employed to assign statistically robust weights to selected indicators, ensuring an objective aggregation of vulnerability components. A questionnaire with a mix of closed-ended and open-ended items was used to collect data through a household survey. The findings revealed that a substantial proportion (40%) of respondents experienced high multidimensional vulnerability, while approximately 30% exhibited moderate vulnerability. Factors such as age distribution, household income, infrastructure quality, and risk perception significantly contributed to overall vulnerability. This study developed a scalable and replicable model for assessing rural flood vulnerability, offering practical insights for policymakers, planners, and disaster management authorities.

In 2022, the United Nations launched the “Early Warnings for All” (EW4All) initiative, which aims to ensure that early warning systems are available to all inhabitants of the world by 2027. It is a response to the fact that climate-related disasters are increasing and many countries still do not have effective systems in place. For EW4All, the World Meteorological Organization (WMO) has selected 30 countries whose meteorological and hydrological services will be supported to strengthen their monitoring capacities for recurrent climate-related hazards in their country. This work aims to assess the impact of disasters in the period from January 2000 to November 2024 for the 30 EW4All countries using a composite scale representing a combination of different impact indicators. The unique feature of this work is that the different societal impacts are summarized in a single index. In this way, a comparative assessment of impacts between countries can be made, which can serve as a basis for action beyond that undertaken by the WMO and purely academic interest. This is a tool that can help decision makers to implement risk management measures. For this study, we selected the Emergency Events Database (EM-DAT) from the available global datasets because it is the only dataset with a time series long enough to fulfill the statistical criteria of this study and also uses a common disaster recording protocol for all countries.

This study critically interrogates dominant models of post-disaster recovery by combining an interdisciplinary review of critical scholarship with grounded empirical analysis from Brazil. It focuses on landless and unhoused populations, as well as residents of informal settlements, to explore how disaster recovery frameworks, rather than reducing vulnerability, often reproduce spatial inequality and deepen exclusion. The research draws on a multi-site, multi-temporal mixed-methods study conducted in collaboration with the Movimento dos Atingidos por Barragens (MAB), analyzing Brazil's most severe recent climate-related disasters: landslides and floods in Petrópolis (2011, 2022, 2024) and São Sebastião (2023). Fieldwork involved participant observation, over 200 semistructured interviews with affected residents and officials, and 110 completed questionnaires. Findings reveal that Brazil's disaster governance framework embeds exclusionary dynamics, privileging legally recognized property owners while marginalizing those without formal tenure. Recovery programs often simplify complex social realities through rigid eligibility criteria, thereby silencing diverse lived experiences. As a result, recovery often becomes a prolonged, secondary disaster for the most vulnerable. The article argues that prevailing recovery models, anchored in technocratic management and depoliticized resilience discourse, fail to address the structural roots of marginalization. By centering the role of grassroots movements such as MAB, this article highlights how collective action can expose recovery injustices and foster more inclusive, participatory, and transformative approaches to disaster governance.

Road networks are a critical infrastructure system for the sustainable functioning of cities. However, they are frequently disrupted by urban flooding, leading to increased travel times and hindering emergency responses. This study proposed a novel dynamic flood-response simulation framework for urban transportation to evaluate the impacts of rainstorms and flooding on traffic systems, focusing on coupling the Integrated Hydrology and Hydrodynamics Urban Flood Model (IHUM) and the Simulation of Urban MObility (SUMO) model. The results obtained from Xiaoguwei Island, Guangzhou City, indicate that a 2-h rainstorm of a 2-year return period can affect traffic for over 4.5 h. During a 100-year return period rainstorm, average travel speed declines by 54%, while the emergency response time, for example, for police services, increases from 4.83 to 14.52 min. These findings highlight the significant impacts of flooding on urban traffic networks, assisting local authorities and stakeholders to proactively identify vulnerable network segments and prioritize targeted interventions for enhancing transportation system resilience to floods.

Extreme disaster events, particularly floods, impact individuals, households, and communities differently depending on a range of factors. Some residents are more vulnerable than others to floods, hence urgent action is needed to improve preparedness of vulnerable groups to reduce potential impacts of flooding. To achieve this, it is important to assess household flood preparedness, and identify the influence of household-level attributes on flood preparedness. Using a large-scale community survey, this study investigated how key household attributes such as evacuation assistance, Internet access, and key motivational factors and sources of motivation such as personal and social networks influence flood preparedness among vulnerable households. Households were categorized into three levels of vulnerability (high, medium, and low) by combining household economic capacity, as measured by household monthly expenditure, and the presence of vulnerable family members. Six key findings emerged: (1) Highly vulnerable households showed higher resilience to floods, and flood preparedness levels are independent of household vulnerability levels; (2) Self-reported household flood preparedness is positively influenced by learning from past disaster experience; (3) Financial and time commitments, and a sense of urgency for household-level flood preparedness are key intrinsic motivational factors that influence flood preparedness; (4) Access to reliable Internet can be used as a proxy to predict the degree of household flood preparedness; (5) Higher levels of awareness and knowledge of flood preparedness were reported despite low levels of community consultation; and (6) Self-motivation is the key source of motivation for flood preparedness. The study findings will support key institutional stakeholders such as local governments to devise strategies to strengthen the flood resilience of vulnerable households and communities.

Identifying the optimal intensity measures (IMs) of ground motion is a critical step in the seismic fragility analysis of slopes using probabilistic seismic demand models. In this study, we investigated various IMs of earthquake ground motions, considering both vertical and horizontal components that can trigger landslides, through numerical simulations. A set of 19 IMs was examined for three heights of slopes. The optimal IMs were assessed using the maximum permanent displacement as an engineering demand parameter. The findings reveal that acceleration-related parameters specifically sustained maximum acceleration (SMA) and root-mean-square of acceleration, and velocity-related parameters namely sustained maximum velocity (SMV) and peak ground velocity, are the most effective IMs for slopes subjected to both vertical and horizontal ground motions. For slopes subjected exclusively to horizontal ground motion, SMA is recommended as the optimal IM for lower-height slopes, while SMV is more suitable for the taller slope. In contrast, for models subjected to combined horizontal and vertical ground motions, SMA is consistently identified as the optimal IM for slope across all heights. Notably, the study concludes that peak ground acceleration, a commonly used parameter in seismic analysis, is unsuitable for the considered slopes.

This study examined public support for disaster-related measures (risk awareness, memory transmission, prevention facilities, and information networks) in the long-term recovery phase of a disaster-affected municipality. Focusing on Rikuzentakata City, which was severely impacted by the 2011 Great East Japan Earthquake and Tsunami, a stated-preference survey was conducted and analyzed using discrete choice models. Three research questions were addressed: RQ1 on the main effects of disaster-related measures, RQ2 on the interaction effects among these measures, and RQ3 on the interaction effects between disaster-related measures and economic-livelihood measures (ELMs). Stand-alone disaster-related measures and their within-domain combinations reduced public support, indicating dilution effects. By contrast, support increased when they were integrated with complementary ELMs. The policy implications are threefold. First, disaster-related measures should be implemented with caution in the medium- to long-term recovery process, as pursuing them alone may generate dilution effects. Second, integrated policy packages that combine disaster-related measures with complementary ELMs should be prioritized. Third, shrinking-city municipalities can better overcome fiscal and human resource constraints and enhance sustainability by leveraging complementarities across policy domains. Overall, the findings provide quantitative evidence that disaster-related policy must be reconceptualized as part of a broader policy portfolio. This insight has broader relevance for hazard-prone regions worldwide and offers international implications for long-term disaster governance in line with the Sendai Framework, the Sustainable Development Goals, and the Paris Agreement.

The intensification of extreme rainfall events, driven by climate change, has exacerbated hydrological hazards in Brazil, affecting millions of people. This study investigated how previous disaster experience influences individuals' self-preparedness and key elements of community resilience, following the model by Norris et al. (2008), which includes information, social capital, community competence, and economic resources. A total of 1064 responses to a structured questionnaire survey was analyzed using the χ² test to identify statistical associations between behavioral variables and disaster experience. The results show that individuals with prior disaster experience report higher levels of perceived individual preparedness, concern about the impacts of heavy rainfall, and greater sensitivity to climate change. However, direct experience did not translate into greater confidence in institutional measures or stronger perceptions of community preparedness, revealing weaknesses in information flows and social cohesion. All interpretations are presented strictly in relation to the sample and do not imply population-level generalization. The study reinforces the relevance of experiential learning in shaping risk perception and preparedness, while highlighting contextual constraints associated with Brazil's socio-spatial inequalities and uneven governance capacities. These findings underscore the need for policies that strengthen institutional credibility, participatory risk communication, and community-level preparedness structures. The findings contribute to advancing risk management strategies in vulnerable contexts.

Building structure characteristics are essential for seismic risk assessment and management. However, accurately classifying building structural types at the city scale remains challenging due to limited data availability, spatial heterogeneity, and the difficulty in capturing contextual dependencies. In this study, a novel graph neural network (GNN)-based framework, BSPGNN (Building Structural Type Prediction using Graph Neural Networks), was proposed, integrating spatial relationships and building geometric features to improve structural type classification. A Delaunay triangulation (DT) graph was constructed from building footprint centroids to represent spatial proximity, and node features included footprint area, height, and construction year. Experiments using a real-world building dataset from Tianjin, China demonstrated that BSPGNN significantly outperformed traditional machine learning models, such as random forest (RF) and support vector machine (SVM), particularly in capturing spatially coherent patterns. The proposed model achieved a classification accuracy of 90.25% and 85.51% on the training set and validation set respectively, showing robust performance under missing data conditions. The results highlight the potential of spatial graph-based models in advancing building structural type classification for seismic risk assessment and management.

Previous studies have found that the higher the level of quality of life (QoL) or well-being is, the more desirable behavior people may take, including disaster preparedness actions. However, other variables like socio-demographics and risk perception might have varying effects on both of them. Therefore, comparisons between socio-demographic groups might be of help to disentangle this complex mechanism, but no studies have investigated their relationships. This study revisited surveys in Taiwan, China and Kinki, Japan and took a simple QoL measurement as an indicator of well-being. Multi-group analysis provided the analysis of the relationships between QoL, trust in government, disaster experience (EX), disaster risk perception (RP), and preparedness behavior (PB) for each dataset and for each grouping, here, by gender and by marital status. As a result, among others, the effect of QoL on PB was only significant in the female group in Taiwan, while RP and EX differently affected PB in different gender groups in Kinki. Moreover, no significant differences were found between the marital status groups in the associations between QoL, RP, and PB in Taiwan. These results imply the importance of group-specific approaches in intervention measures. Considering and addressing the limitations of this study, such as a cross-sectional design and the omission of potential variables, future studies may further explore the associations in different groups or with new variables such as self-efficacy.

The public's attribution of responsibility during a crisis is a central process in crisis communication, often explained by the situational crisis communication theory (SCCT). However, SCCT was developed in a pre-social media era, and its applicability in the new ecosystem of algorithm-driven, short-video platforms remains a critical theoretical gap. This study investigated how the core mechanisms of public responsibility attribution are reconfigured in the unique context of China's leading short-video platform, Douyin. Analyzing 185,148 comments following the tragic Yingcai School fire, our large language model (LLM)-based analysis answered two questions: (1) How are public attributions of responsibility structured in this emotionally charged, algorithmic environment? and (2) How do offline socioeconomic factors shape these digital crisis discourses? Our findings reveal two distinct attribution pathways, namely an anger-accountability track and a sadness-reflection track and demonstrate that critical discourse is systematically linked to regional development. This research provides a crucial empirical validation of SCCT for the short-video era and offers a data-driven guide for context-aware public administration.

Inefficient and ineffective fire management practices are common to most urban areas of developing countries.Nigerian cities are typical examples of high vulnerability and low preparedness level for fire disaster.This study examined the institutional framework for fire disaster risk reduction(FDRR) and explored the roles of key actors in fire disaster preparedness in Ibadan,a large traditional city in Nigeria.The study was anchored on the concept of urban governance.A case study research design was adopted using primary and secondary data.Primary data were obtained through field observation aided by a structured checklist and key informant interview.Interviews were conducted on key officials of the major organs for FDRR-Oyo State Fire Service(OSFS) and Oyo State Emergency Management Agency(OYSEMA).The study identified a disjointed and fragmented approach to fire management.Matters relating to fire risk reduction and disaster recovery were domiciled under the OYSEMA,while emergency response to fire disasters was the prerogative of the OSFS.The results show that only five out of 11 local government areas had public fire stations;only three fire stations had an on-site water supply;three fire stations lacked firefighting vehicles;and distribution of fire stations and facilities was uneven.Two fire stations responded to 80% of all fire cases in 12 years.The study concluded that the institutional structure and resources for fire risk reduction was more empowered to respond to fire disaster,rather than facilitating preparedness capacity to reduce disaster risk.

In many low-income countries, migrant remittances are essential in sustaining people's livelihoods and become even more important during and after disasters.Researchers, policymakers, and practitioners increasingly emphasize the need to better support this people-based mechanism, so disaster risk can be reduced. This suggests the importance of understanding migrants' perspectives on the remittance channels used and the challenges and opportunities of supporting remittances. However, such information is largely missing. Drawing on interviews and a focus group discussion carried out with Pacific Island migrants living in New Zealand, the article identifies the capacity of migrants to utilize different remittance channels and resources to assist those affected in their country of origin. Challenges faced include high transfer fees, lack of information and support from external stakeholders, and limited resources to effectively send both individual and collective remittances. The article concludes that there is a serious need to involve a large array of stakeholders in finding ways to better support remittances for disaster risk management, including migrants, government agencies, the private sector, nongovernmental organizations, and those receiving remittances.

<正>1 Introduction The Sendai Framework for Disaster Risk Reduction 2015–2030 shifts the focus from managing disasters to reducing risks.Such a shift requires a better understanding of risk in all its dimensions of environment,hazards,exposure,and vulnerability;a disaster risk governance that ensures

Relocation is not typically considered the best planning option for post-disaster reconstruction and rehabilitation,but it may be necessary if the site has suffered severe damage or is at imminent risk.There is a growing recognition that strong community participation is necessary in the post-disaster relocation decision-making process since relocation can have detrimental effects on a community's livelihood,cultural system,and way of life,among others.However,the realization of this still needs to be improved.As of yet,few studies have examined a comprehensive account of meaningful community engagement in post-disaster relocation and reconstruction,particularly in developing countries.This study investigated what factors influenced local communities' participation in post-disaster relocation and reconstruction works after the 2017Cyclone Dineo flood disaster in the Tsholotsho District of Zimbabwe.Qualitative research methods such as face-to-face interviews,observations,and focus groups were used to collect qualitative data from a purposive sample of 25 community members and 6 stakeholders.This empirical investigation showed that despite the fact that the relocation project was conceived as a community-centered project,there was no meaningful community engagement,due to the absence of a participatory framework or planning guidelines for stakeholder engagement,as well as the lack of political willingness among government officials.The study concluded that the lack of community involvement led to local communities abandoning the reconstruction sites because relocation projects failed to accommodate the cultural beliefs,place attachments,and livelihood concerns of local communities.This study suggested that it is imperative to enhance the awareness of government officials and other stakeholders about the importance of community participation for the effective implementation of post-disaster relocation works.Meaningful community participation can also provide avenues for incorporating local needs and concerns,cultural beliefs,and alternative and sustainable livelihood restoration,which are essential for effective reconstruction after disasters.This research aimed to enrich the academic discourse by providing valuable insights into the intricacies of postdisaster recovery initiatives in the country.

The importance of workplace safety in the ready-made garment(RMG) industry in Bangladesh came to the forefront after a series of disastrous events in recent years. In order to reduce the loss of lives and to ensure sustainable development, an in-depth understanding of the determining factors governing structural vulnerability in the RMG industry is needed. This research explores the key factors influencing the vulnerability of factory buildings under both vertical and earthquake loads. For this purpose,an ordered probit model was applied to 3746 RMG factory buildings to determine the key factors that influenced their vertical load vulnerability. A smaller subset of the original sample, 478 buildings, was examined by the same modeling method in greater detail to assess the key factors that influenced their earthquake load vulnerability. This research reveals that column capacity, structural system,and construction materials are the most influential factors for both types of vulnerabilities. Among other factors, soil liquefaction and irregular internal frame affect earthquake load vulnerability significantly. These findings are expected to enable factory owners and designers to better weigh the appropriate vulnerability factors in order to make informed decision that increase workplace safety. Theresearch findings will also help the designated authorities to conduct successful inspections of factory buildings and take actions that reduce vulnerability to both vertical and earthquake loads.

The third UN World Congress on Disaster Risk Reduction, held in Sendai, Japan in March 2015, agreed on a new framework to guide disaster risk reduction policy and practice for the next 15 years. The Sendai Framework for Disaster Risk Reduction 2015–2030(SFDRR) leaves important implementation issues unspecified and potentially creates both problems and opportunities for complex,multilevel governance systems in coping with hazards and disastrous events. Early warning systems(EWS), if built into the mainstream of planning for development and disaster relief and recovery, could present a significant opportunity to realize many SFDRR goals. We explore the complexities of using hydrometeorological EWS to prepare for drought and flood disasters in the densely populated communities of Pakistan's Indus River Basin in contrast to the African Sahel's less densely settled grasslands. Multilevel governance systems are often dominated by a topdown, technocentric, centralized management bias and have great difficulty responding to the needs of peripheral and vulnerable populations. People-centered, bottom-up approaches that incorporate disaggregated communities with local knowledge into a balanced, multilevel disaster risk management and governance structure have adramatically better chance of realizing the SFDRR goals for disaster risk reduction.

This article addresses three large earthquake disasters in Iran: Tabas in 1978, Rudbar in 1990, and Bam in 2003. Lessons and "Lessons Learned" from these three earthquake disasters were investigated together with their contributions over time towards earthquake disaster risk reduction in Iran. Many lessons from 1978 Tabas, 1990 Rudbar, and 2003 Bam did not become "Lessons Learned" and they were identified again within the dramatic context of other earthquake disasters in various places of Iran. Both lessons and "Lessons Learned" from Tabas, Rudbar, Bam,and other earthquake disasters in Iran require a sustainable long-term framework—an earthquake culture.

Tropical cyclones(TCs) may cause severe impacts on the activities of coastal fishing vessels. Due to the unavailability or unacceptability of detailed Automatic Identification System(AIS) data that are capable of differentiating fishing activity from navigation, as well as the lack of detailed models and observation data of TC winds, few studies have provided quantitative and reliable assessment of the impacts of TCs on fishing activities. In this study,we modeled snapshots for the TC winds of 52 TCs over the Northwest Pacific(NWP) basin from 2013 to 2018, as well as daily fishing hours and daily hours of presence(hereafter “vessel hours”) of fishing vessels. Based on these data, the spatiotemporal pattern of fishing vessel activity over off-shore China was first analyzed and mapped. Then, a TC wind hazard index and absolute and relative impact indices were proposed to assess the impact of the 52 TCs on fishing and vessel hours. Their relationship was then fitted with the cumulative distribution function(CDF) of the log-normal distribution. The results show that in the 2013-2018 period,the most active fishing areas were located in the South China Sea. In each instance, an increase was first observed in the initial several years; then a decrease followed in the yearly total fishing hours per vessel in the remaining years. The relative impact index was significantly correlated to the TC wind hazard index proposed in this study. Based on the quantitative relationship between the specified TC hazard index and the impact indices, it is possible to implement a pre-cyclone rapid loss assessment due to TC avoidance in the future.

The presence of high indoor radon concentrations, C_x, is a major concern of the public worldwide.Measurements of indoor radon in South Lebanon have been achieved using CR-39 detectors. Cxvalues ranged between 30 and 122 Bq m~(-3) in one of the major towns in the area and are compared with measured atmospheric air Radon.Moderate seasonal variation of Cxindoors has been observed, although 90 % of the obtained indoor Cxmeasurements are below 100 Bq m~(-3). Some homes produced Cxreadings above the permissible limit. Results showed that the ventilation effect played a major factor in reducing radon concentration levels indoors. Health assessment has been considered. Annual effective doses of radon varied from 1.01 ± 0.10 to 8.65 ± 0.50 m Sv a~(-1) in six homes in one of the four cases studied. These dosage values are above the permitted limit of 2.5 m Sv a~(-1). Several types of granite contained in the studied homes were identified and their contributions to radon levels indoors were calculated.

Recent seismic events show that urban areas are increasingly vulnerable to seismic damage,which leads to unprecedented levels of risk.Cities are complex systems and as such their analysis requires a good understanding of the interactions between space and the socioeconomic variables characteristic of the inhabitants of urban space.There is a clear need to develop and test detailed models that describe the behavior of these interactions under seismic impact.This article develops an overall vulnerability index to seismic hazard based on a spatial approach applied to Bucharest,Romania,the most earthquake-prone capital in the European Union.The methodology relies on:(1) spatial post-processed socioeconomic data from the2011 Romanian census through multicriteria analysis;and(2) analytical methods(the Improved Displacement Coefficient Method and custom-defined vulnerability functions)for estimating damage patterns,incorporated in a GIS environment.We computed vulnerability indices for the128 census tracts of the city.Model sensitivity assessment tested the robustness of spatially identified patterns of building vulnerability in the face of uncertainty in model inputs.The results show that useful seismic vulnerability indices can be obtained through interdisciplinaryapproaches that enhance less detailed datasets,which leads lead to better targeted mitigation efforts.

The Millennium Development Goals(MDGs)with their holistic perspective of development are focused on different issues of vulnerability.This article highlights the situation of women in disasters and the challenges in achieving the MDGs with special reference to India.It is accepted that there is no disaster without human engagement and that issues of differential impact on genders is an essential consideration for recovery.The international guidelines on disaster management and intervention have a considerable focus on gender equality,balance,mainstreaming,and sensitive programing,yet the situation is quite grim.India still lacks separate policy guidelines on gender aspects in disaster.In the twenty-first century,India has witnessed a series of disasters in different parts of the country.The author's personal experiences of working in intervention programs of these disasters showed that gender vulnerability depends on various factors like the intensity of the disaster impact,local sociocultural perspectives,effective disaster intervention strategies,the specific focus on issues of women in training of personnel,and gender-sensitive disaster intervention programs in the community.In the context of the MDGs,while development has become a priority concern to end age-old inequalities in society,the added challenge of disasters needs considerable focus on gender inequalities to achieve the goal of gender equity.

Industrial accidents have shown that many people can be affected,such as in Seveso,Italy,in 1976.Industrial accidents in nuclear power plants have also led to fatalities and evacuations.To better guide preparedness against and mitigation of industrial accidents,an assessment is necessary to evaluate hazard exposure and the type of potentially vulnerable social groups that need to be taken into account.This study conducted a spatial assessment of three types of industrial facilities in Germany:facilities registered under the Seveso Directive,chemical parks,and nuclear power plants.The method consisted of a spatial assessment using a Geographic Information System of exposure around hazardous sites registered under the S eveso Directive in Germany and of census data to analyze social vulnerability.Hazards analyzed included industrial accidents and earthquakes.The results revealed that most industrial sites are in urban areas and that population density,the numbers of foreigners,and smaller housing unit sizes are higher in close proximity to these sites.The buffer zones analyzed in circles between 1 and 40 km show a decreasing vulnerability with more distance.This can guide emergency management planners and other stakeholders to better prepare for major accidents and better devise disaster risk reduction strategies specifically for different social groups.

One of the most serious resource and health issues in coastal communities of Bangladesh is the scarcity of safe drinking water, triggered by the combined effects of salinity, arsenic, and drought. This article explores community perception of vulnerabilities in daily life, livelihood, and environment, and investigates how communities and institutions cope with or adapt to drinking water scarcity. This study outlines community expectations for support from government and nongovernment organizations to overcome this problem. The findings reveal that nearly all respondents from the drinking water scarcity area perceive that salinity is the primary reason for the lack of safe drinking water compared to arsenic and drought hazards. Despite a number of socioeconomic factors and a geographical location that aggravates the coastal communities' vulnerability, these communities have established their own adaptation mechanism to cope with this crisis.Government and nongovernment organizations have also supported community efforts to cope with the problem. By emphasizing both community adaptation methods and efforts of institutions, this article illustrates an integrated community-based approach, which would be effective for reducing drinking water scarcity in the southwestern coastal region of the country.

The eastern Mediterranean region is an active tectonic setting that includes the Dead Sea Transform Fault, which forms the boundary between the African and the Arabian Plates and crosses Lebanon from south to north, striking in a restraining bend around 25–30°NE. The major structural feature in Lebanon is the Yammouneh Fault, which reaches to Syria and southern Turkey in a north–south direction. Measurements of radon gas concentration and exhalation rates in two locations along the southern segment of the Yammouneh Fault in south Lebanon were performed. Two profiles in the El-Khiam basin and Blat pull-apart basin and perpendicular to the Yammouneh Fault trace were analyzed. An approximate fault width 25–30 m wide was determined in the El-Khiam study area. Temporal increase of radon concentration was measured and correlated with stress/strain tectonic activity and stress drops along the studied fault segment boundary.Anomalous variable radon concentrations were detected during one of the measurements where an earthquake occurred in the region of Tiberias Lake in northern Palestine along the Yammouneh Fault in the study area. Measurements of radon concentration along a station's profile in Blat village did not show any radon anomalous variation due to the discontinuity along the fault(pull-apart), and possible absence of stress and energy accumulation along the Yammouneh Fault line in that location.

To investigate why people live in areas at high risk of floods, a qualitative case study was carried out in the areas around Akuressa, in southwest Sri Lanka. Data collection consisted mainly of semistructured interviews with local residents and government officials. The purpose was to study why people live in areas at high risk of floods, by looking beyond the purely physical aspects of living with hazards and exploring the underlying social factors. Four main factors were identified: an overall good living situation; a sense of place; difficulties relocating; and being well-adapted to the situation. The analysis also examined whether government officials shared the views of local residents. The findings highlighted both areas of consensus and discrepancies related to risk awareness, and the efficiency of risk reduction measures that had been implemented by the government. The case study identified and explored underlying social factors, such as risk normalization, risk trade-offs, and push-and-pull processes, which seem to influence the decision to live in a high-risk area.

To prepare a landslide susceptibility map of Shivkhola watershed,one of the landslide prone parts of Darjeeling Himalaya,remote sensing and GIS tools were used to integrate 10 landslide triggering parameters:lithology,slope angle,slope aspect,slope curvature,drainage density,upslope contributing area(UCA),lineament,settlement density,road contributing area(RCA),and land use and land cover(LULC).The Analytical Hierarchy Process(AHP) was applied to derive factor weights using MATLAB with reasonable consistency ratio(CR).The frequency ratio(FR) model was used to derive class frequency ratio or class weights that indicate the relative importance of individual classes for each factor.The weighted linear combination(WLC) method was used to determine the landslide susceptibility index value(LSIV) on a GIS platform,by incorporating both factor weights and class weights.The Shiv-khola watershed is classified into five landslide susceptibility zones.The overall classification accuracy is 99.22 and Kappa Statistics is 0.894.

To estimate human loss in an earthquake-prone area, it is necessary to analyze the role played by the spatiotemporal distribution of the area's resident population. In order to evaluate earthquake impact, this article focuses on the spatiotemporal distribution of population and five scenario earthquakes that form the basis for loss estimation in the city of Sylhet, Bangladesh. Four temporal contexts(weekday, weekly holiday, the 30 days of Ramadan, and strike days) expand the more typical daytime and nighttime settings in which to examine hazard risk. The population distribution for every 2 hour interval in a day is developed for each type of day. A relationship between the occupancy classes and average space(persons per 100 m~2)is used to distribute people in each building regardless of building locations. A total daytime and nighttime population is obtained for each building and the estimated nighttime population is used to model the population for four temporal scenarios in a year based on different factors and weights. The resulting data are employed to estimate population loss for each of the temporal and earthquake scenarios. This study used building-specific human vulnerability curves developed by the Central American Probabilistic Risk Assessment(CAPRA) to obtain possible loss of life estimates. The results reveal that there is a high positive correlation between the spatiotemporal distribution of population and the potential number of casualties.

This article summarizes and analyzes the Children & Youth Forum and youth participation in the process during and leading up to the Third UN World Conference on Disaster Risk Reduction(WCDRR) in2015. An organizing committee consisting of international students and young professionals brought together around200 young professionals and students from around the globe to exchange ideas and knowledge on reducing disaster risk, building resilient communities, and advocating for the inclusion of youth priorities within the Sendai Framework for Disaster Risk Reduction 2015–2030(SFDRR). The knowledge exchange during the Forum was structured around a Toolbox for Resilience that connected to the SFDRR section on Priorities for Action. This article presents the outcomes of these young people's participation in the disaster risk reduction capacity building eventsand policy-making, as well as the follow-up actions envisioned by the young participants of the Forum. The voices of the younger generation were heard in the SFDRR and young people are ready to expand their actions for the framework's effective implementation. Young people call on technical experts, donors, NGOs, agencies, governments, and academia to partner with them on this journey to create a more resilient tomorrow together.

Climate change adaptation(CCA) and disaster risk reduction(DRR) have similar targets and goals in relation to climate change and related risks. The integration of CCA in core DRR operations is crucial to provide simultaneous benefits for social systems coping with challenges posed by climate extremes and climate change.Although state actors are generally responsible for governing a public issue such as CCA and DRR integration,the reform of top-down governing modes in neoliberal societies has enlarged the range of potential actors to include non state actors from economic and social communities. These new intervening actors require in-depth investigation. To achieve this goal, the article investigates the set of actors and their bridging arrangements that create and shape governance in CCA and DRR integration. The article conducts a comprehensive literature review in order to retrieve main actors and arrangements. The article summarizes actors and arrangements into a conceptual governance framework that can be used as a backdrop for future research on the topic. However, this framework has an explorative form, which must be refined according to site-and context-specific variables, norms, or networks.Accordingly, this article promotes an initial application of the framework to different contexts. Scholars may adopt the framework as a roadmap with which to corroborate the existence of a theoretical and empirical body of knowledge on governance of CCA and DRR integration.

Scholars from environmental psychology,geography, disaster science, and sociology have recently focused attention on evacuation and relocation behaviors and influencing factors in hazard-threatened areas. However, existing studies are mainly focused on developed countries and the influence of individual characteristics,household characteristics, and the perception of risk of urban households on evacuation and relocation behaviors.Few studies examine developing countries and the influence of farmers' sense of place in geological hazardthreatened areas. Using statistics of farming households in an area threatened by landslides, this is a pilot study to explore the relationship of sense of place to the relocation willingness of farming households while controlling for other variables. The results show that:(1) Households with higher scores of place identity and place dependence are less willing to relocate, whereas place attachment has no significant relationship to household relocation willingness;(2) Risk perception dimensions, including probability,threat, and controllability have a significant relationship to household relocation willingness, while worry and fear of the unknown have no significant relationship;(3) Household characteristics, including income, whether a household has experienced economic loss from landslides, and social support are significantly correlated with household relocation willingness, while gender, age, experience, distance to hazard sites, size of household, children, older people, and housing material are not. The results for information and education are not robust. This study contributes to the current literature by improving the understanding of the relationship of sense of place to the relocation willingness of farming households in villages threatened by geological disasters in rural China.

Planning in advance to prepare for and respond to a natural hazard-induced disaster-related emergency is a key action that allows decision makers to mitigate unexpected impacts and potential damage. To further this aim, a collaborative, modular, and information and communications technology-based Spatial Data Infrastructure(SDI)called SIRENE—Sistema Informativo per la Preparazione e la Risposta alle Emergenze(Information System for Emergency Preparedness and Response) is designed and implemented to access and share, over the Internet, relevant multisource and distributed geospatial data to support decision makers in reducing disaster risks. SIRENE flexibly searches and retrieves strategic information from local and/or remote repositories to cope with different emergency phases. The system collects, queries, and analyzes geographic information provided voluntarily by observers directly in the field(volunteered geographic information(VGI) reports) to identify potentially critical environmental conditions. SIRENE can visualize and cross-validate institutional and research-based data against VGI reports,as well as provide disaster managers with a decision support system able to suggest the mode and timing of intervention, before and in the aftermath of different types of emergencies, on the basis of the available information and in agreement with the laws in force at the national andregional levels. Testing installations of SIRENE have been deployed in 18 hilly or mountain municipalities(12 located in the Italian Central Alps of northern Italy, and six in the Umbria region of central Italy), which have been affected by natural hazard-induced disasters over the past years(landslides, debris flows, floods, and wildfire) and experienced significant social and economic losses.

Most policy analyses of both short-term and long-term disasters focus on aggregate impacts of their costs and the benefits of policy remedies. Distributional considerations relating to the costs of these disasters and the benefits of their risk management, however, are very important in many cases. This article examines two broad categories of cases in terms of distributional considerations. The first category is where transboundary considerations strongly affect risk governance, as in the case of climate change. The second relates to ordinary, short-term disasters, which include fewer, but still important, transboundary issues. Climate change policy requires information regarding the distribution of impacts and policy responses across countries because it is a global problem.Conventional disasters involve transboundary considerations much less frequently, so the attention typically shifts to the distribution of benefits and costs within a jurisdiction. In both cases distributional information is needed to evaluate the equity of policies and to provide information for public participation in the policy process. This article offers modeling and policy approaches to address these issues.

Isolated communities on small islands are often characterized as vulnerable and marginalized. We studied the recent history of Laingpatehi, a village on Ruang Island off the north coast of Sulawesi, Indonesia to show that the marginalization-vulnerability nexus can be offset by capacity and social cohesion to enable sustainable livelihoods. The island has been impacted by volcanic eruptions,earthquakes, and competition for marine resources from mainland-based fishermen. The community has shown a remarkable ability to cope and prosper in the face of a series of external hazards. We used a sustainable livelihoods approach to identify the assets that enabled the villagers to cope. Strong social cohesion was central to the ability to organize the community and confront hazards. A diversified livelihood strategy drawing on the small island environment and its coastal and marine resources, income generating activities in a distant satellite village, and significant remittances from employment in other parts of Indonesia underpinned people's capacities to face hazards.Government assistance played a supporting role. The case of Laingpatehi demonstrates how remoteness, rather than being a source of vulnerability, can provide access to existing resources and facilitate innovation. Disaster risk reduction strategies should focus more on reinforcing these existing capacities to deal with hazards and less on physical protection and postdisaster responses.

One relatively novel way of assessing the characteristics and limitations of resilience and vulnerability(R&V)is undertaken in this article by investigating a growing alternative paradigm—loss and damage(L&D)policy.The idea of L&D as an emerging policy may be surprising to many in the disaster risk management community,and so we first outline the origins of this trend,and then explore the potential benefits and pitfalls of adopting it.This short article represents our preliminary opinions and observations regarding this reintroduction of a longestablished concept.We also present results from a very brief peer-group survey on some of the first immediate reactions towards L&D policy.At this early stage,this article cannot offer a full-fledged analysis,but our reflections may serve as a starting point to encourage further discussion.

This article addresses resilience and vulnerability as two prominent concepts within disaster risk science. The authors provide an overview of current uses and bene?ts of and challenges to resilience and vulnerability concepts for disaster risk management(DRM). The article summarizes the evolution of these concepts and of attempts to de?ne them precisely,and addresses the potential bene?ts of conceptual vagueness.The usage and conception of resilience and vulnerability within a selection of strategies and legislations in DRM are compared. Complementing this analysis of disaster risk research and management practice, a survey identi?es some of the bene?ts of and challenges to the concepts of resilience and vulnerability as seen by a peer-community. Synthesizing the three approaches, we conclude that a certain conceptual and methodological ‘‘haze'' prevails, which hampers the transfer of information and ?ndings within disaster risk science, from science to practice, and vice versa. But this vagueness offers opportunities for communication between disaster risk science, policy, and practice. Overall, evaluations of the resilience and vulnerability concepts are lacking, which demands the development of criteria to identify and assess the challenges to and bene?ts of resilience and vulnerability for DRM.

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

Resilience has become a cornerstone for risk management and disaster reduction. However, it has evolved extensively both etymologically and conceptually in time and across scientific disciplines. The concept has been(re)shaped by the evolution of research and practice efforts. Considered the opposite of vulnerability for a long time, resilience was first defined as the ability to resist,bounce back, cope with, and recover quickly from the impacts of hazards. To avoid the possible return to conditions of vulnerability and exposure to hazards, the notions of post-disaster development, transformation, and adaptation(build back better) and anticipation, innovation,and proactivity(bounce forward) were then integrated.Today, resilience is characterized by a multitude of components and several classifications. We present a selection of 25 components used to define resilience, and an interesting linkage emerges between these components and the dimensions of risk management(prevention, preparedness,response, and recovery), offering a perspective to strengthen resilience through the development of capacities. Despite its potential, resilience is subject to challenges regarding its operationalization, effectiveness, measurement, credibility, equity, and even its nature. Nevertheless,it offers applicability and opportunities for local communities as well as an interdisciplinary look at global challenges.