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This paper investigates local-scale social vulnerability to flood hazards in Romania, aiming to identify the most vulnerable social and demographic groups across a wide range of geographical locations by considering three dimensions: demographic, socioeconomic, and the built environment. The purpose of the paper is threefold: first, it strives to improve the Social Vulnerability model (SoVI®) by applying a different weighting method adapted to the Romanian context, taking into consideration the municipalities exposed to flood movements. Second, it aims to develop an assessment model for the most vulnerable communities by measuring the heterogeneity according to local indicators related to disaster risks. Third, it aims to facilitate emergency managers to identify community sub-groups that are more susceptible to loss and to increase the resilience of local communities. To perform local-level vulnerability mapping, 28 variables were selected and three aggregated indexes were constructed with the help of the ArcGIS software. Moreover, a model of Geographically Weighted Regression (GWR) between communities directly affected by floods and localities with high- and very high values of the Local Social Vulnerability Index (LoSoVI) was used to explore the spatial relationship among them and to compare the appropriateness of Ordinary Least Square (OLS) and GWR for such modelling. The established GWR model has revealed that the negative effects of flood hazards are often associated with communities with a high degree of social vulnerability. Thus, the analysis is able to provide a more comprehensive picture on communities in desperate need of financial resources in order to have the ability to diminish the negative impacts of flood hazards and to provide a more sustainable society.

28 Figure 7 : limites de la zone inondable et la zone inondée historiquement de la rive de Montréal de la rivière des prairies. [...] 68 Figure 27 : Aperçu de la table d’attributs de la base des données de la description de la sensibilité territoriale. [...] 41 Graphique 3 : Distribution des degrés de la sensibilité sociale par nombre d’aires de diffusion (206 AD au total) du secteur de la rivière des Prairies à Montréal à partir des résultats de l’indice ISSAIP des groupes de l’atelier de travail. [...] Cette analyse implique plusieurs étapes et le développement de plusieurs outils dont : la collecte des données disponibles et nécessaires pour réaliser un état des lieux des zones inondées historiquement pour une partie de la Ville de Montréal, la modélisation de l'espace occupé par l'eau selon différents niveaux d'eau possiblement atteints lors de débordement de la rivière, la collecte des donnée. [...] : la formation de réseaux de communication, la prise de décision, la création de consensus), qu’il est possible de mesurer, mais pas au moyen de données d’archives secondaires.

Abstract A leading challenge in measuring social vulnerability to hazards is for output metrics to better reflect the context in which vulnerability occurs. Through a meta-analysis of 67 flood disaster case studies (1997–2013), this paper profiles the leading drivers of social vulnerability to floods. The results identify demographic characteristics, socioeconomic status, and health as the leading empirical drivers of social vulnerability to damaging flood events. However, risk perception and coping capacity also featured prominently in the case studies, yet these factors tend to be poorly reflected in many social vulnerability indicators. The influence of social vulnerability drivers varied considerably by disaster stage and national setting, highlighting the importance of context in understanding social vulnerability precursors, processes, and outcomes. To help tailor quantitative indicators of social vulnerability to flood contexts, the article concludes with recommendations concerning temporal context, measurability, and indicator interrelationships.

Abstract Fatalities caused by natural hazards are driven not only by population exposure, but also by their vulnerability to these events, determined by intersecting characteristics such as education, age and income. Empirical evidence of the drivers of social vulnerability, however, is limited due to a lack of relevant data, in particular on a global scale. Consequently, existing global‐scale risk assessments rarely account for social vulnerability. To address this gap, we estimate regression models that predict fatalities caused by past flooding events ( n  = 913) based on potential social vulnerability drivers. Analyzing 47 variables calculated from publicly available spatial data sets, we establish five statistically significant vulnerability variables: mean years of schooling; share of elderly; gender income gap; rural settlements; and walking time to nearest healthcare facility. We use the regression coefficients as weights to calculate the “ Glob al‐ E mpirical So cial V ulnerability I ndex (GlobE‐SoVI)” at a spatial resolution of ∼1 km. We find distinct spatial patterns of vulnerability within and across countries, with low GlobE‐SoVI scores (i.e., 1–2) in for example, Northern America, northern Europe, and Australia; and high scores (i.e., 9–10) in for example, northern Africa, the Middle East, and southern Asia. Globally, education has the highest relative contribution to vulnerability (roughly 58%), acting as a driver that reduces vulnerability; all other drivers increase vulnerability, with the gender income gap contributing ∼24% and the elderly another 11%. Due to its empirical foundation, the GlobE‐SoVI advances our understanding of social vulnerability drivers at global scale and can be used for global (flood) risk assessments. , Plain Language Summary Social vulnerability is rarely accounted for in global‐scale risk assessments. We develop an empirical social vulnerability map (“GlobE‐SoVI”) based on five key drivers of social vulnerability to flooding, that is, education, elderly, income inequality, rural settlements and travel time to healthcare, which we establish based on flood fatalities caused by past flooding events. Globally, we find education to have a high and reducing effect on social vulnerability, while all other drivers increase vulnerability. Integrating social vulnerability in global‐scale (flood) risk assessments can help inform global policy frameworks that aim to reduce risks posed by natural hazards and climate change as well as to foster more equitable development globally. , Key Points We develop a global map of social vulnerability at ∼1 km spatial resolution based on five key vulnerability drivers (“GlobE‐SoVI”) We establish vulnerability drivers empirically based on their contribution to predicting fatalities caused by past flooding events Accounting for social vulnerability in global‐scale (flood) risk assessments can inform global policy frameworks that aim to reduce risk

Based on the Yearbook of Meteorological Disasters in China, we analyzed the spatiotemporal variations in major meteorological disaster (MD) losses at the provincial scale during 2001–2020 to determine the spatiotemporal variations in MDs and vulnerability in China. Our results suggest that the impacts of MDs, including floods, droughts, hail and strong winds (HSs), low temperature and frosts (LTFs), and typhoons, have been substantial in China. MDs in China affect an average of 316.3 million people and 34.3 million hectares of crops each year, causing 1,739 deaths and costing 372.3 billion yuan in direct economic losses (DELs). Floods and droughts affected more of the population in China than the other MDs. Fatalities and DELs were mainly caused by floods, and the affected crop area was mainly impacted by drought. The national average MD losses decreased significantly, except for DELs. The trends in the affected population and crop area were mainly caused by droughts, and the trends in fatalities and DELs were dominated by floods. Floods and typhoons showed increasing influence in the last two decades relative to other disasters. The annual mean and long-term trends in MD losses exhibited regional heterogeneity and were subject to different dominant hazards in different regions. The disaster losses and their trends in southeastern China were mainly attributed to typhoons. The affected population, crop area, and DELs were all significantly and positively correlated with exposure. The vulnerability of the population, crops, and economy tended to decrease. Economic development reduced the vulnerability of the population and economy but showed no significant influence on the vulnerability of crops. Our findings suggest that more focus should be placed on the impacts of floods and typhoons and that socioeconomic development has an important influence on the vulnerability of the population and economy. These results provide a foundation for designing effective disaster prevention and mitigation measures.

Tokyo is located in a lowland area that is vulnerable to flooding. Due to global climate change, the scalability and frequency of flooding is increasing. On the other hand, population aging and family structural changes, as well as the lack of adaptation measures, would accelerate flooding vulnerability. The key factors involved in social vulnerability must be studied to reduce the risk of flooding. In this study, we refer to the MOVE framework (a disaster vulnerability assessment framework) and analyze it from three perspectives: Exposure to social vulnerability, susceptibility, and resilience. We subsequently develop an index system to complete the evaluation using 11 indicators. The collected data will help reveal social vulnerability to floods in the Katsushika Ward, Tokyo, using the information entropy method and GIS. We found that the western region of the Katsushika Ward is at more risk than the eastern region during flooding. Additionally, the possibility of a serious crisis erupting is greater in the southwestern region than in the northwestern region. Consequently, we conclude that the spatial distribution of flooding varies in the region. The results of this study will help in understanding social vulnerability, in selecting and combining adaptation measures suited to the characteristics of the area, and in the effective and efficient implementation of these measures by the local government’s disaster department.

The impacts of flooding are expected to rise due to population increases, economic growth and climate change. Hence, understanding the physical and spatiotemporal characteristics of risk drivers (hazard, exposure and vulnerability) is required to develop effective flood mitigation measures. Here, the long-term trend in flood vulnerability was analysed globally, calculated from the ratio of the reported flood loss or damage to the modelled flood exposure using a global river and inundation model. A previous study showed decreasing global flood vulnerability over a shorter period using different disaster data. The long-term analysis demonstrated for the first time that flood vulnerability to economic losses in upper-middle, lower-middle and low-income countries shows an inverted U-shape, as a result of the balance between economic growth and various historical socioeconomic efforts to reduce damage, leading to non-significant upward or downward trends. We also show that the flood-exposed population is affected by historical changes in population distribution, with changes in flood vulnerability of up to 48.9%. Both increasing and decreasing trends in flood vulnerability were observed in different countries, implying that population growth scenarios considering spatial distribution changes could affect flood risk projections.

INTRODUCTION A substantial body of research has focused on the vulnerability of racial/ethnic minorities to hazards and disasters. This work has lumped people with diverse characteristics into general groups, such as "Hispanic" or "Latino/a" (Bolin 2007). Today, Hispanic immigrants represent an important group in U.S. society due to their large and increasing population. According to American Community Survey estimates, as of 2013 there were 21 million foreign-born Hispanics in the U.S., representing 52.5 percent of the total foreign-born population and 6 percent of the U.S. population. Hispanic immigrants are distinguishable from U.S.--born Hispanics due to their concerns about immigration status as well as cultural and linguistic differences. Treating Hispanics as a homogenous group may mask important differences between foreign-born and U.S.--born Hispanics and lead to erroneous conclusions about their disaster vulnerabilities. In order to address the particular risks experienced by foreign-born Hispanics in the U.S., more research characterizing salient dimensions of their vulnerability to hazards and disasters is needed. This study highlights particular vulnerabilities of foreign-born Hispanics living at risk to flooding and hurricanes in the Houston, Texas, and Miami, Florida, Metropolitan Statistical Areas (MSAs) by examining their self-protective actions, and their perceptions of and knowledge about flood risks, in comparison to both U.S.--born non-Hispanic whites and U.S.--born Hispanics. It addresses two research questions: what differences exist in self-protective actions and perceptions of risk between Hispanic immigrants, U.S.--born Hispanics, and U.S.--born white residents who live at high risk to flooding and hurricanes; and why do differences in self-protective actions and perceptions of risk exist between Hispanic immigrants, U.S.--born Hispanics, and U.S.--born white residents who live at high risk to flooding and hurricanes? Approaching these questions, we analyze primary structured survey and semistructured interview data using a mixed-method analysis approach, which enables us to clarify particular factors that place Hispanic immigrants at increased risk to flood and hurricane disasters. LITERATURE REVIEW The last three decades have marked the emergence of a social-vulnerability perspective on hazards and disasters, which emphasizes the influence of inequalities on differential risks (Hewitt 1983, 1997; Peacock and others 1997; Wisner and others 2004; Tierney 2006; Thomas and others 2013). From this perspective, risk is determined partly by human exposure to a hazard and partly by people's social vulnerability. While there is debate about the meaning and measurement of social vulnerability, the following definition is useful: "the characteristics of a person or group and their situation that influence their capacity to anticipate, cope with, resist and recover from the impact of a natural hazard" (Wisner and others 2004, 11). In this study, we analyze the social vulnerability of Hispanic immigrants in terms of self-protection from flood/hurricane hazards, and perceptions of and knowledge about flood/hurricane risks. Here, self-protection is defined as any structural or nonstructural strategy used by households to minimize loss and enable recovery from the impacts of flood or hurricane hazard exposures (NRC 2006). Self-protection strategies in the context of flood and hurricane hazards include home structural as well as nonstructural actions. Structural mitigation actions include elevating home structures, flood-proofing homes, and installing hurricane shutters (FEMA 2014). They also include nonstructural actions, such as maintaining flood insurance. In terms of nonstructural self-protection strategies, in the U.S., flood insurance plays an important protective role, since it provides compensation for property losses. Disaster preparedness is another dimension of nonstructural self-protection that has been examined extensively (Mulilis and Lippa 1990; Faupel and others 1992; Norris and others 1999; Sattler and others 2000; Miceli and others 2008; Borque and others 2013), and can include evacuation planning, maintaining basic supplies (for example, a first aid kit) and being alert (for example, being attentive to hazard reports). …

Abstract High-resolution global flood risk maps are increasingly used to inform disaster risk planning and response, particularly in lower income countries with limited data or capacity. However, current approaches do not adequately account for spatial variation in social vulnerability, which is a key determinant of variation in outcomes for exposed populations. Here we integrate annual average exceedance probability estimates from a high-resolution fluvial flood model with gridded population and poverty data to create a global vulnerability-adjusted risk index for flooding (VARI Flood) at 90-meter resolution. The index provides estimates of relative risk within or between countries and changes how we understand the geography of risk by identifying ‘hotspots’ characterised by high population density and high levels of social vulnerability. This approach, which emphasises risks to human well-being, could be used as a complement to traditional population or asset-centred approaches.

IntroductionCaribbean Small island developing states (SIDS) are generally qualified as disproportionately vulnerable to climate change, including extreme weather events like hurricanes. While many studies already documented the impacts of climate change on health in the wealthiest countries, there is little knowledge in this field in Caribbean SIDS. Our study aims to discuss health risks and vulnerabilities in a Caribbean context to inform future adaptation measures to climate change.MethodsOur paper is based on a qualitative study that was conducted in Dominica, a Caribbean SIDS. The data come from semi-structured interviews organized between March 2020 and January 2021 with people internally displaced following an extreme climate event, either tropical storm Erika (2015) or Hurricane Maria (2017), and with some people who migrated to Guadeloupe after Hurricane Maria. Interview guides were based on conceptual frameworks on climate change, migration and health, and vulnerability to climate change. Data were analyzed deductively based on frameworks and inductively to allow new codes to emerge.ResultsOur findings suggest that current knowledge of climate change by those who have been displaced by an extreme climate event varied greatly depending on the education level, class, and socioeconomic condition of the participant. Participants experienced various negative consequences from a storm or hurricane such as increased risk of relocation, lack of access to healthcare, and food, job, and water insecurities – all circumstances know to correlate with mental health issues. Participants suggested stronger dwellings, community preparedness committees to act sooner, and climate change sensitization and awareness campaigns to foster community unity and solidarity.ConclusionThese findings contribute to the perspectives and knowledge of climate change, highlighting that existing extreme climate event committees and government officials need to address structural and social barriers that can potentially increase social inequalities and lead to maladaptation to climate change with potential consequences on public health.

This paper explores the risk approach, considering both the physical and human dimensions of the phenomenon in order to produce a more realistic and spatial analysis of risk. Exposure and vulnerability were combined and evaluated multidimensionally, considering individual, socio-economic, and structural (building-related) aspects. These risk factors were then integrated in a multi-criteria analysis in order to produce a comprehensive risk index that could be visualized at the building scale. The relative importance of the indicators was determined through a participatory process involving local and national experts on civil security and flooding. Particular attention was paid to individual vulnerability, including perception and preparedness for flood risk, which were explored directly with local people using a questionnaire. Qualitative and quantitative analyses of the responses allowed for a better understanding of the perception and preparedness of populations exposed to flooding. These data should help to improve risk communication between the authorities concerned and the populations at risk, as well as encouraging implementation of appropriate measures and a bottom-up participatory management approach. The integration of data in a geographic information system enables the visualization and spatialization of risk, but also each of its components.