An approach for measuring social vulnerability in context: The case of flood hazards in Muzarabani district,Zimbabwe

Understanding the complexity of vulnerability to disasters, including those triggered by floods, droughts and epidemics is at the heart of disaster risk reduction. Despite its importance in disaster risk reduction, there remains a paucity of approaches that contribute to our understanding of social vulnerability that is hidden in dynamic contextual conditions. The study demonstrates an accessible means to assessing the spatial variation of social vulnerability to flood hazards and related for the context of Muzarabani district in northeast Zimbabwe. The study facilitated local identification with residents of variables contributing to social vulnerability and used the principal component analysis (PCA) technique to develop a social vulnerability index (SoVI). Using ArcMap10.2 geographic information systems (GIS) tool, the study mapped composite SoVI at the ward level. The results showed that Muzarabani district is socially vulnerable to hazards. The social vulnerability is influenced by a variety of economic, social and institutional factors that vary across the wards. Quantifying and visualising social vulnerability in Muzarabani provides useful information for decision makers to support disaster preparedness and mitigation programmes. The approach shows how spatially distributed multivariate vulnerability, as grounded in interpretations at local level, can be quantitatively derived for contexts such as those of Muzarabani. The study findings can inform disaster risk reduction communities and cognate disciplines on quantitative assessments for managing hazard vulnerability where these have hitherto not been developed.     

Social vulnerability to natural hazards in Indonesia: driving factors and policy implications

Indonesia is located in the Pacific Ring of Fire and situated at the joining point of four major world tectonic plates. Regions of Indonesia are highly prone to various natural hazards such as earthquakes, tsunamis and volcanic eruptions. Some recent major natural hazard events are the 2004 tsunami in Aceh and Nias and the 2010 Mount Merapi volcanic eruptions in Central Java. In parallel with advancement in knowledge of the existing hazards, the importance of social aspects of vulnerability in mitigating natural hazards has been acknowledged by the Indonesian government. However, to date, there is no institutionalized effort for assessing social vulnerability to natural hazards that would cover all the districts of Indonesia. Accordingly, no comprehensive profile of social vulnerability is available as basis information for developing strategies to prevent larger risk and losses and reduce vulnerability of communities in Indonesia. Only a few studies have been conducted in Indonesia on this field. This study attempts to fill this gap by quantifying the social vulnerability of Indonesian districts to natural hazards, determining its driving factors and mapping its variations. The social vulnerability index (SoVI) approach is utilized in this study. Three main driving factors affecting social vulnerability in Indonesia are found: ‘socioeconomic status and infrastructure,’ ‘gender, age and population growth’ and ‘family structure.’ The combination of SoVI with thematic map utilizing ArcView GIS can be used to identify districts with relative high social vulnerability level. The results can support the prevention, mitigation, preparedness, response and recovery programs of the impacts of natural hazards in Indonesia.     

Assessment of provincial social vulnerability to natural disasters in China

Assessment of social vulnerability has been recognized as a critical step to understand natural hazard risks and to enhance effective response capabilities. Although significant achievements have been made in social vulnerability researches, little is know about the comprehensive profile of regional social vulnerability in China. In this study, the social vulnerability to natural hazards was firstly divided into socioeconomic and built environmental vulnerability. Then, using factor analysis, we identified the dominant factors that influence the provincial social vulnerability in China to natural hazards based on the socioeconomic and built environmental variables in 2000 and 2010 and explored the spatial patterns of social vulnerability. The results indicated that the provincial social vulnerability in China showed significant regional differences. The social vulnerability in the southeastern and eastern regions of China was greater than its northern and central parts over the past decade. Economic status, rural (proportion of agricultural population and percentage of workers employed in primary industries), urbanization, and age structure (children) were the dominant driving forces of variations in provincial socioeconomic vulnerability in two studied years, while lifelines and housing age could explain most of changes in built environmental vulnerability in 2000 and 2010. There were no statistically significant correlations between social vulnerability and disaster losses (p > 0.05), indicating the impact of disasters was also related to the intensity of hazards and exposure. Disaster relief funds allocated to each province of China depended more on its disaster severity than the regional integrated social vulnerability over the past decade. These findings would provide a scientific base for the policy making and implementation of disaster prevention and mitigation in China.     

Integrated risk assessment of multi-hazards in China

Maps of population exposure, vulnerability and risk to natural hazards are useful tools for designing and implementing disaster risk mitigation programs in China. The ranking of provinces by relative risk to natural hazards would provide a metric for prioritizing risk management strategies. Using provinces as our study unit, from the perspectives of hazard exposure, susceptibility, coping capacity and adaptive capacity, this study first constructed China’s disaster risk index for five types of major natural hazards: earthquakes, floods, droughts, low temperatures/snow and gale/hail. Then, the relative risk level at the provincial scale in China was assessed. Finally, the hotspots with the highest hazard exposure, vulnerability and risk were identified. The results showed that high exposure was a significant risk driver in China, whereas high vulnerability, especially social vulnerability, amplified the risk levels. Similar to the population exposure to disasters, the relative risk levels in the southwestern, central and northeastern regions of China were significantly higher than those in the eastern, northern and western regions. The high-risk regions or hotspots of multi-hazards were concentrated in southern China (less-developed regions), while the low-risk regions were mainly distributed in the eastern coastal areas (well-developed regions). Furthermore, a nonlinear relationship existed between the disaster risk level and poverty incidence as well as per capita GDP, demonstrating that disaster losses in middle-income areas are likely to increase if economic policies are not modified to account for the rising disaster risk. These findings further indicated that research on disaster risk should focus not only on hazards and exposure but also on the vulnerability to natural disasters. Thus, reducing vulnerability and population exposure to natural hazards would be an effective measure in mitigating the disaster risk at hotspots in China.     

Social vulnerability assessment of natural hazards on county-scale using high spatial resolution satellite imagery: a case study in the Luogang district of Guangzhou,South China

Social vulnerability assessment of natural hazards aims to identify vulnerable populations and provide decision makers with scientific basis for their disaster prevention and mitigation decisions. A new method based on remote sensing is presented here to establish a model of social vulnerability for county-scale regions that lack of relative data. To calculate population density, which is the most important indicator in social vulnerability assessment, first, a statistical model is established to estimate the population on village level. Then a new concept defined as “population density based on land use” is created to replace the arithmetic population density. The former has taken the dynamic human distribution related to land use into account; thus, it can map the population distribution more realistically. The other two indicators are age structure and distance to hospital. The application of this method to the Luogang District of Guangzhou, South China demonstrated its capability of providing high spatial resolution and reasonable social vulnerability for social vulnerability assessment of natural hazards.     

Understanding the vulnerability of migrants in Shanghai to typhoons

China has experienced considerable migration from inland to coastal areas since the reforms of 1978, with migrants becoming an important population in many coastal cities. Compared with non-migrants (long-term residents), migrant vulnerability to typhoons is considered high due to limited access to job opportunities, social security, information, and other resources; however, there is no research on vulnerability of this population sector to natural hazards. This initial study analysed the perceptions and personal experiences of migrants living in Shanghai of typhoon hazards. During May 2010, empirical data were collected using an online questionnaire and face–face interviews. Response data indicated that risk knowledge of migrants was significantly lower than among non- migrants; differing risk perceptions between the groups were consistent with levels of personal typhoon experience; statistically significant differences in hazard knowledge within the sample also related to education and occupation; a variety of strategies to cope with typhoon hazards was being applied by residential committees; and that migrants were not generally recognised as a vulnerable group requiring special consideration in hazard risk management. To reduce the vulnerability of migrants to typhoons, we recommend expanding the range of accessible communication technologies distributing warning information; organising more educational and training programmes, at government and corporate level, to increase community awareness of natural hazards; encouraging local residential committees to promote social networks and engagement for migrants; and providing corporate incentives to develop insurances specifically for migrant needs. Further research is necessary to assess the differences in vulnerability between different types of migrants.     

Integrated risk assessment method of waterlog disaster in Huaihe River Basin of China

Regional waterlog disaster integrated risk system, affected by natural, social, and economic systems and its combination relationship, is a complex system with certain structure and function. Waterlog disaster integrated risk results from the combined effects of regional environment, impact factors, vulnerability, and disaster-reducing capability of flood hazards in the drainage area. Waterlog disaster integrated risk system can be divided into four subsystems of hazard, vulnerability, disaster-reducing capability, and disaster conditions. Evaluation indexes are selected using fuzzy analytic hierarchy process method, and the evaluation index system is established. Then, the waterlog disaster integrated risk evaluation model is proposed based on set pair analysis method. Taking Huaihe river in Anhui Province of China as the typical area in this study, the results show that the proposed approach is able to obtain the spatial distribution characteristics of waterlog hazard, vulnerability, mitigation capabilities, and integrated disaster risk within the study area. From the quantitative point of view, identification of the areas with high flood risk can provide a scientific basis for the flood management and technical support.     

Integrated risk assessment method of waterlog disaster in Huaihe River Basin of China

Regional waterlog disaster integrated risk system, affected by natural, social, and economic systems and its combination relationship, is a complex system with certain structure and function. Waterlog disaster integrated risk results from the combined effects of regional environment, impact factors, vulnerability, and disaster-reducing capability of flood hazards in the drainage area. Waterlog disaster integrated risk system can be divided into four subsystems of hazard, vulnerability, disaster-reducing capability, and disaster conditions. Evaluation indexes are selected using fuzzy analytic hierarchy process method, and the evaluation index system is established. Then, the waterlog disaster integrated risk evaluation model is proposed based on set pair analysis method. Taking Huaihe river in Anhui Province of China as the typical area in this study, the results show that the proposed approach is able to obtain the spatial distribution characteristics of waterlog hazard, vulnerability, mitigation capabilities, and integrated disaster risk within the study area. From the quantitative point of view, identification of the areas with high flood risk can provide a scientific basis for the flood management and technical support.

     

Constructing a social vulnerability index to earthquake hazards using a hybrid factor analysis and analytic network process (F’ANP) model

Iran is a seismic prone country and has been host to a long series of devastating earthquakes which have resulted in heavy casualties and damages. In order to assess social vulnerability (SV) to earthquake hazards, this paper presents the development of a hybrid factor analysis and analytic network process model for aggregating vulnerability indicators into a composite index of SV to earthquake hazards. The proposed model is then applied in Iran as a case study. The proposed model uses factor analysis (FA) to extract the underlying dimensions of SV. The identified dimensions of SV and their primary variables are then entered into a network model in Analytic Network Process (ANP). The ANP is used to calculate the relative importance of different SV variables, taking into consideration the results obtained from FA and the possible interdependence between variables of the individual dimensions of SV. These weights are then used to compute the factor scores for the individual dimensions of SV and also the composite social vulnerability index (SOVI). The application of the proposed model to a real world case study and its validation show that it is a robust approach for constructing a composite SOVI. Its application to counties in Iran indicates that there exist severe regional differences in terms of SV to earthquake hazards. The pronounced regional variations in SV warrant special attention by both local authorities and the national government to reconsider current natural disaster management strategies.     

Social vulnerability in the context of bushfire risk at the urban-bush interface in Sydney: a case study of the Blue Mountains and Ku-ring-gai local council areas

In the recent past, Australia has experienced several catastrophic hazard events and the frequency and intensity of such events is expected to increase in the future. Natural hazards can rarely be fully prevented, yet their losses can be minimized if the necessary preparedness and mitigation actions are taken before an event occurs. Identification of vulnerable groups is an important first step in any preparedness and emergency management planning process. Social vulnerability refers to population characteristics that influence the capacity of a community to prepare for, respond to and recover from disasters. Factors that contribute to social vulnerability are often hidden and difficult to capture. This study analyzes the relative levels of social vulnerability of communities at the urban?Cbush interface in the Blue Mountains and Ku-ring-gai local council areas in New South Wales (NSW), Australia. We tested whether a standardized social vulnerability index could be developed using a pre-existing set of indicators. We created an exploratory principle component analysis model using Australian Bureau of Statistics 2006 census data at the Census Collection District (CCD) level. We identified variables contributing to social vulnerability and used the component scores to develop a social vulnerability index. Finally, the social vulnerability index was mapped at the CCD level. Our results indicate that both contributors to and the level of social vulnerability differ between and within communities. In other words, they are spatially variable. They show different spatial patterns across the areas, which provides useful information for identifying communities that are most likely to experience negative disaster impacts due to their socio-demographic characteristics.     

The tourism disaster vulnerability framework: an application to tourism in small island destinations

Islands are known to be vulnerable to natural hazards, resulting in substantial risks for their tourism industries. To facilitate the systematic analysis of the underlying vulnerability drivers, a tourism disaster vulnerability framework was developed. The conceptual model then guided qualitative empirical research in three regions: the Caribbean, the South Pacific, and the Indian Ocean. The results from 73 interviews highlight common, as well as idiosyncratic, factors that shape the islands’ hazardscapes and vulnerabilities. Key vulnerabilities included social, economic, political, and environmental dimensions. Probably, the most critical vulnerability driver is the lack of private sector investment in disaster risk reduction. This is interrelated with deficient planning processes, on-going demand for coastal products, lack of political will, and poor environmental conditions. Notwithstanding many barriers, some businesses and organisations engage proactively in addressing disaster risk. The paper’s empirical evidence supports the validity of the framework, and suggestions for further research are made.     

The constituent components and local indicator variables of social vulnerability index

Natural Hazards - Social vulnerability index (SoVI) has been widely used to measure the extent to which people or places are socially vulnerable. The SoVI is an aggregate composite index that...     

Multi-criteria vulnerability analysis to earthquake hazard of Bucharest, Romania

The expansive infrastructure, along with the high population density, makes cities highly vulnerable to the severe impacts of natural hazards. In the context of an explosive increase in value of the damage caused by natural disasters, the need for evaluating and visualizing the vulnerability of urban areas becomes a necessity in helping practitioners and stakeholders in their decision-making processes. The paper presented is a piece of exploratory research. The overall aim is to develop a spatial vulnerability approach to address earthquake risk, using a semi-quantitative model. The model uses the analytical framework of a spatial GIS-based multi-criteria analysis. For this approach, we have chosen Bucharest, the capital city of Romania, based on its high vulnerability to earthquakes due to a rapid urban growth and the advanced state of decay of the buildings (most of the building stock were built between 1940 and 1977). The spatial result reveals a circular pattern, pinpointing as hot spots the Bucharest historic centre (located on a meadow and river terrace, and with aged building stock) and peripheral areas (isolated from the emergency centers and defined by precarious social and economic conditions). In a sustainable development perspective, the example of Bucharest shows how spatial patterns shape the ??vulnerability profile?? of the city, based on which decision makers could develop proper prediction and mitigation strategies and enhance the resilience of cities against the risks resulting from the earthquake hazard.     

Social vulnerability assessment for mitigation of local earthquake risk in Los Angeles County

Comprehensive hazard mitigation involves (1) understanding natural systems, (2) assessment of interactions within and between social systems and the built environment, and (3) understanding geo-spatial processes. To achieve this, local emergency managers must recognize variability in vulnerable populations exposed to hazards and develop place-based emergency plans accordingly. In this study, we assess whether cities in Los Angeles County are subject to disproportionally greater earthquake losses modeled from a M7.8 earthquake on the San Andreas fault. Furthermore, we analyze whether the variation in demographic and socioeconomic characteristics across cities is associated with the earthquake losses. We were able to explain 23.2?% of variance in economic losses by looking at the percentage of minority residents, income, and renter residents in a city [F(3,84)?=?8.47; p?<?.001]. Cities with primarily minority residents had greater economic losses when compared to cities with primarily White residents (b?=?1.01; p?<?.001). When looking at the association between demographic predictors and potential casualty rate, the percentage of Hispanic residents was positively associated with the potential casualty rate. We argue that knowledge of the relationship between earthquake hazard and the demographic characteristics of people in the area at risk is essential to mitigate the local impact from earthquakes. In other words, we apply social vulnerability assessment as part of a comprehensive risk management framework to accelerate recovery after an event. Local policy makers and the private sector can use this approach to gain a better understanding of a city??s social vulnerability and adapt their preparedness efforts accordingly.     

Community-based disaster risk and vulnerability models of a coastal municipality in Bangladesh

Bangladesh is one of the most natural hazard-prone countries in the world with the greatest negative consequences being associated with cyclones, devastating floods, riverbank erosion, drought, earthquake, and arsenic contamination, etc. One way or other, these natural hazards engulfed every corner of Bangladesh. The main aim of this research paper is to carry out a multi-hazards risk and vulnerability assessment for the coastal Matlab municipality in Bangladesh and to recommend possible mitigation measures. To this aim, hazards are prioritized by integrating SMUG and FEMA models, and a participation process is implemented so as to involve community both in the risk assessment and in the identification of adaptation strategies. The Matlab municipality is highly vulnerable to several natural hazards such as cyclones, floods, and riverbank erosion. The SMUG is a qualitative assessment, while FEMA is a quantitative assessment of hazards. The FEMA model suggests a threshold of highest 100 points. All hazards that total more than 100 points may receive higher priority in emergency preparedness and mitigation measures. The FEMA model, because it judges each hazard individually in a numerical manner, may provide more satisfying results than the SMUG system. The spatial distributions of hazard, risk, social institutions, land use, and other resources indicate that the flood disaster is the top environmental problem of Matlab municipality. Hazard-specific probable mitigation measures are recommended with the discussion of local community. Finally, this study tries to provide insights into the way field research combining scientific assessments tools such as SMUG and FEMA could feed evidence-based decision-making processes for mitigation in vulnerable communities.     

Coastal vulnerability assessment for Chennai, east coast of India using geospatial techniques

The study area is 56-km coastal zone of Chennai district of the Tamil Nadu state, southeast coast of India. The coastline, which includes tourist resorts, ports, hotels, fishing villages, and towns, has experienced threats from many disasters such as storms, cyclones, floods, tsunami, and erosion. This was one of the worst affected area during 2004 Indian Ocean tsunami and during 2008 Nisha cyclone. The present study aims to develop a Coastal Vulnerability Index for the Chennai coast using eight relative risk variables to know the high and low vulnerable areas, areas of inundation due to future SLR, and land loss due to coastal erosion. Both conventional and remotely sensed data were used and analyzed with the aid of the remote sensing and geographic information system tools. Zones of vulnerability to coastal natural hazards of different magnitude (high, medium, and low) are identified and shown on a map. Coastal regional elevation, near-shore bathymetry, and socio-economic conditions have been considered as additional important variables. This study revealed that 11.01?km of the coastline has low vulnerability, 16.66?km has medium vulnerability, and 27.79?km is highly vulnerable in the study area, showing the majority of coastline is prone to erosion. The map prepared for the Chennai coast can be used by the state and district administration involved in the disaster mitigation and management plan and also as a tool in planning a new facility and for insurance purpose.     

Identifying urban–rural differences in social vulnerability to natural hazards: a case study of China

Identifying and analyzing the urban–rural differences of social vulnerability to natural hazards is imperative to ensure that urbanization develops in a way that lessens the impacts of disasters and generate building resilient livelihoods in China. Using data from the 2000 and 2010 population censuses, this study conducted an assessment of the social vulnerability index (SVI) by applying the projection pursuit cluster model. The temporal and spatial changes of social vulnerability in urban and rural areas were then examined during China’s rapid urbanization period. An index of urban–rural differences in social vulnerability (SVI_D) was derived, and the global and local Moran’s I of the SVI_D were calculated to assess the spatial variation and association between the urban and rural SVI. In order to fully determine the impacts of urbanization in relation to social vulnerability, a spatial autoregressive model and Bivariate Moran’s I between urbanization and SVI were both calculated. The urban and rural SVI both displayed a steadily decreasing trend from 2000 to 2010, although the urban SVI was always larger than the rural SVI in the same year. In 17.5% of the prefectures, the rural SVI was larger than the urban SVI in 2000, but was smaller than the urban SVI in 2010. About 12.6% of the urban areas in the prefectures became less vulnerable than rural areas over the study period, while in more than 51.73% of the prefectures the urban–rural SVI gap decreased over the same period. The SVI_D values in all prefectures had a significantly positive spatial autocorrelation and spatial clusters were apparent. Over time, social vulnerability to natural hazards at the prefecture-level displayed a gathering–scattering pattern across China. Though a regional variation of social vulnerability developed during China’s rapid urbanization, the overall trend was for a steady reduction in social vulnerability in both urban and rural areas.

     

Simulation of physical and socioeconomic factors of vulnerability to cyclones and storm surges using GIS: a case study

The objective of the present study is to simulate the physical and socioeconomic factors of human vulnerability to tropical cyclones and storm surges at the household level in existing and changing status of households. The primary data were collected from a cyclone prone coastal area in Bangladesh, through structured questionnaire and GPS survey, key informants interviews and field observations. In order to simulate the physical and socioeconomic factors geographical information systems based Structured Query Language (SQL) query has been used. The study simulated the physical and socioeconomic factors of human vulnerability to tropical cyclones and storm surges on the basis of collected data through pre-designed SQL query. The study found the number of most vulnerable households under existing conditions and how much it will be afterward of a favourable or adverse change of the factors of vulnerability associated with households. The major findings of the study unveil that the socioeconomic and physical factors of human vulnerability have important function to determine the household’s level of vulnerability to the cyclone induced disaster. It has been demonstrated that the degree of vulnerability of households is changed with its physical and socioeconomic status. This study provides a conceptual model for assessing and simulating vulnerability to other natural hazards like floods, droughts, riverbank erosions and so forth. This study highlights that the households’ intrinsic vulnerable conditions are responsible for its defencelessness to the hazards and the reduction of vulnerability is the first measure of integrated and sustainable disaster management in the coastal Bangladesh.     

The Determinants of Disaster Vulnerability: Achieving Sustainable Mitigation through Population Health

The growing appreciation of mitigation is highlighting theneed to develop a better understanding of what makes some people more vulnerable tothe impacts of a disaster. Health researchers have asked a similar question regarding thevarying vulnerability to illness within a population. This has lead to the identification of a setof social, physical and economic factors that are now referred to as the determinants of health.These factors are the same as those commonly associated with disaster vulnerability. Recognizingthat these same concepts are being applied in both the health and disaster management contextspresents an opportunity to also achieve a shared objective of reducing vulnerability withina population.     

基于自然灾害风险评价框架的省级地质灾害风险区划方法探讨——以吉林省为例

地质灾害风险区划是地质灾害风险管理与防治的有效手段之一,对于科学防治地质灾害具有重要意义。基于自然灾害风险理论,从致灾因子危险性,承灾体暴露性和脆弱性以及防灾减灾能力（恢复力）等入手,选取评价指标,构建省级地质灾害风险评价模型,对全省地质灾害进行风险区划。该模型在吉林省地质灾害风险区划中应用表明,评价结果合理,与野外调查情况吻合,可以为规划和地质灾害防治等工作提供依据。