Urban Seismic Risk Evaluation: A Holistic Approach

Risk has been defined, for management purposes, as the potential economic, social and environmental consequences of hazardous events that may occur in a specified period of time. However, in the past, the concept of risk has been defined in a fragmentary way in many cases, according to each scientific discipline involved in its appraisal. From the perspective of this article, risk requires a multidisciplinary evaluation that takes into account not only the expected physical damage, the number and type of casualties or economic losses, but also the conditions related to social fragility and lack of resilience conditions, which favour the second order effects (indirect effects) when a hazard event strikes an urban centre. The proposed general method of urban risk evaluation is multi hazard and holistic, that is, an integrated and comprehensive approach to guide decision-making. The evaluation of the potential physical damage (hard approach) as the result of the convolution of hazard and physical vulnerability of buildings and infrastructure is the first step of this method. Subsequently, a set of social context conditions that aggravate the physical effects are also considered (soft approach). In the method here proposed, the holistic risk evaluation is based on urban risk indicators. According to this procedure, a physical risk index is obtained, for each unit of analysis, from existing loss scenarios, whereas the total risk index is obtained by factoring the former index by an impact factor or aggravating coefficient, based on variables associated with the socio-economic conditions of each unit of analysis. Finally, the proposed method is applied in its single hazard form to the holistic seismic risk evaluation for the cities of Bogota (Colombia) and Barcelona (Spain).     

Urban flood vulnerability assessments: the case of Dire Dawa city,Ethiopia

Dire Dawa city is identified as one of the most flood-affected cities in Ethiopia. Classifying village-level flood vulnerability using flood indicators is a new approach to Dire Dawa city. Analysis of different flood vulnerability factors underpins sustainable flood risk management and the application of Flood Vulnerability Index (FVI) approach is the hub of this study. Relevant data were collected from 110 households sampled from purposely selected 10 villages found in Dire Dawa city. The flood vulnerability index was used to compare, classify and rank villages in terms of their flood vulnerability levels. For this purpose, 24 sets of indicators which are strongly affecting the levels of flood vulnerability were assessed from social, economic and physical perspectives. The FVI of each village was computed with unequal method of weighting indicators. The findings of the study revealed that Dire Dawa city villages were experiencing varying levels of flood vulnerability. Accordingly, villages 05, 06, 07 and 09 were identified with high flood vulnerability level while villages 03, 04 and 08 and villages 01, 02 and extension village were identified with medium and low level of vulnerability, respectively. Interestingly, the findings of the study confirmed that social factors contributed much for flood vulnerability in Dire Dawa city. Hence, future urban flood risk planning and management endeavors in the city of Dire Dawa must be underpinned by proper utilization of the flood vulnerability map developed addressing social vulnerability component through both structural and non-structural urban flood risk management measures.

     

Urban social vulnerability assessment with physical proxies and spatial metrics derived from air- and spaceborne imagery and GIS data

Risk management in urban planning is of increasing importance to mitigate the growing amount of damage and the increasing number of casualties caused by natural disasters. Risk assessment to support management requires knowledge about present and future hazards, elements at risk and different types of vulnerability. This article deals with the assessment of social vulnerability (SV). In the past this has frequently been neglected due to lack of data and assessment difficulties. Existing approaches for SV assessment, primarily based on community-based methods or on census data, have limited efficiency and transferability. In this article a new method based on contextual analysis of image and GIS data is presented. An approach based on proxy variables that were derived from high-resolution optical and laser scanning data was applied, in combination with elevation information and existing hazard data. Object-oriented image analysis was applied for the definition and estimation of those variables, focusing on SV indicators with physical characteristics. A reference Social Vulnerability Index (SVI) was created from census data available for the study area on a neighbourhood level and tested for parts of Tegucigalpa, Honduras. For the evaluation of the proxy-variables, a stepwise regression model to select the best explanatory variables for changes in the SVI was applied. Eight out of 47 variables explained almost 60% of the variance, whereby the slope position and the proportion of built-up area in a neighbourhood were found to be the most valuable proxies. This work shows that contextual segmentation-based analysis of geospatial data can substantially aid in SV assessment and, when combined with field-based information, leads to optimization in terms of assessment frequency and cost.     

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.     

Energy transition,CO2 mitigation,and air pollutant emission reduction: scenario analysis from IPAC model

The salinization of freshwater-dependent coastal ecosystems precedes inundation by sea level rise. This type of saltwater intrusion places communities, ecosystems, and infrastructure at substantial risk. Risk perceptions of local residents are an indicator to gauge public support for climate change adaptation planning. Here, we document residential perspectives on the present and future threats posed by saltwater intrusion in a rural, low-lying region in coastal North Carolina, and we compare the spatial distribution of survey responses to physical landscape variables such as distance to coastline, artificial drainage density, elevation, saltwater intrusion vulnerability, and actual salinity measured during a synoptic field survey. We evaluate and discuss the degree of alignment or misalignment between risk perceptions and metrics of exposure to saltwater intrusion. Risk perceptions align well with the physical landscape characteristics, as residents with greater exposure to saltwater intrusion, including those living on low-lying land with high concentrations of artificial drainages, perceive greater risk than people living in low-exposure areas. Uncertainty about threats of saltwater intrusion is greatest among those living at higher elevations, whose properties and communities are less likely to be exposed to high salinity. As rising sea levels, drought, and coastal storms increase the likelihood of saltwater intrusion in coastal regions, integrated assessments of risk perceptions and physical exposure are critical for developing outreach activities and planning adaptation measures.

     

A multi-dimensional assessment of urban vulnerability to climate change in Sub-Saharan Africa

In this paper, we develop and apply a multi-dimensional vulnerability assessment framework for understanding the impacts of climate change-induced hazards in Sub-Saharan African cities. The research was carried out within the European/African FP7 project CLimate change and Urban Vulnerability in Africa, which investigated climate change-induced risks, assessed vulnerability and proposed policy initiatives in five African cities. Dar es Salaam (Tanzania) was used as a main case with a particular focus on urban flooding. The multi-dimensional assessment covered the physical, institutional, attitudinal and asset factors influencing urban vulnerability. Multiple methods were applied to cover the full range of vulnerabilities and to identify potential response strategies, including: model-based forecasts, spatial analyses, document studies, interviews and stakeholder workshops. We demonstrate the potential of the approach to assessing several dimensions of vulnerability and illustrate the complexity of urban vulnerability at different scales: households (e.g., lacking assets); communities (e.g., situated in low-lying areas, lacking urban services and green areas); and entire cities (e.g., facing encroachment on green and flood-prone land). Scenario modeling suggests that vulnerability will continue to increase strongly due to the expected loss of agricultural land at the urban fringes and loss of green space within the city. However, weak institutional commitment and capacity limit the potential for strategic coordination and action. To better adapt to urban flooding and thereby reduce vulnerability and build resilience, we suggest working across dimensions and scales, integrating climate change issues in city-level plans and strategies and enabling local actions to initiate a ‘learning-by-doing’ process of adaptation.

     

Comprehensive evaluation of urban flood-bearing risks based on combined compound fuzzy matter-element and entropy weight model

The extreme precipitation events caused by climate change and the rapid development of urbanization have brought hidden flood risks to the cities. This paper comprehensively considered two major factors of vulnerability of urban flood-bearing and disaster prevention and mitigation (DPAM) capacity and built a comprehensive evaluation index system for urban flood-bearing risks. Secondly, a combined model consisted of composite fuzzy matter-element and entropy weight model was constructed to calculate the comprehensive risk indicator. Finally, the Zhengzhou City was taken as an example, the comprehensive indices of urban flood-bearing risk from 2006 to 2015 were evaluated. The results showed that the comprehensive risk of Zhengzhou City was generally on a slow upward trend, from II level (moderate-risk) in 2006 to III level (secondary high-risk) in 2015, which was mainly due to the mismatch between the rapid development of urbanization and the slow improvement of DPAM capabilities. This paper is expected to provide scientific reference and technical support for urban flood disaster prevention and sponge city construction.

     

Integrated methodology for flood risk assessment and application in urban communities of Pakistan

Flood disasters and its consequent damages are on the rise globally. Pakistan has been experiencing an increase in flood frequency and severity along with resultant damages in the past. In addition to the regular practices of loss and damage estimation, current focus is on risk assessment of hazard-prone communities. Risk measurement is complex as scholars engaged in disaster science and management use different quantitative models with diverse interpretations. This study tries to provide clarity in conceptualizing disaster risk and proposes a risk assessment methodology with constituent components such as hazard, vulnerability (exposure and sensitivity) and coping/adaptive capacity. Three communities from different urban centers in Pakistan have been selected based on high flood frequency and intensity. A primary survey was conducted in selected urban communities to capture data on a number of variables relating to flood hazard, vulnerability and capacity to compute flood risk index. Households were categorized into different risk levels, such as can manage risk, can survive and cope, and cannot cope. It was found that risk levels varied significantly across the households of the three communities. Metropolitan city was found to be highly vulnerable as compared to smaller cities due to weak capacity. Households living in medium town had devised coping mechanisms to manage risk. The proposed methodology is tested and found operational for risk assessment of flood-prone areas and communities irrespective of locations and countries.     

Social vulnerability indices: a comparative assessment using uncertainty and sensitivity analysis

Social vulnerability indices have emerged over the past decade as quantitative measures of the social dimensions of natural hazards vulnerability. But how reliable are the index rankings? Validation of indices with external reference data has posed a persistent challenge in large part because social vulnerability is multidimensional and not directly observable. This article applies global sensitivity analyses to internally validate the methods used in the most common social vulnerability index designs: deductive, hierarchical, and inductive. Uncertainty analysis is performed to assess the robustness of index ranks when reasonable alternative index configurations are modeled. The hierarchical design was found to be the most accurate, while the inductive model was the most precise. Sensitivity analysis is employed to understand which decisions in the vulnerability index construction process have the greatest influence on the stability of output rankings. The deductive index ranks are found to be the most sensitive to the choice of transformation method, hierarchical models to the selection of weighting scheme, and inductive indices to the indicator set and scale of analysis. Specific recommendations for each stage of index construction are provided so that the next generation of social vulnerability indices can be developed with a greater degree of transparency, robustness, and reliability.     

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.     

Analysis of social vulnerability to hazards in China

To improve natural disaster management, it is important to recognize the variability of the vulnerable populations exposed to hazards and to develop location-based emergency plans accordingly. This paper presents a mathematical model to establish a model of social vulnerability index (SoVI), which includes 12 social variables, and the regional social vulnerability to natural hazards was formulated by them. Taking a city as statistical unit, the variability of vulnerability to natural hazards was explored among the 323 cities based on the SoVI. The results indicate that vulnerability is a location-based regional phenomenon, with the most vulnerable cities being located in the southwest of China and the eastern areas being generally less vulnerable. The results will be helpful for policy makers to formulate disaster management plans, which can be beneficial for people in more vulnerable areas who are responding to, coping with, and recovering from natural disasters.     

基于压力?状态?响应模型框架的城市地震综合易损性评价

为了科学评价城市地震灾害状况,降低城市易损性,基于压力-状态-响应模型框架,构建城市地震综合易损性评价指标体系,其中压力类、状态类、响应类指标分别为7、13、8项。应用熵权法确定了各评价指标的权重,提出基于云模型的城市综合易损性评价模型,并运用雷达图分析法实现城市内各个区综合易损性的相对高低。应用上述方法,对兰州市中心城区进行了震害综合易损性评价,结果表明:兰州市综合易损性等级偏向Ⅲ级,易损性中等,其中红古、安宁区的易损性程度较高,城关、七里河易损性程度较低;经济因素对各区域的易损性影响较大,通过对易损区域加强管理建设,提高城市的防震减灾能力。     

Assessment of physical vulnerability to agricultural drought in China

Food security has drawn great attention from both researchers and practitioners in recent years. Global warming and its resultant extreme drought events have become a great challenge to crop production and food price stability. This study aimed to establish a preliminary theoretical methodology and an operational approach for assessing the physical vulnerability of two wheat varieties (“Yongliang #4” and “Wenmai #6”) to agricultural drought using Environmental Policy Integrated Climate model (EPIC). Drought hazard index was set up based on output variables of the EPIC water stress (WS), including the magnitude and duration of WS during the crop-growing period. The physical vulnerability curves of two wheat varieties to drought were calculated by the simulated drought hazard indexes and loss ratios. And the curve’s effect on drought disaster risk was defined as A, B and C sections, respectively. Our analysis results showed that (a) physical vulnerability curves varied between two wheat varieties, which were determined by genetic parameters of crops; (b) compared with spring wheat “Yongliang 4#” winter wheat “Wenmai 6#” was less vulnerable to drought under the same drought hazard intensity scenario; (c) the wheat physical vulnerability curve to drought hazard displayed a S shape, suggesting a drought intensity–dependent magnifying or reducing effect of the physical vulnerability on drought disasters; (d) the reducing effect was mainly in the low-value area of vulnerability curve, whereas the magnifying effect was in the middle-value area, and the farming-pastoral zone and the Qinling Mountain–Huaihe River zone formed important spatial division belts.     

Assessment of social vulnerability to natural disasters: a comparative study

The purpose of this study is to examine and compare the methodologies being developed in assessing social vulnerability to natural disasters. Existing vulnerability literature shows that two methods have been used in developing social vulnerability indexes: (1) a deductive approach based on a theoretical understanding of relationships and (2) an inductive approach based on statistical relationships (Adger et al. in New indicators of vulnerability and adaptive capacity. Tyndall Centre for Climate Change Research, Norwich, 2004). Two techniques were also utilized in aggregating social vulnerability indicators: (1) a deductive approach using standardization techniques such as z scores or linear scaling (Wu et al. in Clim Res 22:255?C270, 2002; Chakraborty et al. in Nat Hazards Rev 6(1):23?C33, 2005) and (2) an inductive approach using data-reduction techniques such as factor analysis (Clark et al. in Mitig Adapt Strateg Glob Change 3(1):59?C82, 1998; Cutter et al. Soc Sci Quart 84(2):242?C261, 2003). This study empirically compares deductive and inductive index development and indicator aggregation methods in assessing social vulnerability to natural disasters in the Gulf of Mexico and Atlantic coastal areas. The aggregated social vulnerability index is used to examine a relationship with disaster losses in the Gulf of Mexico and Atlantic coastal areas. The results show that coastal counties with more vulnerability in terms of social achieved status are positively associated with disaster damages, while variations in the development of the index using deductive and inductive measurement approaches produce different outcomes.     

A multi-dimensional assessment of urban vulnerability to climate change in Sub-Saharan Africa

In this paper, we develop and apply a multi-dimensional vulnerability assessment framework for understanding the impacts of climate change-induced hazards in Sub-Saharan African cities. The research was carried out within the European/African FP7 project CLimate change and Urban Vulnerability in Africa, which investigated climate change-induced risks, assessed vulnerability and proposed policy initiatives in five African cities. Dar es Salaam (Tanzania) was used as a main case with a particular focus on urban flooding. The multi-dimensional assessment covered the physical, institutional, attitudinal and asset factors influencing urban vulnerability. Multiple methods were applied to cover the full range of vulnerabilities and to identify potential response strategies, including: model-based forecasts, spatial analyses, document studies, interviews and stakeholder workshops. We demonstrate the potential of the approach to assessing several dimensions of vulnerability and illustrate the complexity of urban vulnerability at different scales: households (e.g., lacking assets); communities (e.g., situated in low-lying areas, lacking urban services and green areas); and entire cities (e.g., facing encroachment on green and flood-prone land). Scenario modeling suggests that vulnerability will continue to increase strongly due to the expected loss of agricultural land at the urban fringes and loss of green space within the city. However, weak institutional commitment and capacity limit the potential for strategic coordination and action. To better adapt to urban flooding and thereby reduce vulnerability and build resilience, we suggest working across dimensions and scales, integrating climate change issues in city-level plans and strategies and enabling local actions to initiate a ‘learning-by-doing’ process of adaptation.     

Implementation of an integrated vulnerability and risk assessment model

An integrated vulnerability and risk assessment model (IVR) is proposed. The proposed model is a composite index that assesses the relationships among four critical components, namely exposure, hazard, vulnerability and capacities and measures, and how these can be used to illustrate the integrated risk and vulnerability situation of an area. These factors are assessed using individual variables. Fifty-four variables, objectively decided upon, were used to measure the contribution of each component factor. The general characteristics of vulnerability, risk, exposure and capacities and measures are well known; however, the relative importance of each variable and their inter-relatedness, in measuring risk and vulnerabilities, as demonstrated by the IVR; and how these in turn affect the impacts of natural hazards, are still debatable. The IVR though provides a valid, reliable and sensitive tool, which can be used to further explore these relationships. Through robust testing and application, subjectivity in the selection of variables can be reduced. Moreover, through the establishment of a database for data collection and storage, objectivity (reliability) can be achieved as well as, availability of the requisite data inputs. The sensitivity of the model allows for the quick identification of strategic action, which will ultimately lead to hazard loss reduction. The values yielded for each component factor can help decision-makers in the allocation of scarce developmental funds as well as identify trends in levels of risk, vulnerability, exposures and capacities and measures as well as determine areas where mitigation strategies are needed most.     

Social and economic vulnerability of coastal communities to sea-level rise and extreme flooding

This paper assesses the socioeconomic consequences of extreme coastal flooding events. Wealth and income impacts associated with different social groups in coastal communities in Israel are estimated. A range of coastal flood hazard zones based on different scenarios are identified. These are superimposed on a composite social vulnerability index to highlight the spatial variation in the socioeconomic structure of those areas exposed to flooding. Economic vulnerability is captured by the exposure of wealth and income. For the former, we correlate the distribution of housing stock at risk with the socioeconomic characteristics of threatened populations. We also estimate the value of residential assets exposed under the different scenarios. For the latter, we calculate the observed change in income distribution of the population under threat of inundation. We interpret the change in income distribution as an indicator of recovery potential.     

Assessing physical vulnerability in large cities exposed to flash floods and debris flows: the case of Arequipa (Peru)

Understanding the physical vulnerability of buildings and infrastructure to natural hazards is an essential step in risk assessment for large cities. We have interpreted high spatial resolution images, conducted field surveys, and utilized numerical simulations, in order to assess vulnerability across Arequipa, south Peru, close to the active El Misti volcano. The emphasis of this study was on flash floods and volcanic or non-volcanic hyperconcentrated flows, which recur on average every 3.5 years across the city. We utilized a geographic information system to embed vulnerability and hazard maps as a step to calculate risk for buildings and bridges along the Río Chili valley and two tributaries. A survey of ~1,000 buildings from 46 city blocks, different in age, construction materials, and land usage, provided architectural and structural characteristics. A similar survey of twenty bridges across the three valleys was based on structural, hydraulic, and strategic parameters. Interpretation of high spatial resolution (HSR) satellite images, which allows for quick identification of approximately 69 % of the structural building types, effectively supplemented field data collection. Mapping vulnerability has led us to pinpoint strategic areas in case of future destructive floods or flows. Calculated vulnerability is high if we examine structural criteria alone. We further consider physical setting with the most vulnerable city blocks located on the lowermost terraces, perpendicular or oblique to the flow path. Statistical analysis conducted on 3,015 city blocks, considering nine criteria identified from HSR images, indicated that building-type heterogeneity and the shape of the city blocks, along with building and street network density, are the most discriminant parameters for assessing vulnerability.     

Assessing landslide exposure in areas with limited landslide information

Landslide risk assessment is often a difficult task due to the lack of temporal data on landslides and triggering events (frequency), run-out distance, landslide magnitude and vulnerability. The probability of occurrence of landslides is often very difficult to predict, as well as the expected magnitude of events, due to the limited data availability on past landslide activity. In this paper, a qualitative procedure for assessing the exposure of elements at risk is presented for an area of the Apulia region (Italy) where no temporal information on landslide occurrence is available. Given these limitations in data availability, it was not possible to produce a reliable landslide hazard map and, consequently, a risk map. The qualitative analysis was carried out using the spatial multi-criteria evaluation method in a global information system. A landslide susceptibility composite index map and four asset index maps (physical, social, economic and environmental) were generated separately through a hierarchical procedure of standardising and weighting. The four asset index maps were combined in order to obtain a qualitative weighted assets map, which, combined with the landslide susceptibility composite index map, has provided the final qualitative landslide exposure map. The resulting map represents the spatial distribution of the exposure level in the study area; this information could be used in a preliminary stage of regional planning. In order to demonstrate how such an exposure map could be used in a basic risk assessment, a quantification of the economic losses at municipal level was carried out, and the temporal probability of landslides was estimated, on the basis of the expert knowledge. Although the proposed methodology for the exposure assessment did not consider the landslide run-out and vulnerability quantification, the results obtained allow to rank the municipalities in terms of increasing exposure and risk level and, consequently, to identify the priorities for designing appropriate landslide risk mitigation plans.     

The socioeconomic impact of climate-related hazards: flash flood impact assessment in Kuala Lumpur,Malaysia

Small-scale flash flood events are climate-related disasters which can put multiple aspects of the system at risk. The consequences of flash floods in densely populated cities are increasingly becoming problematic around the globe. However, they are largely ignored in disaster impact assessment studies, especially in assessing socioeconomic loss and damage, which can provide a significant insight for disaster risk reduction measures. Using a structured questionnaire survey, this study applied a statistical approach and developed a structural equation model (SEM) for assessing several socioeconomic dimensions including physical impacts, mobility disruption, lifeline facilities, health and income-related impacts. The study reveals that respondents have experienced a stronger impact on direct tangible elements such as household contents and buildings as well as direct intangible elements with β coefficients 0.703, 0.576 and 0.635, respectively, at p?<?0:001 level. The direct intangible impacts affect mobility disruption with β coefficients equal to 0.701 at p?<?0:001 level which then further cause adversity to income-generating activities with β 0.316 at significant p?<?0:001 as well. The overall model fit indices show highly acceptable scores of SRMR 0.068, RMSEA 0.055 and PClose 0.092. Thus, the SEM has successfully incorporated the socioeconomic dimensions of disaster impact and explained the impact phenomena reliably. This modeling approach will allow inclusion of various variables from different disciplines to assess hazard impact, vulnerability and resilience.