Socioeconomic vulnerability and electric power restoration timelines in Florida: the case of Hurricane Irma

Large-scale damage to the power infrastructure from hurricanes and high-wind events can have devastating ripple effects on infrastructure, the broader economy, households, communities, and regions. Using Hurricane Irma’s impact on Florida as a case study, we examined: (1) differences in electric power outages and restoration rates between urban and rural counties; (2) the duration of electric power outages in counties exposed to tropical storm force winds versus hurricane Category 1 force winds; and (3) the relationship between the duration of power outage and socioeconomic vulnerability. We used power outage data for the period September 9, 2017–September 29, 2017. At the peak of the power outages following Hurricane Irma, over 36% of all accounts in Florida were without electricity. We found that the rural counties, predominantly served by rural electric cooperatives and municipally owned utilities, experienced longer power outages and much slower and uneven restoration times. Results of three spatial lag models show that large percentages of customers served by rural electric cooperatives and municipally owned utilities were a strong predictor of the duration of extended power outages. There was also a strong positive association across all three models between power outage duration and urban/rural county designation. Finally, there is positive spatial dependence between power outages and several social vulnerability indicators. Three socioeconomic variables found to be statistically significant highlight three different aspects of vulnerability to power outages: minority groups, population with sensory, physical and mental disability, and economic vulnerability expressed as unemployment rate. The findings from our study have broader planning and policy relevance beyond our case study area, and highlight the need for additional research to deepen our understanding of how power restoration after hurricanes contributes to and is impacted by the socioeconomic vulnerabilities of communities.     

Soil sealing,population structure and the socioeconomic context: a local-scale assessment

In the most recent decades European urban regions underwent functional changes reflecting heterogeneous land-use patterns and specific urban footprints. Several mono-centric cities shifted towards a scattered development with impact on the socio-spatial structure. Discontinuous expansion determined, in some cases, a net increase in land consumption. Using a multivariate exploratory approach, the present study analyzes the spatial relationships between 14 morphological variables and 22 socioeconomic indicators in Rome’s province. The aim of this study was to identify the demographic and socioeconomic indicators most associated to the transition from a mono-centric and semi-compact morphology towards a more dispersed settlement structure based on different sealing profiles observed at the local scale. Four groups of socioeconomic indicators (population structure, job market, economic specialization and settlement characteristics) associated to different sealing profiles (low, medium and high imperviousness) were identified and local municipalities classified accordingly. Although the urban–rural axis maintains an important role in the spatial organization of Rome’s province, other variables were found associated to areas with moderately low imperviousness, evidencing a specific demographic structure and persisting socioeconomic disparities at the base of the settlement model observed at the regional scale.     

Social vulnerability assessment to seismic risk using multicriteria analysis: the case study of Vila Franca do Campo (S?o Miguel Island, Azores, Portugal)

The increase in the frequency and magnitude of disasters triggered by earthquakes in different regions of the Earth is a major challenge to contemporary societies. The awareness that disasters and risk are processes structured on spatial?Ctemporal interactions maintained at the social-ecological system between the natural hazards and the vulnerabilities of socioeconomic, political and physical nature becomes utterly important in the increase of social systems?? resilience. Thus, the assessment of social vulnerability plays a decisive role in understanding the factors that distinguishes individuals, households and communities, in terms of their ability to anticipate, cope with, resist to and recover from the impact of disasters triggered by natural hazards. This article presents a geographic information system (GIS)-based approach model to assess the social vulnerability to seismic risk using multicriteria analysis (MCA) techniques, in a group decision-making process. The methodology applied to the municipality of Vila Franca do Campo (S?o Miguel Island, Azores, Portugal) identified moderate social vulnerability values at the neighbourhood level and higher social vulnerability values for the built environment and demographic characteristics of the social groups. The social vulnerability patterns make a clear distinction between the older/historical urban cores and the new urban areas. In the first case, the presence of ancient buildings constructed with materials of low resistance to earthquakes coupled with a higher population density and the traits of demographic and socioeconomic frailties of the social groups, results in higher vulnerability values. This pattern is common in the historic centre of S. Miguel district, Ribeira das Taínhas, northern areas of água de Alto and western and eastern neighbourhoods of Ponta Gar?a. The new urban areas, mainly found in S. Pedro, central areas of água de Alto, S. Miguel and Ponta Gar?a districts, have lower values of social vulnerability due to changes in the built, demographic and socioeconomic environments. Results recommend the integration of social vulnerability indexes into seismic risk mitigation policies and emergency management planning.     

Permanent versus temporary rural migrants in Riyadh,Saudi Arabia

"The aim of this paper is to investigate the factors affecting intentions of rural-migrants to return to their rural origins. Several socioeconomic, demographic, spatial, and temporal variables will be introduced to explore their explanatory power and interrelationship with the migrants' intentions. These variables are: Years lived in Riyadh, the current place of parents' residency, land ownership in the village, home ownership in the urban area, income, household size, and the area of origin. The data, which come from a sample survey of migrants conducted in Riyadh in 1983, will be analyzed by the means of binary logit model."     

Importance of soil and elevation characteristics for modeling hurricane-induced power outages

Hurricanes can severely damage the electric power system, and therefore, predicting the potential impact of an approaching hurricane is of importance for facilitating planning and storm-response activities. A data mining approach, classification and regression trees (CART), was employed to evaluate whether the inclusion of soil and topographic variables improved the predictive accuracy of the power outage models. A total of 37 soil variables and 20 topographic variables were evaluated in addition to hurricane, power system, and environmental variables. Hurricane variables, specifically the maximum wind gust and duration of strong winds, were the most important variables for predicting power outages in all models. Although the inclusion of soil and topographic variables did not significantly improve the overall accuracy of outage predictions, soil type and soil texture are useful predictors of hurricane-related power outages. Both of these variables provide information about the soil stability which, in turn, influences the likelihood of poles remaining upright and trees being uprooted. CART was also used to evaluate whether environmental variables can be used instead of power system variables. Our results demonstrated that certain land cover variables (e.g., LC21, LC22, and LC23) are reasonable proxies for the power system and can be used in a CART model, with only a minor decrease in predictive accuracy, when detailed information about the power system is not available. Therefore, CART-based power outage models can be developed in regions where detailed information on the power system is not available.     

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.     

Forecasting hurricane-induced power outage durations

Accurate estimates of the duration of power outages caused by hurricanes prior to landfall are valuable for utility companies and government agencies that wish to plan and optimize their restoration efforts. Accurate pre-storm estimates are also important information for customers and operators of other infrastructures systems, who rely heavily on electricity. Traditionally, utilities make restoration plans based on managerial judgment and experience. However, skillful outage forecast models are conducive to improved decision-making practices by utilities and can greatly enhance storm preparation and restoration management procedures of power companies and emergency managers. This paper presents a novel statistical approach for estimating power outage durations that is 87 % more accurate than existing models in the literature. The power outage duration models are developed and carefully validated for outages caused by Hurricanes Dennis, Katrina, and Ivan in a central Gulf Coast state. This paper identifies the key variables in predicting hurricane-induced outage durations and their degree of influence on predicting outage restoration for the utility company service area used as our case study.     

Spatio-temporal distributions of climate disasters and the response of wheat yields in China from 1983 to 2008

Climate disasters are now on the rise and more likely to increase in frequency and/or severity under climate change in the future. To clearly illustrate spatial–temporal distributions of climate disasters and the response of wheat yields to disasters over the past three decades, several disaster indices including the impact of climate disasters, the sensitivity to climate disasters and the response index of wheat yield losses to climate disasters were defined and calculated. The impact and sensitivity indices were examined by the agricultural production losses due to climate disasters, and the response of wheat yields to climate disasters was assessed by wheat yield loss compared with the 5-year moving average. The results showed that the indices of climate disaster impacts and sensitivities as well as response index of wheat yields to climate disasters could represent the spatial–temporal distributions of climate disasters well in the whole China. Droughts in northern China had higher impacts and sensitivities than those in southern China during the period 1983–2008, but the impacts of floods were opposite. In northern China, although impacted area by drought was larger than that by flood, the flood sensitivities were larger than drought sensitivities when flood happened. Although drought significantly affected wheat yields in most of the regions with drier conditions during 1983–2008 in major wheat-producing regions, better management practices like irrigation and drought-tolerant cultivars applied in the Huang-Huai-Hai Plain can adapt to climate disasters especially droughts. To ensure the stability of agricultural production, future food security will need to be achieved through quantifying the relative effects of climate disasters and effective adaptation to increasingly frequent extreme climate events.     

Household response to cyclone and induced surge in coastal Bangladesh: coping strategies and explanatory variables

The purpose of this research is to explore indigenous coping strategies and identify underlying demographic, socio-economic and other relevant variables that influence the adoption of coping strategies in three distinct cyclone-prone coastal villages of Bangladesh. The study finds that cyclones and induced surges are a recurrent phenomenon in coastal Bangladesh; hence people are used to adjusting their lifestyle and adopting their own coping strategies intelligently. Adoption of a particular set of coping strategies depends not only on the magnitude, intensity and potential impacts of the cyclone and induced surge, but also age, gender, social class, dissemination of early warning information, locational exposure, external assistance, social protection and informal risk sharing mechanisms within the community. Indigenous cyclone disaster prevention and mitigation strategies significantly minimize the vulnerability of the people. Under extreme situations, when such disasters surpass the shock-bearing capacity of the victims, informal risk sharing mechanisms through social bonding and social safety-nets become vital for short-term survival and long-term livelihood security. Therefore, proper monitoring and understanding of local indigenous coping strategies are essential in order to target the most vulnerable groups exposed to disasters. Additionally, proper dissemination of early warning and government and non-government partnerships for relief and rehabilitation activities should be prioritized to ensure pro-poor disaster management activities. The study also recommends effective monitoring of the impact of aid to ensure corrective measures to avoid the development of relief dependency by disaster victims.     

基于灾情数据的新疆雪灾的评估与区划

选取1955-2017年新疆因雪灾造成的牲畜受灾数量、作物受灾面积、经济损失三大灾情数据,揭示新疆雪灾时间和空间分布特征,通过构建雪灾灾损指数,对新疆雪灾进行区划。分析表明：新疆雪灾的发生北疆多于南疆,山区多于盆地,西部多于东部,主要集中发生在阿尔泰山区、天山山区及昆仑山区,灾情最重的是阿勒泰地区、伊犁地区、塔城地区;进入2000年以后,雪灾呈现明显高位震荡特点;利用多指标综合评估法,运用连续型随机变量分布密度近似求法,求得的新疆雪灾灾损指数,能客观反映新疆雪灾灾情;雪灾灾损指数遵从Γ分布,根据Γ分布函数属性及各类雪灾事件发生概率,进行了新疆雪灾等级区划。研究成果可为决策服务及气候可行性论证提供理论依据,对科学准确地制定防灾备灾措施、及时组织开展雪灾应急救助工作以及灾后的恢复重建决策给予一定参考。     

Identifying population vulnerable to hydrological hazards in San Juan, Puerto Rico

The hazards of place framework developed by Cutter (1996) has been applied to several areas across the United States. This article tests the applicability of that model for analysis of hydrological disasters in the municipio of San Juan, Puerto Rico. San Juan is chosen because it combines many socioeconomic attributes of a developing area while offering data availability befitting its status as a US commonwealth. The interoperability of principal components and arithmetically based methods for producing a social vulnerability layer are examined. For both methods, a basket of commonly cited demographic variables representing social and economic vulnerability is extracted from Census 2000 sample (SF-3) data at the census block-group level of analysis. These results provide insight on the strengths and weaknesses of the methods both methodologically and regarding policy implementation. A look at the neighborhood of La Perla suggests complex local positive and negative effects of local processes on vulnerability not captured by demographic analysis. These effects relate to possible census undercounts in peripheral areas and uncaptured coping ability provided by social networks.     

Atmospheric Hazards Preparedness in Bangladesh: A Study of Warning,Adjustments and Recovery from the April 1991 Cyclone

In probabilistic terms, Bangladesh is prone, to at least one major 'tropical cyclone' every year. This situation is primarily due to the geographical location of Bangladesh in tropical Asia, and to its concave coastline and shallow continental shelf. The devastating impact of such cyclones on humans stems from a combination of intense human occupation of the area, predominance of traditional sociocultural values and religion, the precarious socioeconomic conditions of the majority of the coastal inhabitants, and the lack of a coordinated institutional disaster planning and management strategy. Bangladesh has experienced several catastrophic environmental disasters during the last decade; among these events, the 1991 April cyclone was the most catastrophic in terms of both physical and human dimensions.An initial study was carried out in the coastal regions of Bangladesh less than two weeks after they were hit by the severe cyclone of 29 April 1991. This research examined the process through which warning of the impending disastrous cyclone was received by the local communities and disseminated throughout the coastal regions of Bangladesh. It was found that the identification of the threatening condition due to atmospheric disturbance, the monitoring of the hazard event, and the dissemination of the cyclone warning were each very successful. The present study followed up on the initial research by surveying 267 respondents with an elaborate survey instrument, focusing on the most crucial academic and planning issues identified in the 1991 study. In particular, the nature and characteristics of the cyclone preparedness of the coastal inhabitants were assessed by the study; other factors considered included rural-urban variations, mainland-island differences, the nature and role of previous knowledge, and the disaster experience.The survey results show the variety of indigenous adjustment mechanisms that help to rehabilitate the survivors; also visible are the profound roles played by the social inequality variables and the magnitude of physical vulnerability in influencing the disaster loss and recovery process. The study recommends that hazard mitigation policies should be integrated with national economic development plans and programs. Specifically, it is suggested that the cyclone warning system should incorporate the human response to warnings as its constituent part, and in this way accommodating human dimensions in its operational design.     

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.

     

School vulnerability to disaster: examination of school closure,demographic, and exposure factors in Hurricane Ike’s wind swath

Damage and destruction to schools from climate-related disasters can have significant and lasting impacts on curriculum and educational programs, educational attainment, and future income-earning potential of affected students. As such, assessing the potential impact of hazards is crucial to the ability of individuals, households, and communities to respond to natural disasters, extreme events, and economic crises. Yet, few studies have focused on assessing the vulnerability of schools in coastal regions of the USA. Using Hurricane Ike’s tropical storm wind swath in the State of Texas as our study area, we: (1) assessed the spatial distribution patterns of school closures and (2) tested the relationship between school closure and vulnerability factors (namely physical exposure and school demographics) using zero-inflated negative binomial regression models. The regression results show that higher probabilities of hurricane strikes, more urbanized school districts, and school districts located in coastal counties on the right side of Ike’s path have significant positive associations with an increase in the number of school closure days. Socioeconomic characteristics were not significantly associated with the number of days closed, with the exception of proportion of Hispanic youth in schools, a result which is not supported by the social vulnerability literature. At a practical level, understanding how hurricanes may adversely impact schools is important for developing appropriate preparedness, mitigation, recovery, and adaptation strategies. For example, school districts on the right side of the hurricane track can plan in advance for potential damage and destruction. The ability of a community to respond to future natural disasters, extreme events, and economic crises depends in part on mitigating these adverse effects.     

Spatial prediction of urban landslide susceptibility based on topographic factors using boosted trees

As global warming accelerates, abnormal weather events are occurring more frequently. In the twenty-first century in particular, hydrological disruption has increased as water flows have changed globally, causing the strength and frequency of hydrological disasters to increase. The damage caused by such disasters in urban areas can be extreme, and the creation of landslide susceptibility maps to predict and analyze the extent of future damage is an urgent necessity. Therefore, in this study, probabilistic and data mining approaches were utilized to identify landslide-susceptible areas using aerial photographs and geographic information systems. Areas where landslides have occurred were located through interpretation of aerial photographs and field survey data. In addition, topographic maps generated from aerial photographs were used to determine the values of topographic factors. A frequency ratio (FR) model was utilized to examine the influences of topographic, soil and vegetation factors on the occurrence of landslides. A total of 23 variables that affect landslide frequency were selected through FR analysis, and a spatial database was constructed. Finally, a boosted tree model was applied to determine the correlations between various factors and landslide occurrence. Correlations among related input variables were calculated as predictor importance values, and sensitivity analysis was performed to quantitatively analyze the impact of each variable. The boosted tree model showed validation accuracies of 77.68 and 78.70% for the classification and regression algorithms using receiver operating characteristic curve, respectively. Reliable accuracy can provide a scientific basis to urban municipalities for policy recommendations in the management of urban landslides.     

Infrastructure failure interdependencies in extreme events: power outage consequences in the 1998 Ice Storm

This paper addresses the problem of interdependent failures of critical infrastructures in disasters. Disruptions to critical infrastructure systems such as electric power or transportation frequently cause major social and economic loss in disasters, both directly and through failures in one system leading to or compounding disruptions in another. Strategic approaches regarding infrastructure failures are needed to guide community mitigation and preparedness efforts. This paper defines and provides a conceptual framework for investigating infrastructure failure interdependencies (IFIs) from the standpoint of societal impacts. In order to identify empirical patterns, a unique database has been developed of IFIs observed in major electric power outage events. This paper presents analysis of this data for a major Canadian disaster, the 1998 Ice Storm that affected the northeastern region of the country. The analysis identifies IFIs due to power outage caused by the storm that are of greatest societal concern. These represent potential foci for effective, targeted pre-disaster mitigation and preparedness efforts. The framework and approach are broadly applicable across a range of natural and human-induced hazards.     

Mapping soil erodibility from composed data set in Sele River Basin, Italy

Evaluation of soil erodibility is an important task for Mediterranean lands, in which fertility and crop yield are significantly affected by soil erosion. The soil physicochemical parameters affecting soil erodibility are highly variable in space and, as for many other environmental variables, sample measurements are generally not enough for assessing its spatial variability with an acceptable level of uncertainty at the scales of practical interest. This study illustrates the procedure applied for estimating the pattern of soil erodibility across the Sele Basin (Southern Italy), where soil properties have been measured on a limited number of sparse samples. Sampled data were integrated with other sparse data estimated by local regression functions, which relate soil erodibility to auxiliary variables, such as terrain attributes and land system class memberships. Sampled and estimated data were merged in a composed data set to assess the spatial pattern of soil erodibility by ordinary kriging. The proposed approach offers effective spatial predictions, and it is exportable to regions where financial costs for soil sampling are not feasible.     

地球化学场时-空结构分析的方法体系

地球化学场可定义为地球化学变量在各种尺度的区域上的分布,地球化学场是各种地质地球化学作用的对象和空间载体。成矿作用及其他各类地球化学过程都可理解为地球化学场空间结构随时间的演化,即地球化学场的时－空结构。本文把地球化学场时－空结构分析厘定为一维时－空序列的分析,二维场空间结构分析,三维场空间结构分析和数值矿床模型,时－空结构的动力学分析等４部分内容,并讨论了各自的分析方法。     

Perspectives of Natural Disasters in East and South Asia,and the Pacific Island States: Socio-economic Correlates and Needs Assessment

The regions of East and South Asia, and the Pacific Islands are among the most-hazardprone areas in the world. Because of this, during the last century, most of the humancasualties of `natural-triggered' disasters have taken place in this region. This circumstance therefore has become a major global humanitarian concern. Another major concern, specifically for the donor agencies, is the damage sustained by infrastructure resulting from environmental disasters. These recurrent loses take away a significant proportion of the cumulative economic gains accrued from development investments over many years.Stepwise multiple regression results substantiated the fact that many of the socio-economic and demographic variables significantly influence disaster-related deaths and injuries in this part of the world. A comparative temporal analysis has shown that, over the past two decades, demographic variables have become prominent predictors of disaster-loss in South, Southeast and East Asian and the Pacific states.Many countries of the region are lagging behind in understanding and recognizing thebroader scope of disaster mitigation and management. Emerging needs and awarenessamong the decision-makers and the general public, however, have prompted institutionsin many countries to initiate a critical review of the prevailing approaches. Thecountry-specific disaster-management capacities and needs in the region vary widely.There are many differences in historical courses, institutional and administrative settings, sociocultural characteristics, as well as political and economic systems. Development of a common institutional framework for the region, therefore, seems unfeasible. Based upon a regional review, it has become clear that the research calls for improving the understanding of the significance of disaster mitigation and management in light of sustainable development and the emerging global issues. In addition, aspects of human resource development to enhance institutional mitigation and response capacities are emphasized.     

Risk analysis and influencing factors of drought and flood disasters in China

The risk analysis of flood and drought disasters and the study of their influencing factors enhance our understanding of the temporal and spatial variation law of disasters and help identify the main factors affecting disasters. This paper uses the provincial administrative region of China as the research area. The proportion of the disaster area represents the degree of the disaster. The statistical distribution of the proportions was optimized from 10 alternative distributions based on a KS test, and the disaster risk was analyzed. Thirty-five indicators were selected from nature, agriculture and the social economy as alternative factors. The main factors affecting flood and drought disasters were selected by Pearson, Spearman and Kendall correlation coefficient test. The results demonstrated that the distribution of floods and drought is right-skewed, and the gamma distribution is the best statistical distribution for fitting disasters. In terms of time, the risk of flood and drought disasters in all regions showed a downward trend. Economic development and the enhancement of the ability to resist disasters were the main reasons for the change in disasters. Spatially, the areas with high drought risk were mainly distributed in Northeast and North China, and the areas with high flood risk were mainly distributed in the south, especially in Hubei, Hunan, Jiangxi and Anhui. The distribution of floods and drought disasters was consistent with the distribution characteristics of precipitation and water resources in China. Among the natural factors, precipitation was the main factor causing changes in floods and drought disasters. Among the agricultural and socioeconomic factors, the indicators reflecting the disaster resistance ability and regional economic development level were closely related to flood and drought disasters. The research results have reference significance for disaster classification, disaster formation mechanisms and flood and drought resistance.