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Smallholder farmers in the Tigray region are highly vulnerable to climate change-induced shocks due to their heavy reliance on rain-fed agriculture. This study aims to assess the multidimensional livelihood vulnerability of smallholder farmers in the Tigray region to climate change using the framework provided by the Intergovernmental Panel on Climate Change (IPCC). The study used a mixed methods research design composed of qualitative and quantitative research methods. Data were collected from 120 randomly selected households, Focus Group Discussions (FGDs) and Key Informant Interviews (KIIs). The findings reveal that more than 30% of the Atsbi Womberta district and 28% of the Tahtay Koraro district are classified as highly vulnerable to climate change. In Atsbi, the primary contributing factor to the High Vulnerability Index (HVI) is exposure, accounting for approximately 37% (mean value: 0.579 ± 0.111), followed by adaptive capacity at 33% (0.523 ± 0.104), and sensitivity at 30% (0.467 ± 0.160). Similarly, in Tahtay Koraro, exposure is the dominant contributing factor, comprising 38% (mean value: 0.618 ± 0.176), followed by low adaptive capacity at 32% (0.553 ± 0.113), and sensitivity at 30% (0.524 ± 0.167). Both districts indicate low adaptive capacity and high exposure to climate variabilities. To address the high vulnerability of smallholder farmers to climate change in the Tigray region, policymakers must prioritize disaster risk management strategies. These strategies should aim to reduce exposure to climate variabilities and strengthen the adaptive capacity of farming households.

Fuzzy decision-making and analytic hierarchical processes are ubiquitously used to predict the seismic damage and vulnerability of building clusters. However, the factors affecting the seismic vulnerability of building structures are diversification, cognitive uncertainty, and complex fuzziness. To probe the impact of multiple fuzzy influencing factors on the vulnerability of regional buildings and the degree of membership between them, the development of a structural vulnerability prediction model based on fuzzy decision-making and a hierarchical system with multiple factors has strong theoretical and practical significance. This study proposes a novel method for rapidly predicting structural vulnerability based on a multivariate fuzzy membership index. Rapid fragility prediction models of fiv4e typical structures considering the multivariate fuzzy membership index are established. A new approach is proposed based on the relationship model between the empirical vulnerability index and seven fuzzy membership parameters. Five types of typical structural vulnerability index rapid prediction innovation models are developed. The new prediction model is compared and verified using the quantitative value of China's macrointensity standard and the structural seismic loss observation data (98,050 × 104 m2 and 995,000 buildings) of 213 typical earthquakes to establish an empirical vulnerability index belt model. The proposed prediction model comprehensively considers multiple fuzzy membership parameters and the empirical structural earthquake damage database. The model analysis and validation results indicate that the proposed model can be further used for the seismic damage evaluation of typical structures and rapid fragility prediction. [ABSTRACT FROM AUTHOR]

This paper examines the extent of vulnerability and resilience to fight against Covid-19 virus in India. The vulnerability indices are constructed for the domains of hospital infrastructure, demography, housing, and health for all 36 states and union territories. An overall vulnerability index is constructed as the weighted average of domain-specific indices. The results reveal that vulnerability to coronavirus varies significantly across the states. The hospital and health vulnerabilities contribute most to the overall vulnerability in each state. As on 29 March 2021, the cumulative corona cases are the highest in Maharashtra, followed by Kerala, Karnataka, and Andhra Pradesh. The resilience to fight against the virus is weak in India. The lockdown imposed in India has severely affected jobs and incomes. The government should enhance fiscal spending to strengthen the national resilience and administer safe vaccination program not only to stop the spread of virus but also bring life to the normal. [ABSTRACT FROM AUTHOR]

Mediterranean dune systems have undergone a large reduction in the last decades. The main factors involved in this process are urbanisation promoting an alteration of dune morphology and changes in plant communities. The most representative coastal dune systems of Sardinia have been selected as a study case and analysed to evaluate their environmental status, vulnerability, and the potential for dune restoration. Thirty coastal-dune systems, ranging from high natural sites to urbanised areas were analysed. A matrix of 35 variables × 30 sites was built to calculate the relationship among dune development (StaDun) and other indices related to the coastal dunes potential to host dunes (BeaPot), the conservation actions and management of coastal-dune systems (CoMan), and the anthropogenic pressure and the transgression capacity of the sand (SurLan). The values obtained for StaDun and Dune restoration potential index (DPR) were clustered. The results highlighted the relationship among StaDun, BeaPot and CoMan indices. The geomorphological and ecological characteristics determine the main factors that influence the presence, typology, and development of dunes in each site. Conversely, StaDun was weakly correlated to SurLan index. The DPR index allowed to discriminate the coastal dunes that required management actions. The first group included well-developed dune systems for which conservation and management actions were not necessary. The second one consisted of sites for which these previous actions and restoration measures were necessary. DPR index provides a tool useful to assess and classify coastal dune areas based on their potential for restoration, and to plan appropriate management actions. [ABSTRACT FROM AUTHOR]

Certain communities along the coast of Ketu South Municipality in south-eastern Ghana, remain vulnerable to coastal flood events from storm surges, high tidal waves, lagoon overflow, and heavy rainfall. However, the local conditions that make these communities vulnerable are poorly understood and knowledge on which communities are most vulnerable is lacking. This study improves the conceptual understanding of different dimensions of vulnerability that exist across the communities and the various levels of vulnerability that each exposed community exhibits. The study surveyed 354 household heads from selected flood-prone communities including Blekusu, Agavedzi, Salakope, Amutsinu, and Adina. The survey collected data on demographic, social, economic, physical, exposure, and adaptive capacity to flood hazards. The data was then used to construct composite vulnerability indices at community levels. Results from the study demonstrate that the communities have different levels of vulnerability as a result of differences in their exposure, sensitivity, and adaptive capacity levels. The willingness to relocate as an adaptation strategy was determined by household flood duration, number of livelihoods, and sea defence preference. These results are relevant to flood disaster management programs and the adoption of effective adaptation measures that take into account local knowledge. The findings imply that interventions aimed at reducing vulnerability should take into account household characteristics, as well as flood exposure, and adaptive capacity factors. [ABSTRACT FROM AUTHOR]

The dense settlements at the eastern hills of Rara Lake are at higher risk of existing landslides. Seepage of water from the lake has increased erosion rates, exaggerating the threats to villages. People are worried due to the potential of inadvertent disaster, therefore it became necessary to estimate the vulnerability of the communities and inform concerned authorities.Setting this requirement as an objective, underlying influencing indicators were assessed. The vulnerability assessment was based on the scoring of the responses emanated from indicator-based household's survey.These scores were summed up to generate indices and also mapped with their true locations. Vulnerability scores ranged from 16.50to 21.75 andwere categorized into five classes after standardization. A moderate vulnerability was exhibited by 33.08% of households sampled. High and very high categories of vulnerability occupied 18.80% and 4.51% of households, respectively. Field observation showed solitary households built away from village clusters were highly vulnerable. Most households showed moderate vulnerability and characteristics like stones/mud-built houses, firewood as a primary fuel, decreasing forests and grasslands, increasing temperatures, and decreasing rainfall were major influencing indicators for higher vulnerability in the research area.

The dense settlements at the eastern hills of Rara Lake are at higher risk of existing landslides. Seepage of water from the lake has increased erosion rates, exaggerating the threats to villages. People are worried due to the potential of inadvertent disaster, therefore it became necessary to estimate the vulnerability of the communities and inform concerned authorities. Setting this requirement as an objective, underlying influencing indicators were assessed. The vulnerability assessment was based on the scoring of the responses emanated from indicator-based household's survey. These scores were summed up to generate indices and also mapped with their true locations. Vulnerability scores ranged from 16.50 to 21.75 and were categorized into five classes after standardization. A moderate vulnerability was exhibited by 33.08% of households sampled. High and very high categories of vulnerability occupied 18.80% and 4.51% of households, respectively. Field observation showed solitary households built away from village clusters were highly vulnerable. Most households showed moderate vulnerability and characteristics like stones/mud-built houses, firewood as a primary fuel, decreasing forests and grasslands, increasing temperatures, and decreasing rainfall were major influencing indicators for higher vulnerability in the research area. [ABSTRACT FROM AUTHOR]

Bibliometric analysis is a quantitative evaluation method for scientific research aiming at measuring knowledge expressed as scientific publications in a given field. This paper proposes to analyze the worldwide scientific production on social vulnerability of coastal populations through six bibliometric indicators: typology, historical evolution, geographic distribution, main sources, relevant authors and publications and recurring keywords. The research theme was chosen given the continuous increase of studies related to climatic changes and their consequences to populations in coastal zones. In total, 191 indexed documents covering the period from 1991 to 2019 were selected from the Scopus database, after the examination of more than 900 entries, and analyzed through VOSViewer software and the Bibliometrix R package. The results obtained confirmed the exponential growth of scientific production on this subject. Most frequently impacts considered were coastal flooding and erosion triggered by extreme events and the majority of studies have been presented as academic articles published in scientific journals. Moreover, most documents identified were site-specific, based on secondary data and associated with authors from the USA and the UK, with an emerging production related to authors from developing economies in recent years. Among the 658 authors found, only nine have published three or more articles on the theme, with citations highly concentrated in only four publications. The analysis also revealed the evolution of preferred keywords over time and the lack of consensus in the use of terminology. Studies about coastal social vulnerability were initially mostly focused on the evaluation of risks and exposure to hazards, evolving over time such that the focus shifted to adaptation measures seeking to minimize impacts from climate change to coastal zones. [ABSTRACT FROM AUTHOR]

Composite indices are used to assess and prioritize mitigation and adaptation strategies for addressing the impacts of global environmental change. We evaluate different aggregation tools for creating these indices and their potential effects on mitigation and adaptation efforts. We assess the association of each aggregation tool with different types of trade-offs, risk strategies, and the resulting spatial and statistical distribution of their composite scores. Four aggregation tools are investigated (Weighted Linear Combination, WLC; Ordered Weighted Average, OWA; Data Envelopment Analysis, DEA; Compromise Programming, CP) using an example of vulnerability to flooding in the eastern United States. The choice of aggregation tool affects vulnerability outcomes, decision risk strategies, and the prioritization of vulnerability reduction strategies. DEA produces the highest vulnerability scores, representing a risk averse strategy associated with pessimistic outcomes. WLC implies a neutral and fixed risk strategy. CP produces a range of outcomes from neutral (equivalent to the WLC) to pessimistic, depending on its parameters. OWA offers the highest flexibility to adjust the levels of trade-off and risk strategy, producing a range of vulnerability outcomes, from optimistic to pessimistic. The units of analysis, when prioritized across the different aggregation tools, are more consistent for the top ranked units. However, the differences in rank become substantial as the selection threshold score decreases. To obtain better informed vulnerability reduction strategies, we recommend to (i) address how trade-off and decision risk are embedded in the aggregation tool chosen, and (ii) evaluate their effect in the prioritization of mitigation and adaptation strategies being considered. [ABSTRACT FROM AUTHOR]

In the actual scenario of progressive coastal occupation man-made infrastructure is increasingly threatened by natural hazards. As a consequence, in the last two decades different methodologies have been proposed to assess coastal vulnerability to the potential impacts of storm surges on developed areas. In this study, the susceptibility of sandy beaches to erosion was assessed by using an analytical approach based on geoindicators survey. This framework considers that a selected set of variables can express short-term environmental dynamics and be used, therefore, as proxies for the multiplicity of factors acting over coasts. Geoindicators are site-specific and rely on the description of coastal geomorphic features, both natural or man-induced. Santa Catarina State, located in southern Brazil, was selected as case study. Its shoreline contains beaches of different extents that alternate with headlands and a wide continental shelf on the adjoining Atlantic Ocean. It is regularly under influence of extra-tropical cyclones and other storm systems that frequently reach southern Brazil. Due to the occurrence of high energy episodes, damages resulting from short-term coastal erosion and inundation have been increasingly reported over the years. In this research, 302 points were surveyed during 40 days of field work and 32 geoindicators were considered representative of susceptibility. They were identified in the field, ranked in risk levels, weighted using AHP (Analytic Hierarchy Process) and tabulated, resulting in an index expressing local susceptibility in five progressive classes. In average, most of Santa Catarina sampled points were classified around intermediate degrees of susceptibility (High + Medium + Low = 82%), with a slight tendency to higher levels. Very Low levels of susceptibility were identified in 10% of the points, while Very High in 8%. Spatial distribution of data indicates that lower susceptibility values dominate in the south of the area while in the north prevails an alternating distribution of susceptibility classes, with a tendency to higher values. The different levels of coastal indentation along the state, a result of the regional geological setting, and the induced susceptibility resulting from sectors of dense human concentration close to the shore explain the observed pattern. The selected geoindicators were effective to evaluate the erosional propensity of Santa Catarina's sandy beaches, and allowed a relatively fast and low-cost approach for susceptibility assessment and monitoring analysis, with a potential practical use in coastal zone planning and management. [ABSTRACT FROM AUTHOR]

The objective of this work is to show the procedure used to develop the vulnerability map to the contamination of two important aquifer horizons, constituted by karstic stratum waters, in the southern western Cuba. The method of quantification of vulnerability is based on the electrical conductivity of the surface layers, through the use of indicators deduced by Kalinski, Röttger and others. The map shows that the vulnerability to pollution is high at the western end of the region, while for the main aquifer, associated with the Miocene limestones of the Paso Real formation, the vulnerability is mostly medium. [ABSTRACT FROM AUTHOR]

This paper provides an example for regional scale analysis of climate vulnerability incorporating environmental as well as socio-economic indicators. Researches have focused on different aspects of climate vulnerability so far, but usually there is little connection between the physical and social dimensions. Our study provides a more complex analysis, which builds on the application of international indices which have been used on the local and regional levels very rarely. In our research we combined physical and human geographical approaches and research techniques. The physical geographical assessment is based on indicators referring to ground water levels and vegetation production, while the human geographical side of the analysis focuses on economic and social sensitivity, adaptation and exposure indices, combined in the so-called socio-economic climate vulnerability index. In the analysis we tried to figure out the most sensitive areas in the Hungarian Southern Great Plain region. The main findings of the study are „hot spots" which coincide on both analyses, therefore, the most sensitive areas under current climate change conditions could be delimited. This study also demonstrates that the resolution of global climate change vulnerability indices is not suitable for regional scale analysis because of the significant territorial differences. Therefore, local or regional scale assessments are needed for the preparation of strategies for the elaboration of mitigation and adaptation policies. [ABSTRACT FROM AUTHOR]

Flood vulnerability indices for the Kelantan River sub-basins were developed from various flood-related variables. The vulnerability indices of the Kelantan River sub-basins involved flood depth-inundation area, soil erosion potential, and potential of soil for agricultural use, population vulnerability, road infrastructure vulnerability and market infrastructure vulnerability. These indices were developed from the use of Geographic Information System (GIS) technique. The result indicates that the flood vulnerability indices of sub-basins were mostly ranked high in the areas with high concentration of development activities and densely populated region with large infrastructure existence that are more flood-prone group than others especially in major metropolitan areas. In order to steer against probable damage caused by flood, it remains important to develop a tool that is most beneficial for river basin managers and policy makers, so that they can conduct vulnerability assessment and flood risk in term of human lives losses and property damages during future massive floods. The output of this study can guide decision makers to reduce flood risks Kelantan River basin in future. [ABSTRACT FROM AUTHOR]

The variation of the height of the columns in a storey of a multi-storeyed building increases their vulnerability to seismic forces. Assessment of seismic vulnerability of buildings can be carried out by various approaches. In this paper, an approach based on pushover analysis was used for generating vulnerability indices. The indices quantify the deficiencies in lateral load resistance and lateral drift of a building, storey drift, and the performance ranges of the hinges formed in the beams and columns. First, a regular mid-rise reinforced concrete building was analysed to evaluate the vulnerability indices. Next, the study investigated the effects of increased height of the open ground storey, foundations on sloping levels, split-level Hoors, and partial height infill walls in similar buildings. It was observed that the increase in vulnerability due to the variation of the height of the columns in a storey could be quantified by the indices for lateral load resistance, storey drift, and the performance of the columns in a storey. [ABSTRACT FROM AUTHOR]

Vulnerability to climate change is a product of biophysical and social dynamics. Assessments of community or regional vulnerability, however, often focus on quantitative infrastructure and environmental assessments, or qualitative assessments of a community’s social dynamics and livelihood activities. A dearth of integrated quantitative assessments is a major barrier for decision makers who require quantitative outputs and indicators, which can measure where vulnerability is most severe and can be linked to climate projections. Our framework and analysis helps address such gaps by identifying variables to build climate change vulnerability indices, which we pilot here focusing on Inuit communities in the Canadian Arctic. We start with a systematic literature review of community-based vulnerability studies and assess relationships among 58 social and biophysical variables. We then use multiplex network analysis to determine how social and environmental variables interact among and within the key component of vulnerability: exposure, sensitivity, and adaptive capacity. We identify several structurally important variables that interact within and across the three dimensions of vulnerability. This method is transferable as an integrative means of understanding not only the direct causes of vulnerability, but also relations that are less tangible. The approach of multiplex network analysis can be a building block to ongoing development of vulnerability indices within the human dimensions of climate change field.

Vuln-Indices Java-based software was developed on concepts of vulnerability to climate change of agro-ecological systems. It implements the calculation of vulnerability indices on series of state variables for assessments at both site and region levels. The tool is useful because synthetic indices help capturing complex processes and prove effective to identify the factors responsible for vulnerability and their relative importance. It is suggested that the tool may be plausible for use with stakeholders to disseminate information of climate change impacts. [ABSTRACT FROM AUTHOR]

There are several suspected sources of lead contamination in the Dominican Republic (DR) to which populations, to a greater or lesser extent, may be exposed. These sources include: a lead battery recycling plant, a gold mine and vehicles using leaded gasoline. In this paper we create and compare indices of spatial vulnerability using different index construction methods including: the weighted average, ordered weighted average, and Data Envelopment Analysis. The vulnerability attributes used to create these indices include: exposure to lead effluents in water from the gold mine as measured by distance from potentially contaminated water, point source lead air emissions from the battery recycling plant estimated by air plume analysis; and mobile source exposure to lead emissions from road transportation measured by potential traffic impacts. The intensities of vulnerability to lead of the towns and cities in the DR, produced by each of the different index construction methods, are compared and evaluated. [ABSTRACT FROM AUTHOR]

Abstract: Aggregate measures that capture multiple aspects of socio-ecological vulnerability in a single or small number of vulnerability indices can produce vulnerability maps that act as powerful visual tools to identify those areas most susceptible to future environmental changes. Such indices are easily communicable and offer valuable guidance to policymakers and investors, providing insights as to where more targeted research or policy interventions can address current challenges and reduce future risks. However, such aggregation inevitably reduces the richness of information provided by the suites of individual vulnerability indicators on which the maps are based. This trade-off between information richness and information communicability is a challenge in the quantification and communication of complex phenomena such as socio-ecological vulnerability. This paper investigates the use of Principal Component Analysis (PCA) techniques as a means of creating information-rich spatially-explicit aggregate indices of socio-ecological vulnerability. We present a ‘proof of concept’ analysis of socio-ecological vulnerability for the Southern Africa Development Community (SADC) region using both PCA and traditional normalization based techniques for generating spatially explicit, aggregated socio-ecological vulnerability indices. The vulnerability indices are based on published biophysical and socio-economic data and mapped at a 10 arc minute resolution. The resulting PCA based vulnerability maps indicate the regional spatial variability of four statistically independent, unique components of socio-ecological vulnerability, providing more information than the single index produced using a normalization/summation approach. Such uncorrelated, information-rich vulnerability indices represent a potentially useful policy tool for identifying areas of greatest concern in terms of both the relative level, and the underlying causes and impacts of, socio-ecological vulnerability to environmental changes across broad spatial scales. [Copyright &y& Elsevier]

Ice flashover faults (IFFs) that occur in groups can be a key factor in grid collapse. This study analyzed IFF characteristics and developed a basic risk assessment model. The aim is to reveal the IFF inherent law, and provides a direction for the future ice storms. Moreover, IFF risk model is the basis of risk assessment of power grid during ice storms. The critical values of ice bridging and shedding from insulators were identified. A state division principle categorized the IFF modes. A risk rating method then developed, based on these IFF modes. In view of the limited experience data with small sample size and many important inputs, the least squares support vector machines risk modeling method was adopted and its model parameters optimized by Bayesian inference. In reduction to practice, some vulnerability indices are suggested to analyze the risk of grid IFFs for future ice storms. [ABSTRACT FROM AUTHOR]

This paper states research of traditions to develop and analyze vulnerability indices, a compendium variety related to vulnerability indices, theoretical approaches, to natural hazards developed up to date. The paper focuses on vulnerability indices progression and the new wave directions of different scholars to develop an unflinching method, through managing social, economic, environmental, physical and institutional components all together; using variable indicators is a tempting prospect for the future, but the quantification of vulnerability in general and social vulnerability in special has to focus on wise-minded approach, overall, vulnerability index to natural hazards. [ABSTRACT FROM AUTHOR]

Populations around the world are vulnerable to natural disasters. Such disasters are occurring with increased frequency as a consequence of socio-economic and land-use developments and due to increased climate variability. This paper describes a methodology for using indicators to compute a Flood Vulnerability Index which is aimed at assessing the conditions which influence flood damage at various spatial scales: river basin, sub-catchment and urban area. The methodology developed distinguishes different characteristics at each identified spatial scale, thus allowing a more in-depth analysis and interpretation of local indicators. This also pinpoints local hotspots of flood vulnerability. The final results are presented by means of a standardised number, ranging from 0 to 1, which symbolises comparatively low or high flood vulnerability between the various spatial scales. The Flood Vulnerability Index can be used by international river basin organisations to identify and develop action plans to deal with floods and flooding or on smaller scales to improve local decision-making processes by selecting measures to reduce vulnerability at local and regional levels. In this work the methodology has been applied to various case studies at different spatial scales. This leads to some interesting observations on how flood vulnerability can be reflected by quantifiable indicators across scales, e.g. the relationship between the flood vulnerability of a sub-catchment with its river basin or the weak relation between the flood vulnerability of an urban area with the sub-catchment or river basin which it belongs to [ABSTRACT FROM AUTHOR]

• Vulnerability curves may overestimate loss for some events. • Vulnerability indices complement vulnerability curves giving better insights into the interaction between a building and a physical process. • Process intensity is a key variable for the assessment of physical vulnerability. • Indices should be constantly updated using data from upcoming events and a wider indicator inventory. • Sensitivity analysis of some variables is a valuable support for improved damage and event documentation. Vulnerability analysis is crucial to assess natural hazard risk. Methods for vulnerability assessment include indices as well as vulnerability curves. Vulnerability curves make use of empirical data to show the relationship between the process intensity and the resulting degree of loss on each affected building whereas vulnerability indices are based on a number of indicators representing building characteristics and their surroundings. In the present paper, damage data from two relatively recent torrential events in the European Alps are used to compare results using a vulnerability curve (Beta model) and a physical vulnerability index (PVI). Following the application of both methods, their strengths and weaknesses are outlined. Vulnerability curves constitute a valuable quantitative method for the assessment of physical vulnerability but, in the present study, they tend to overestimate damages. On the other hand, vulnerability indices better support the understanding of local-scale damage patterns but they require detailed data and further research on weighting and indicator selection. The study leads to the conclusion that both methods complement each other providing better insights into the physical vulnerability of buildings exposed to torrential hazards. Furthermore, uncertainties associated with the two approaches are related to the required data. Therefore, a sensitivity analysis is carried out showing that process intensity is a key variable for the assessment of vulnerability, whereas, differences in the calculation of the degree of loss based on different building values are less important. Finally, the paper gives clear recommendations for improved event and damage documentation and provides an outlook on future needs in vulnerability assessment, including constant updating of both methods based on recent events. [ABSTRACT FROM AUTHOR]

Vulnerability assessment is a requirement of NERC's cybersecurity standards for electric power systems. The purpose is to study the impact of a cyber attack on supervisory control and data acquisition (SCADA) systems. Compliance of the requirement to meet the standard has become increasingly challenging as the system becomes more dispersed in wide areas. Interdependencies between computer communication system and the physical infrastructure also become more complex as information technologies are further integrated into devices and networks. This paper proposes a vulnerability assessment framework to systematically evaluate the vulnerabilities of SCADA systems at three levels: system, scenarios, and access points. The proposed method is based on cyber systems embedded with the firewall and password models, the primary mode of protection in the power industry today. The impact of a potential electronic intrusion is evaluated by its potential loss of load in the power system. This capability is enabled by integration of a logic-based simulation method and a module for the power flow computation. The IEEE 30-bus system is used to evaluate the impact of attacks launched from outside or from within the substation networks. Countermeasures are identified for improvement of the cybersecurity. [ABSTRACT FROM AUTHOR]

Most previously developed coastal vulnerability/sensitivity indices acknowledge that the addition of socioeconomic variables would assist in defining vulnerable areas. This study investigated the incorporation of socioeconomic variables into a GIS based coastal vulnerability index for wave-induced erosion in Northern Ireland. In this application, a socio-economic sub-index was developed to contribute potentially one third of the overall index score; the other components consisted of coastal forcing and coastal characteristic sub-indices. All variables were ranked on an arbitrary 1-5 scale with 5 being most vulnerable. The variables were merged within sub-indices and then the sub-indices were combined to produce the overall index. Several problems were encountered in assessing socio-economic vulnerability indicators. These relate to the inherent difficulties involved in ranking socio-economic data on an interval scale. Temporal aspects also caused difficulties as socio-economic variables vary over time as coastal populations and policies change. There were also problems in relation to the size of the unit used to display the data and how this affected the vulnerability of certain areas. Larger, more fundamental, problems in relation to human perceptions of vulnerability were also investigated. The final results of the combined index were tested against field and desk-top studies and although they correlated well with expected outcomes, the results did suggest an under representation of the socio-economic index. Suggestions are put forward to alleviate this problem in any future developments. [ABSTRACT FROM AUTHOR]