Vulnerability Assessment Process Research Articles

Modal-based fragility analysis of high-rise tubular structures: A methodology for vulnerability assessment

This study addresses the limitations of current vulnerability assessment processes for tall buildings, which fail to incorporate the effects of higher modes and the resulting structural vulnerability to seismic hazards. Additionally, the extensive computational resources required for assessing tubular high-rise buildings make vulnerability assessments almost impossible. This study proposes a new methodology for assessing the modal-based structural vulnerability of high-rise reinforced concrete (RC) tubular buildings by incorporating nonlinear response and reducing computational effort. The proposed methodology discreetly develops the vulnerability information of each structural vibrational mode separately using nonlinear time history analysis rather than the linear Modal Response Spectrum Analysis (MRSA). The methodology includes steps for establishing vulnerability information for high-rise tubular buildings, and a case study of a 55-story RC building with core wall is presented to demonstrate the methodology. The vibrational modes of the building were decoupled and analyzed separately using single degree of freedom (SDOF) systems, and fragility curves were developed for three different limit states using various intensity measures. The obtained fragility relationships were compared with the curves of another structure of similar class. The results indicated good compatibility and significance of incorporating higher vibrational modes in assessment of structural vulnerability, thus, proposed methodology can be extended to any structural configuration of tubular buildings.

The role of vulnerability assessments in USA agricultural animal operations

Major disaster events such as hurricanes, floods, fires, earthquakes and tornadoes pose significant challenges to agricultural production every year. Commercial livestock and poultry operations are highly dependent on favourable environment, weather conditions and infrastructure to thrive. Adverse conditions during extreme weather events and other emergencies can result in significant loss of animals and commodities due to disruptions in utilities and critical services, facility damage, contamination of feed and water supplies, environmental extremes and biosecurity lapses. The effects on production can be long lasting and cumulative. Being able to identify, assess and mitigate potential vulnerabilities that lower risk helps organisations to prepare for and recover from these events. This paper provides an overview of the vulnerability assessment process in the United States that focuses on general and better practices that should be considered when applying these principles to commercial livestock and poultry operations. This approach has broad advantages for all countries where livestock and agriculture are exposed to these risks.

Flood damage and shutdown times for industrial process facilities: a vulnerability assessment process framework

Much of the U.S. petrochemical infrastructure is heavily concentrated along the western coast of the Gulf of Mexico within the impact zone of major tropical cyclone events. Flood impacts of recent tropical disturbances have been exacerbated by an overall lack of recognition of the vulnerabilities to process systems from water intrusion, as well as insufficient disaster mitigation planning. Vulnerability assessment methods currently call for the aggregation of qualitative data to survey the susceptibility of industrial systems to floodwater damage. A means to quantify these consequences is less often employed, resulting in a poor translation of the threat of flood hazards to a crucial element of the economy. This paper reviews flood damage assessment for industrial facilities and presents a component-level conceptual methodology to assess the consequences of flood events. To more effectively communicate loss potential from flood events, the proposed methodology utilizes synthetic estimation to calculate repair requirements, shutdown time, and direct cost.

A co-produced national climate change risk and vulnerability assessment framework for South Africa

IntroductionThere are mounting demands to undertake climate risk and vulnerability (CRV) assessments for policy, planning, funding, insurance, and compliance reasons. In Africa, given the adaptation imperative, this is particularly important. Increasingly, it has become clear that sub-national assessments are needed to inform adaptation practice. However, there has been relatively little guidance on how to undertake these more local assessments and aggregate them making it difficult for national governments to know the extent and variability of climate vulnerability and risk across the country.MethodsIn South Africa, the national government, led by the Department of Forestry, Fisheries and the Environment (DFFE), undertook to establish a common framework to guide the development and review of CRV assessments. This paper presents the framework that was co-developed through a series of engagements with stakeholders active in implementing and supporting CRV assessments.ResultsThe framework is intended to provide guidance on what to consider when undertaking CRV assessments within diverse South African contexts in order to enable alignment, comparison, and aggregation between them and work towards an effective climate adaptation response across scales. Rather than standardizing a methodology, the framework promotes the use of a standard set of concepts as the basis for each assessment and profiles a diversity of methods, tools and data sources for applying the concepts in a contextually sensitive way. This provides a flexible yet structured sequence of three interlinked steps in a risk and vulnerability assessment process, namely: (1) Planning, (2) Scoping and (3) Assessing. The framework guides users through the choice and application of three assessment depths, depending on decision-context, resourcing and extent of pre-existing data and information. It encourages the integration of participatory and indicator-based methods through an impact chain approach, profiling more than 30 freely available tools and resources. This process builds a strong evidence base and a deepening set of engagements and shared understanding between relevant stakeholders, upon which to act.DiscussionThis South African process can provide insight and support for actors driving the climate agenda in other countries looking to develop comparable assessments as the basis to drive equitable and transformative climate action and learning.

Assessment of Physical Vulnerability and Uncertainties for Debris Flow Hazard: A Review concerning Climate Change

Global climate change has increased severe torrential hazards, particularly debris flows in mountainous regions. After floods and earthquakes, debris flows are the most devastating natural hazard in the world. The effects of debris flow on human life and built environments necessitate reconsidering current infrastructure planning, engineering, and risk management practices. Hence, the vulnerability of elements at risk is critical for effective risk reduction systems. Therefore, this article reviews the existing physical vulnerability approach of infrastructure, particularly building toward debris flow hazards in the last 20 years. Furthermore, uncertainties associated with the vulnerability assessment and their quantification techniques have also been discussed in detail. It was found that matrices, curves, and indicators have been extensively used for vulnerability assessment approaches in the last two decades. However, if aleatory and epistemic uncertainties are not quantified or conserved in the vulnerability assessment process, it makes the system inefficient and unreliable. Moreover, data requirements, strengths, and weaknesses of approaches presented herein are highlighted with case studies. Finally, a thorough discussion on future needs in the field of risk assessment methodologies is highlighted by considering uncertainties into account.

Preservation of Villages in Central Italy: Geomatic Techniques’ Integration and GIS Strategies for the Post-Earthquake Assessment

Historical villages represent a highly vulnerable cultural heritage; their preservation can be ensured thanks to technological innovations in the field of geomatics and information systems. Among these, Geographical Information Systems (GISs) allow exploiting heterogeneous data for efficient vulnerability assessment, in terms of both time and usability. Geometric attributes, which currently are mainly inferred by visual inspections, can be extrapolated from data obtained by geomatic technologies. Furthermore, the integration with non-metric data ensures a more complete description of the post-seismic risk thematic mapping. In this paper, a high-performance information system for small urban realities, such as historical villages, is described, starting from the 3D survey obtained through the integrated management of recent innovative geomatic sensors, such as Unmanned Aerial Vehicles (UAVs), Terrestrial Laser Scanners (TLSs), and 360º images. The results show that the proposed strategy of the automatic extraction of the parameters from the GIS can be generalized to other case studies, thus representing a straightforward method to enhance the decision-making of public administrations. Moreover, this work confirms the importance of managing heterogeneous geospatial data to speed up the vulnerability assessment process. The final result, in fact, is an information system that can be used for every village where data have been acquired in a similar way. This information could be used in the field by means of a GIS app that allows updating the geospatial database, improving the work of technicians. This approach was validated in Gabbiano(Pieve Torina), a village in Central Italy affected by earthquakes in 2016 and 2017.

Machine learning takes a village: Assessing neighbourhood-level vulnerability for an overdose and infectious disease outbreak.

Multiple areas in the United States of America (USA) are experiencing high rates of overdose and outbreaks of bloodborne infections, including HIV and hepatitis C virus (HCV), due to non-sterile injection drug use. We aimed to identify neighbourhoods at increased vulnerability for overdose and infectious disease outbreaks in Rhode Island, USA. The primary aim was to pilot machine learning methods to identify which neighbourhood-level factors were important for creating "vulnerability assessment scores" across the state. The secondary aim was to engage stakeholders to pilot an interactive mapping tool and visualize the results. From September 2018 to November 2019, we conducted a neighbourhood-level vulnerability assessment and stakeholder engagement process named The VILLAGE Project (Vulnerability Investigation of underlying Local risk And Geographic Events). We developed a predictive analytics model using machine learning methods (LASSO, Elastic Net, and RIDGE) to identify areas with increased vulnerability to an outbreak of overdose, HIV and HCV, using census tract-level counts of overdose deaths as a proxy for injection drug use patterns and related health outcomes. Stakeholders reviewed mapping tools for face validity and community distribution. Machine learning prediction models were suitable for estimating relative neighbourhood-level vulnerability to an outbreak. Variables of importance in the model included housing cost burden, prior overdose deaths, housing density, and education level. Eighty-nine census tracts (37%) with no prior overdose fatalities were identified as being vulnerable to such an outbreak, and nine of those were identified as having a vulnerability assessment score in the top 25%. Results were disseminated as a vulnerability stratification map and an online interactive mapping tool. Machine learning methods are well suited to predict neighborhoods at higher vulnerability to an outbreak. These methods show promise as a tool to assess structural vulnerabilities and work to prevent outbreaks at the local level.

Self and Place Constructs in Climate Change Vulnerability Assessments: Gaps and Recommendations

In the United States, climate change vulnerability assessments are usually conceived as objectified exercises, based on theoretical orientations such as rational choice or systems theory. They adopt sectorial or population-level frames of reference and are operationalized by means of aggregating mathematical models, geospatial analytical platforms, and advanced visualization tools. While vulnerability assessments are intended to inform decision making, they often lack process-based mechanisms that enable them to be framed in terms of localized knowledge and perspectives. This is a weakness because occupant attitudes regarding places can spark unyieldingly negative reactions to expert-generated, objectivist vulnerability assessment processes and their outputs. In this paper, I attempt to demonstrate the salience of self and place constructs and explore the implications of their tendency to block serious reflection about the nature of potential vulnerabilities and risk management interventions. If acknowledged and addressed in a manner that is empathetic and context sensitive, it may be possible to channel these perspectives to elevate and deepen dialog about climate change and help to identify and compile circumstantially appropriate menus of adaptation policy interventions.

喀斯特含水层的地下水易污性,主要挑战和因素: 在Spain南部Ubrique泉域的应用

Groundwater vulnerability mapping is one of the tools most often applied to analyse the sensitivity of karst aquifers to pollution. These maps aim to support stakeholders in decision-making and to promote land-use management compatible with water protection; however, the validation of these maps is still a challenge in many cases, triggering high uncertainty. For karst media, due to the strong heterogeneity in recharge mechanisms and hydraulic characteristics, validation is a significant stage and it must be inherent within the groundwater vulnerability assessment process. This work aims to assess the implementation of tools used for protecting the quality of water discharging or extracted from the Ubrique karst system in southern Spain, which supplies drinking water that is threatened by periodical pollution/turbidity episodes. A groundwater vulnerability map, attained by application of the COP method and validated by multiple in-situ observations, shows an extremely vulnerable system due to the absence of protective overlayers and the significant development of exokarst landforms, including shallow holes. This map could constitute the basis for defining protection zones for the Ubrique springs; however, their comprehensive protection requires the implementation of monitoring tools and an effective management strategy, through an early warning system that assures stable environmental and hydrogeological conditions and improves operational procedures associated with the drinking water service. This research establishes the strong relationship of the different methods applied to protect the source from contamination events, ranging from classical hydrodynamic and hydrochemical approaches to the implementation of protection zones and early warning groundwater quality monitoring networks.

Seismic and Fire Assessment and Upgrading Process for Historical Buildings: The Case Study of Palazzo Colonna in Caggiano

The assessment and retrofit of existing masonry structures with historical and cultural value in highly seismic zones is a challenging issue in earthquake engineering. In fact, the historic and recent earthquakes have showed the problem of the seismic vulnerability of existing masonry constructions. A historical masonry palace, located in Caggiano (Salerno, Italy) is used herein as case study, showing the vulnerability assessment and the seismic upgrading process. The case study building has a masonry structural type at the first two floor while there is a third floor realized in reinforced concrete and a fourth floor realized with a wood structure. The building was characterized by a remarkable seismic vulnerability and needed seismic upgrading operations. After the vulnerability assessment process, some design suggestions are proposed for the seismic upgrading of the building. The structure before and after the upgrading operations has been checked through non linear static and dynamic analyses. Then, coherently with the ”Sismabonus” approach, the attribution of the seismic risk class, performed through numerical analyses, is founded on two parameters, namely the Annual Expected Average Losses (PAM), related to economic factors, and the Life Safety Index (IS-V), related to the structure seismic safety. Finally, the overcoming of the different classes of risk is showed and compared with the amount of the retrofit operations, their costs and the impact on the existing space. Moreover, also fire assessment has been investigated. In fact, in many cases the buildings such as the case study structure are intended to public activities such as museums, so specific fire requirements, like fire resistance, are necessary. This topic became relevant especially if the structure is equipped with particular structural retrofit interventions which can be altered and modified in case of a fire. The paper presents the results of advanced thermo-mechanical analyses on the historical masonry palace under investigation. Since the case study building has a masonry structural type at the first two floor while there is a third floor realized in reinforced concrete, the fire analyses were conducted on the third and on the fourth floors, which may be more vulnerable to fire.

Seismic Vulnerability Assessment of School Buildings in Seismic Zone 4 of Pakistan

Thick population density and its escalation propensity in seismically active regions of Pakistan has raised sincere concerns about the performance of building stock whose suboptimal performance and complete collapses led to a colossal number of casualties during the past earthquakes. The current research is inspired by the Kashmir earthquake of 2005 which consumed more than 80,000 lives, out of which, approximately 19,000 were children due to wide spread collapse of school buildings. A new database for existing reinforced concrete (RC) school buildings in seismic zone 4 of Pakistan has been developed using the surveyed information and presented briefly. The paper presents the statistics of the data collected through field surveys and professional interviews. It was found that the infrastructural authorities in the considered region developed some specific designs for school buildings, with varying architectural and structural configurations, which were eventually replicated throughout the area. In the current study, almost 2500 schools were surveyed for identifying versatile architectural and structural configurations, and subsequently, 19 different types had been identified, which were eventually used as representative stock for the schools in seismic zone 4 of Pakistan, Muzaffarabad district. The results of the study yield the brief of the collected data from the field and a consolidated methodology for establishing the analytical fragility relationships for one of the 19 structural configurations of the school buildings. A sample building from the collected data has been selected by considering the maximum number of students, and afterwards, the vulnerability is assessed by employing incremental dynamic analysis (IDA) which constitutes the presented methodology. Finally, the fragility curves are developed and presented for the said building type. The derived analytical fragility curves for the considered building type indicate its structural vulnerability and as a whole represent its satisfactory behavior. The vulnerability assessment process and the fragility development are described in an easy manner so that the domestic practicing engineers can readily become able to extend the application towards other school buildings in the region. The developed relationships can be employed for rational decision making so that essential disaster preparedness can be carried out by identifying any need for structural strengthening and interventions.

Cybersecurity Vulnerability Mitigation Framework Through Empirical Paradigm (CyFEr): Prioritized Gap Analysis

Cybersecurity vulnerability assessment tools, frameworks, methodologies, and processes are commonly used to understand the cybersecurity maturity and posture of a system or a facility. Although those tools are strictly developed based on standards defined by organizations such as the National Institute of Standards and Technology (NIST) and the U.S. Department of Energy, the majority of these tools and frameworks do not provide a platform to prioritize the requirements to reach a desired cybersecurity maturity. To address that challenge, we have been developing a framework and a software application called the cybersecurity vulnerability mitigation framework through empirical paradigm (CyFEr). The efficacy of CyFEr was evaluated by implementing it on the NIST cybersecurity framework (CSF). This paper provides a detailed architecture of CyFEr and demonstrates its application to CSF by testing against a real-world cyberattack that targeted industrial control systems in a critical infrastructure facility.

Summarizing vulnerabilities’ descriptions to support experts during vulnerability assessment activities

Vulnerabilities affecting software and systems have to be promptly fixed, to prevent violations to integrity, availability and confidentiality policies of targeted organizations. Once a vulnerability is discovered, it is published on the Common Vulnerabilities and Exposures (CVE) database, freely available on the web. However, vulnerabilities are described using natural language, which makes them hard to be automatically interpreted by machines. As a consequence, vulnerability assessment activities tend to be time-consuming and imprecise, as the assessors must manually read the majority of the vulnerabilities concerning the perimeter to be protected, to make a decision on which vulnerabilities have the highest priority for patching. In this paper we present CVErizer, an approach able to automatically generate summaries of daily posted vulnerabilities and categorize them according to a taxonomy modeled for industry. We empirically assess the classification capabilities of the approach on a set of 3369 pre-labeled CVE records and perform an end-to-end evaluation of CVErizer summaries involving 15 cybersecurity master students and 4 professional security experts. Our study demonstrates the high performance of the proposed approach in correctly extracting and classifying information from CVE descriptions. Summaries are also considered highly useful for helping analysts during the vulnerability assessment processes.

Vulnerability Assessment of Sensor Systems.

There are more and more applications of sensors in today’s world. Moreover, sensor systems are getting more complex and they are used for many high-risk security-critical purposes. Security assurance is a key issue for sensors and for other information technology (IT) products. Still, sensor security facilities and methodologies are relatively poor compared to other IT products. That is why a methodical approach to the sensor IT security is needed, i.e., risk management, implementation of countermeasures, vulnerability removal, and security evaluation and certification. The author proposes to apply the main security assurance methodology specified in ISO/IEC 15408 Common Criteria to solve specific security problems of sensors. A new Common Criteria compliant method is developed which specifies the vulnerability assessment process and related data in a structured way. The input/output data of the introduced elementary evaluation processes are modeled as ontology classes to work out knowledge bases. The validation shows that sensor-specific knowledge can be acquired during the vulnerability assessment process and then placed in knowledge bases and used. The method can be applied in different IT products, especially those with few certifications, such as sensors. The presented methodology will be implemented in a software tool in the future.

Pinning down social vulnerability in Sindh Province, Pakistan: from narratives to numbers, and back again.

This paper reflects critically on the results of a vulnerability assessment process at the household and community scale using a quantitative vulnerabilities and capacities index. It validates a methodology for a social vulnerability assessment at the local scale in 62 villages across four agro‐ecological/livelihood zones in Sindh Province, Pakistan. The study finds that the move from vulnerability narratives to numbers improves the comparability and communicational strength of the concept. The depth and nuance of vulnerability, however, can be realised only by a return to narrative. Caution is needed, therefore: the index can be used in conjunction with qualitative assessments, but not instead of them. More substantively, the results show that vulnerability is more a function of historico‐political economic factors and cultural ethos than any biophysical changes wrought by climate. The emerging gendered vulnerability picture revealed extremes of poverty and a lack of capacity to cope with contemporary environmental and social stresses.

Assessing and adapting to climate change in the Blue Mountains, Oregon (USA): Overview, biogeography, and climate

The Blue Mountains Adaptation Partnership (BMAP) was established to increase climate change awareness, assess vulnerability to climate change, and develop science-based adaptation strategies for national forest lands in the Blue Mountains region of northeast Oregon and southeast Washington (USA). The BMAP process included (1) development of a science-management partnership, (2) a vulnerability assessment of the effects of climate change on natural resources and infrastructure, (3) development of adaptation options that will help reduce negative effects of climate change and assist the transition of biological systems and management to a changing climate, and (4) ongoing dialogue and activities related to climate change in the Blue Mountains region. This special issue of Climate Services describes social context and climate change vulnerability assessments for water use and infrastructure, vegetation, and riparian ecosystems of the Blue Mountains region, as well as adaptation options for natural resource management. This manuscript introduces the special issue, describing the management, biogeographic, and climatic context for the Blue Mountains region; the climate change vulnerability assessment and adaptation process used in BMAP; and the potential applications of the information described in the special issue. Although the institutional focus of information in the special issue is U.S. Forest Service lands (Malheur, Umatilla, and Wallowa-Whitman National Forests), the broader social context and adaptation options should be applicable to other lands throughout this region and the Pacific Northwest.

Assessing vulnerability in Cochabamba, Bolivia and Kota, India: how do stakeholder processes affect suggested climate adaptation interventions?

ABSTRACTIn Cochabamba, the vulnerability assessment process focused on La Maica community and the agriculture sector. Community stakeholders were involved in workshops while municipal and regional actors participated through interviews. In the Kota process, the municipality was in the geographical focal point and a multi-level stakeholder group focused upon slum inhabitants. The suggested interventions and actions in both cities were dominated by systems (infrastructure and ecosystems) while identified barriers and facilitating factors to implementation revealed a greater acknowledgement of governance issues. Focus on marginalized groups and sectors is facilitated by the direct representations of those issues. While multi-stakeholder processes can be important forums for social learning adaptation planning that benefit vulnerable sectors and groups, with limited inclusion and responsibility given to representatives of marginalized sectors and groups for implementation actions, it is likely that the interests and priorities of more powerful actors will dominate and not contribute to increasing the resilience of the most vulnerable.

SOM-DRASTIC: using self-organizing map for evaluating groundwater potential to pollution

Groundwater is considered as the most important water resource, especially in arid and semi-arid regions, so it is crucial to impede this source of water to be contaminated. One of the most common methods to assess groundwater vulnerability is DRASTIC method. However, the subjectivity existing in defining DRASTIC weights and ratings as well as inadaptability of the parameters involved in this method with special geology, hydrogeology, land use and climatic conditions have urged researchers to modify this method. In this paper, a new method combining a special type of the neural networks called Self-Organizing Map (SOM) and the traditional DRASTIC model resulting in the hybrid SOM-DRASTIC model is applied to modify and improve DRASTIC Model. The traditional DRASTIC method holds a summation among all negative effects of different factors contributing to vulnerability, while the proposed hybrid method is able of classifying the groundwater vulnerability and deriving the real relation existing between the DRASTIC parameters as the inputs and the vulnerability class as the output of the method. The vulnerability assessment process was performed on the Zayandeh-Rud river basin aquifers in Iran. The SOM-DRASTIC identified the northern parts of the study area as the most vulnerable areas with a drastically fractured structure, while the traditional DRASTIC ranked the western parts as the most vulnerable regions with a high rate of net recharge. The results demonstrate that the proposed method can be used by managers and decision-makers as an alternative robust tool for vulnerability-based classification and land use planning.

Assessing industrial ecosystem vulnerability in the coal mining area under economic fluctuations

In the context of the depth adjustment of the global economy and wild fluctuations in energy prices, the vulnerability issue of the coal mining industrial ecosystem (CMIES) has seriously affected the sustainable development of the regional economy. Comparisons of CMIES health status at a regional level are worthy of being conducted. This not only contributes to understanding a particular coal mining area's situation in regards to CMIES vulnerability, but also helps to discover a meaningful benchmark to learn the experiences in terms of action programmes formulation. In this study, based on the analysis of the vulnerability response mechanism of CMIES to economic fluctuations, an initial indicator system for vulnerability assessment of CMIES was constructed. Ultimately, 14 vulnerability-evaluating indicators and their weights were obtained using rough set attribute reduction. Based on a composite CMIES Vulnerability Index (CVI), the Rough Set-Technique for Order Preference by Similarity to Ideal Solution-Rank-sum Ratio (RS-TOPSIS-RSR) methodology is proposed to conduct the CMIES vulnerability assessment process from an overall perspective. Using this methodology, 33 coal mining areas in China are ranked as well as grouped into three specific groups based on the CVI score. The results demonstrate the feasibility of the proposed method as a valuable tool for decision making and performance evaluation with multiple alternatives and criteria.

Effectiveness evaluation of objective and subjective weighting methods for aquifer vulnerability assessment in urban context

Groundwater vulnerability assessment has been an accepted practice to identify the zones with relatively increased potential for groundwater contamination. DRASTIC is the most popular secondary information-based vulnerability assessment approach. Original DRASTIC approach considers relative importance of features/sub-features based on subjective weighting/rating values. However variability of features at a smaller scale is not reflected in this subjective vulnerability assessment process. In contrast to the subjective approach, the objective weighting-based methods provide flexibility in weight assignment depending on the variation of the local system. However experts’ opinion is not directly considered in the objective weighting-based methods. Thus effectiveness of both subjective and objective weighting-based approaches needs to be evaluated. In the present study, three methods – Entropy information method (E-DRASTIC), Fuzzy pattern recognition method (F-DRASTIC) and Single parameter sensitivity analysis (SA-DRASTIC), were used to modify the weights of the original DRASTIC features to include local variability. Moreover, a grey incidence analysis was used to evaluate the relative performance of subjective (DRASTIC and SA-DRASTIC) and objective (E-DRASTIC and F-DRASTIC) weighting-based methods. The performance of the developed methodology was tested in an urban area of Kanpur City, India. Relative performance of the subjective and objective methods varies with the choice of water quality parameters. This methodology can be applied without/with suitable modification. These evaluations establish the potential applicability of the methodology for general vulnerability assessment in urban context.