Vulnerability Assessment Research Articles

A meta-ensemble machine learning strategy to assess groundwater holistic vulnerability in coastal aquifers

Assessing the vulnerability of groundwater in coastal aquifers is crucial for mitigating risks associated with seawater intrusion and anthropogenic impacts. This study introduces an innovative machine learning (ML)-enhanced methodology that synergizes the strengths of two established vulnerability assessment frameworks, DRASTIC and GALDIT. The hybrid approach overcomes the limitations of each framework—DRASTIC's inadequacies in coastal settings and GALDIT's limited consideration of agricultural and industrial impacts. Utilizing advanced decision tree-based ML algorithms—Adaptive Boosting (AdaBoost), Extreme Gradient Boosting (XGBoost), Light Gradient Boosting Machine (LGBM), and Random Forest (RF)—this research was conducted in the Azarshahr Plain, NW Iran. Model efficacy was validated using Pearson's correlation coefficient (r) and distance correlation (DC), with nitrate (NO3−) and total dissolved solids (TDS) serving as proxies for evaluating the DRASTIC and GALDIT models, respectively. The original DRASTIC indices exhibited weak correlations with NO3− (r = 0.24, DC = 0.25), but ML-enhanced models, particularly AdaBoost, showed significant improvements (r = 0.78, DC = 0.79). Similar enhancements were observed with GALDIT, where correlations improved markedly with AdaBoost integration. A sophisticated second-level AdaBoost meta-ensemble was developed to integrate enhanced DRASTIC and GALDIT assessments, achieving superior correlation metrics (r = 0.80, DC = 0.84 for NO3−; r = 0.82, DC = 0.83 for TDS). These results underscore the effectiveness of an integrated ML-based approach in advancing beyond traditional vulnerability assessment methods, providing a more comprehensive, accurate, and robust evaluation of coastal aquifer vulnerability.

Factors driving human–elephant conflict: statistical assessment of vulnerability and implications for wildlife conflict management in Sri Lanka

Human–elephant conflict (HEC) is a serious social–ecological problem in Sri Lanka’s elephant range regions, as between 200 and 400 elephants have been killed annually over the last years, and more than 1200 people have died from the consequences of elephant encounters within a decade. Crop foraging causes economic damage to farming households. The study aims to understand factors driving vulnerability to HEC among the population. Employing a cross-communal multi-item large-N field survey (N = 651), authors were able to describe living conditions and perceptions of Sri Lankan villagers affected by HEC. By running a multiple regression analysis with correlated variables, the study is able to correlate independent variables to vulnerability, namely socio-economic conditions, environmental change and land-use, and awareness. Furthermore, a vulnerability map has been created, identifying Puttalam, Anuradhapura, Kurunegala, Matale, and Polonnaruwa districts as conflict hotspots. Private electric fences as a widespread protection measure were found to have unintended negative side-effects to non-protected households. The findings suggest the urgent need to upscale public policies mitigating the consequences of HEC on affected populations by reducing overall vulnerability to environmental hazards, including human–wildlife conflict.

Quantifying the vulnerability of road networks to flood-induced closures using traffic simulation

Disruptions in road networks can significantly impact traffic flow, necessitating the identification and mitigation of vulnerable components. This study presents a methodology to assess the vulnerability and robustness of road networks, addressing the research gap in comprehensive approaches that effectively evaluate both controlled intersections and uncontrolled/free-flow highway segments. The proposed framework employs traffic simulation tools to model road closures within designated study areas, focusing on networks in Qatar. Performance measures such as average control delay and volume to capacity ratios are utilized to calculate vulnerability indices for network components. The two-pronged approach quantifies the impact of simulated closures at both the component and network levels, revealing critical intersections and road segments that markedly affect network performance during disruptions. The findings contribute to the field by providing transportation engineers with an effective quantitative tool to detect vulnerabilities in their road network, guiding design plans and actions to mitigate the potential harmful impacts of disruptive events on transportation infrastructure. The methodology's scalability ensures its applicability to various operational contexts, offering significant insights for transportation planning and infrastructure resilience. By establishing a comprehensive vulnerability analysis framework, this study enhances the understanding and management of road network vulnerabilities in complex urban environments. Further research on integrating dynamic traffic assignment and real-time data is recommended to further enhance the predictive accuracy and applicability of the proposed framework, ultimately improving transportation infrastructure resilience.

Analysis of Socio-Environmental Vulnerability in Areas with Overpopulation and Natural Risks Induced by Their Urban-Territorial Conditions

Analysis of Socio-Environmental Vulnerability in Areas with Overpopulation and Natural Risks Induced by Their Urban-Territorial Conditions

An Analytical Safety Tree for Heritage Buildings: Application to the Archaeological Museum “Domenico Ridola”, Matera (Italy)

ABSTRACT Historical masonry construction is a significant architectural typology that represents the cultural identity of Western Europe. Exposure to seismic events seriously compromises the conservation of architectural heritage, as evidenced by recent earthquakes. In this context, the process of knowledge acquisition, vulnerability evaluation, and planning interventions becomes fundamentally important to identify and implement maintenance and conservation strategies. Safety trees, never used for seismic engineering purposes, are particularly effective in making safety-related decisions in potentially hazardous or complex situations. This paper proposes an analytical framework to evaluate the structural safety of cultural heritage buildings, using an analytical safety tree. This instrument is here applied to assist safety assessments, risk management, and process optimization. Specifically, the proposed tree encompasses a multi-step procedure characterized by three possible vulnerability assessments, with the advantage of providing an overview of the knowledge state, detected pathologies, and analysis of a heritage building, outlining a path to follow to ensure the safety of built heritage. The work first formalizes this new tool, starting from the classical theory of safety decision trees. Secondly, to demonstrate the potential of the approach, the decision tree is developed and applied to the safety assessment of the Archaeological Museum “Domenico Ridola” in Matera, Italy.

Climate change vulnerability assessment of Karşıyaka, İzmir

Climate change vulnerability assessment of Karşıyaka, İzmir

Gender vulnerability assessment to inform gender-sensitive adaptation action: a case study in semi-arid areas of Mali

Gender vulnerability assessment to inform gender-sensitive adaptation action: a case study in semi-arid areas of Mali

Towards sustainable coastal management: a hybrid model for vulnerability and risk assessment

This paper presents the development of a Hybrid Model (HM) integrated with a Bayesian Network (BN) for comprehensive coastal vulnerability and risk assessment, with a focus on Konyaaltı Beach, Antalya, Turkey. The HM incorporates critical environmental parameters such as wind, waves, currents, and sediment transport to simulate conditions at vulnerable coastal areas and perform risk assessments for storm effects, flooding, and erosion. The model includes submodules for predicting coastal storms, quantifying sediment transport rates, assessing tsunami inundation severity, and categorizing storms based on beach typologies. The Adaptive Neuro-Fuzzy Inference System (ANFIS) is utilized for significant wave height predictions, enhancing the model's accuracy. The integration of hydrodynamic modeling, Bayesian networks, and ANFIS offers a robust framework for assessing coastal vulnerability and informing sustainable management practices. The study's results highlight the necessity for integrated risk management strategies, including adaptive infrastructure design, zoning and land use regulations, ecosystem-based management, and continuous monitoring and model refinement to enhance coastal resilience against dynamic environmental forces. This research provides valuable insights for mitigating the impacts of hazards on urban developments, contributing to the advancement of sustainable coastal management.

Climate resilience of European wine regions

Over centuries, European vintners have developed a profound knowledge about grapes, environment, and techniques that yield the most distinguishable wines. In many regions, this knowledge is reflected in the system of wine geographical indications (GI), but climate change is challenging this historical union. Here, we present a climate change vulnerability assessment of 1085 wine GIs across Europe and propose climate-resilient development pathways using an ensemble of biophysical and socioeconomic indicators. Results indicate that wine regions in Southern Europe are among the most vulnerable, with high levels also found in Eastern Europe. Vulnerability is influenced by the rigidity of the GI system, which restricts grape variety diversity and thus contributes to an increased sensitivity to climate change. Contextual deficiencies, such as limited socioeconomic resources, may further contribute to increased vulnerability. Building a climate-resilient wine sector will require rethinking the GI system by allowing innovation to compensate for the negative effects of climate change.

Seismic vulnerability assessment of RC deck-stiffened arch bridges

Due to the recent damage and collapse of several bridges in Italy, reliable quantification of their vulnerability is paramount for planning various risk mitigation and resilience-enhancing strategies. This paper specifically focuses on the seismic vulnerability and loss assessment of existing reinforced concrete (RC) deck-stiffened arch bridges. The study considers a bridge typology known as the “Maillart–type” arch bridge, a common structural typology in the 1950s and characterised by a particularly stiff deck and a slender vault, i.e., a high deck-to-arch flexural stiffness ratio. Such bridges were typically designed considering only gravity loads and usually without ductile structural detailing and consideration of capacity-design principles. Historical documents and original design blueprints are used to simulate the design of an archetype bridge representative of the Italian “Maillart-type” arch bridge population. Then, nonlinear cloud-based time-history analysis is performed to investigate the seismic response of the considered archetype under varying ground-motion intensities and derive fragility and vulnerability relationships. Specifically, three different models are considered: one that adopts a conservative approach where damage is determined by the shear failure of the shortest pillar, another that provides a more detailed representation of structural damage progression, and a third that assumes retrofitting of the shortest pillar. The vulnerability relationships are combined with site-specific seismic hazard curves for case-study locations to estimate expected annual losses. The results represent a first step in assessing the seismic vulnerability of “Maillart–type” arch bridges to plan seismic risk mitigation interventions for such a bridge typology.

Forest Fire Hazards and Livelihood Vulnerability Assessment of Ghumsur Forests in Ganjam District of Odisha

Background: The livelihood patterns of indigenous tribal communities residing in the Ghumsur forests are intricately interwoven with their dependence on forest-related activities. However, the degradation of forest ecosystems, particularly the incidence of forest fires, exerts a profound impact on the socio-economic dynamics and resilience of these communities. Consequently, an exigent need arises to comprehensively elucidate, evaluate and comprehend the nuanced characteristics of these areas concerning the complex interplay between forest fires and livelihoods. Methods: A thorough investigation was conducted to evaluate livelihood vulnerability to forest fires in the Ghumsur North Division forests. This assessment utilized the Livelihood Vulnerability Index (LVI), incorporating 34 indicators condensed into six factors for a comprehensive composite index. The factors represented various aspects of vulnerability and were based on tangible indicators reflecting the complexity of livelihood vulnerability. Data sources were primarily used, with indicators standardized on a scale from 0 to 1, where values near 1 indicated higher vulnerability. Result: The Gallery sub-region is particularly vulnerable due to factors like poor infrastructure, increased reliance on forests, close proximity to forested areas, socio-economic fragility and exposure to extreme weather events. It’s crucial to improve adaptive capacity in fire-affected regions to reduce vulnerability to forest fires. Tailored policy interventions should focus on sector-specific development programs and involve communities in adaptation planning to address the link between livelihoods and susceptibility to forest fires.

Groundwater Vulnerability Assessment—Case Study: Tirana–Ishmi Aquifer, Albania

This paper discusses the groundwater vulnerability to pollution assessment for the Tirana–Ishmi alluvium aquifer, Albania. Economic activities, municipal wastewater discharged into rivers and groundwater overexploitation threaten to pollute the groundwater. Based on the aquifer characteristics and the available data, SINTACS was selected as the most realistic assessment model. The SINTACS parameters’ rates assigned to the aquifer’s characteristics (water table depth, infiltration, unsaturated zone, soil media, aquifer media, hydraulic conductivity, topography) were adapted to the local features, followed by GIS vulnerability mapping. Statistical analysis indicates that the unsaturated zone, hydraulic conductivity and aquifer media have the highest influence on groundwater vulnerability, whereas topography has the lowest influence. Validation through sensitivity analysis and nitrates content confirms the rational selection of the SINTACS model and the reliability of the study’s outputs. The most vulnerable areas to pollution are the recharge zones, followed by the highly urbanized Tirana City area, characterized by high levels of groundwater extraction rate and wastewater discharged into the rivers. The paper, being the first completed groundwater vulnerability assessment of the study area, could serve as a basis for a scientific–based groundwater management that should be considered in local territory planning.

Urban flood-bearing vulnerability evaluation based on the moment estimate weighting and improved gray target model.

Increasingly severe flooding seriously threatens urban safety. A scientific urban flood-bearing vulnerability assessment model is significant to improve urban risk management capacity. The gray target model (GTM) has advantages in urban flood-bearing vulnerability assessment. However, indicator correlation and single bull's-eye are commonly neglected, leading to defective evaluation results. By integrating the four base weights, an improved weighting method based on the moment estimate was proposed. Then, the marginal distance was used to quantify the indicator correlation, and the TOPSIS model was introduced to define the relative bull's-eye distance. Thus, an improved gray target evaluation method was established. Finally, an urban flood-bearing vulnerability evaluation model was presented based on the moment estimate weighting-improved GTM. In this study, Zhengzhou City, China, was taken as an example. The spatial and temporal changing characteristics of the flood-bearing vulnerability of Zhengzhou from 2006 to 2020 were investigated. The results show that: (1) On the temporal scale, the disaster-bearing vulnerability of Zhengzhou City showed an upward trend during the 15 years; (2) On the spatial scale, Guancheng District of Zhengzhou City had the relatively highest vulnerability to urban flooding. This study is expected to provide a scientific reference for urban flood risk management.

Evaluation and Assessment of Software Security Risks and Vulnerabilities Within the Realm of Secure DevOps.

Security plays a vital role in successful software development and consistency, especially in a modern, fast-expanding world dominated by technologies. It guarantees that all privacy, integrity, and accessibility of information, coding, and services are protected. Achieving such requires a consistent consideration of security throughout all developmental stages of software. Although several methods for improving the quality of software have been created, there is still no clear method for effectively integrating security throughout each stage of the software developmental process. The inability to give adequate attention to security has been identified as the main cause of common flaws. Many forward-thinking businesses frequently employ a "patch and infiltrate” technique, taking security into consideration only after the execution of the task. Higher costs, project delays, neglect of verification and integration during the development life cycle of the project, reliance on external tools and parts, and ignorance among all factors contribute to the disregard of security during the SDLC. Nevertheless, Secure-DevOps is indispensable for the survival of companies in the Information and Communication Technology (ICT) landscape. Consequently, applying an effective approach that deals with security within every level of the SDLC is crucial. To bridge this gap, a comprehensive examination of effective techniques for developing secure software was presented, taking into account the financial and time constraints of a project. A framework for ensuring security built upon Secure-DevOps practices, which seamlessly integrates the best security measures into different stages of the SDLC, was identified. To validate this framework, a mathematical model has been employed. The study concludes that effectively incorporating Secure-DevOps practices throughout the Software developmental process, minimizes security risks and vulnerabilities.

Integrated risk assessment of landslide in karst terrains: Advancing landslides management in Beiliu City, China

Beiliu City, Guangxi Zhuang Autonomous Region, China, like other karst landscape areas, is also suffering from the threat of landslides. This research applied the circular variance method to delineate 31,465 slope units and then combined it with a geographic information system and a well-established risk assessment system to synthesize three perspectives-susceptibility, hazard, and vulnerability to realize the risk assessment of karst landslides in Beiliu City. Using perennial field surveys, aerial images-derived landslide inventories, slope unit investigations, and a literature review combined with a Fully Convolutional Neural Networks approach, we present a culminating in the derivation of landslide susceptibility assessment outcomes within the study area. Because Beiliu City is located in a karst area, this research employs the quantification of soil erosion intensity as a metric to assess landslide hazard. In this study, based on a comprehensive analysis of the basic characteristics of landslides and their associated disaster-bearing bodies, a robust landslide vulnerability assessment index system was constructed for risk assessment of karst landslides in Beiliu City. The landslide risk assessment model in karst area is constructed by combining the landslide susceptibility and the vulnerability in the danger range. Detailed field surveys verified the scientific validity and accuracy of the assessment results. This research extends beyond merely furnishing scientific data support for local governmental efforts in disaster prevention and mitigation. It impressively enhances the methodological framework for conducting landslide risk assessments within karst landscapes, thereby offering a robust foundation for both immediate and strategic responses to the inherent geological vulnerabilities of these areas.

The role of strategic planning in Nature- based Solutions (NBS) transformation: An evaluation of the Green Cities Framework in mainstreaming NBS in 6 European countries

Urban areas are currently experiencing a number of adverse effects associated with both climate induced change and the nature of development processes. This has led to, not only a reduction in the provision and performance of environmental attributes but has also generated threats to the well-being of urban inhabitants. In response, the concept of Nature- based Solutions (NBS) has emerged as a means of reconfiguring spatial interactions to maximize adaptation and resilience. Despite this however, the process of transition for NBS has frequently encountered several governance related challenges. This paper examines the extent to which the Green Cities Framework (GCF) can overcome these limitations and aid NBS mainstreaming. Through policy-based experimentation in six European Cities we assess the ability of the GCF to deliver improved NBS capacity and innovation. The research revealed positive strategic planning improvements in all cities studied. Particular areas of strength included improvements to NBS visioning, working group collaboration, climate impact and vulnerability assessment, integration with existing planning instruments and processes, business model development and post-decision evaluation. Several areas of potential improvement were also revealed. These were primarily associated with difficulties in communicating with all relevant actors, concerns with undertaking financial assessments and defining NBS standards for procurement.

Physics-based flood vulnerability assessment for steel portal framed industrial buildings

Steel portal framed industrial buildings have been widely used as warehouses, supermarkets, manufacturing workshops and storage facilities around the world. As such, these buildings make up a significant portion of the building stock. Despite this, there remains a lack of the physics-based flood vulnerability models necessary for undertaking detailed community flood risk management activities (e.g., quantitative risk assessment, cost-benefit analysis of risk reduction and resilience enhancement measures at the building level). To this end, this study developed a physics-based vulnerability assessment method for steel portal framed industrial buildings subjected to hydrostatic and hydrodynamic flood actions. Physical damage induced by flood forces to the building envelope (wall siding and fenestration) and the structural framing (steel portal frames and end wall frames) was considered. Monte Carlo simulations incorporate various flood load cases, probability models of demands and capacities as well as major failure mechanisms of different structural and non-structural components to conduct the damage assessment. The flood vulnerabilities for a prototype industrial building link the physical damage of individual building subassemblies to monetary loss ratios considering various inundation depths, flow velocities and flow directions.

Vulnerability assessment of natural heritage in the North-Eastern Ecuadorian Amazon using land use cover and nature protection status

This study evaluates the vulnerability of natural heritage in the Northeast Ecuadorian Amazon (NEA), from the perspective of intrinsic vulnerability. Therefore, two proxy indicators of vulnerability were established: (i) the ecological integrity vulnerability index (EIVI), indicating the potential loss of ecological integrity, assessed by protection status (2018); (ii) the biological diversity vulnerability index (BVI), deriving the potential loss of biological diversity, using land cover/land use (2014). Biodiversity values were derived with land cover-related biodiversity data, and (iii) and compared with spatial congruence/correlation between (i) and (ii). The EIVI was directly derived using protection status, which defines vulnerability levels by ranking them according to corresponding levels of anthropic development allowance. A robust relationship between land use classes and species richness was found for both endemic vascular plants in neotropical regions and multi-taxa in tropical forests worldwide, validating the BVI. Furthermore, the moderate spatial correlation between protection status and land cover (r = 0.52) may be partially explained by 3,060 km2 of unprotected primary forest. Overall, 42 % of the NEA have a high degree of congruence between potential biodiversity and protection status. In conclusion, this study provides insights into nature conservation efforts in areas with sparse biodiversity data using readily available geographic information.

Assessment of risk intensity in the triffa plain aquifer: Integration of hazard quantification, land use analysis, dynamic vulnerability GCITF, and DRASTIC method

This study aims to assess the level of groundwater pollution risk in the Triffa Plain, stemming from various pollution sources, with a specific focus on agricultural intensification and excessive pesticide use. Data were collected from ABHM (the Moulouya Hydraulic Basin Agency) and ORMVAM (Regional Office of Moulouya Agricultural Development), and a field visit was conducted in July 2023. The study utilized two main methodologies for mapping risk intensity: the COST 620 action and overlaying vulnerability maps with the land use (LU) factor. Vulnerability maps were generated using the original DRASTIC method and the new dynamic vulnerability assessment method, GCITF.The research approach involved comparing the COST 620 risk index (Ri) and the land use risk index (LU) to identify the most suitable method for the study area. Due to challenges in inventorying various point sources of pollution, the study focused on mapping the primary sources of pollution (diffuse, point, and linear). The key findings indicate that the predominant pollution intensity in the region is high, covering 60.66% of the total surface area. These results closely align with those obtained using the European COST 620 approach and the spatial distribution of nitrates. The study demonstrates the reliability of integrating the GCITF method in assessing groundwater contamination risk, highlighting the significant negative impacts of agricultural activities on the Triffa Plain aquifer, primarily due to uncontrolled pesticide and fertilizer use and point sources of pollution.This study suggests that implementing targeted technical solutions for specific pollution sources is crucial for reducing contamination in the Triffa Plain. These pollution risk intensity maps can assist planners and decision-makers in understanding the origin of pollution and identifying necessary actions to minimize contamination risk, contributing to better groundwater management and protection in the region.

A multidimensional framework for assessing cultural heritage vulnerability to flood hazards

ABSTRACT This study proposes a multidimensional framework for the assessment of cultural heritage vulnerability to flood hazards. In this framework, cultural heritage is framed within a landscape approach drawing on the concept of the historic urban landscape as a physical entity, a lived space and a layered socio-economic environment. In such manner, this study emphasises that climate change disturbs both tangible and intangible aspects of cultural heritage – such as social systems and daily life practices – by modifying the material conditions that sustain them. Thus, the proposed framework integrates built and natural heritage with area-based vulnerability and socio-economic deprivation, considering households’ exposure to flood risk. The analysis follows a spatial and quantitative approach using open geospatial data available at the statistical unit level. The data are processed and analysed employing QGIS software and statistical analysis. Results confirm that cultural heritage vulnerability is highly associated with socio-economic deprivation and area-based vulnerability. The understanding of this interrelation is key to the identification of historic urban landscape qualities and priority areas for reconstruction and social support.