Vulnerability Assessment Research Articles

Harnessing ML and GIS for Seismic Vulnerability Assessment and Risk Prioritization

Harnessing ML and GIS for Seismic Vulnerability Assessment and Risk Prioritization

Deep learning vulnerability analysis against adversarial attacks

Deep learning vulnerability analysis against adversarial attacks

Seismic vulnerability analysis of a high‐rise steel frame structure equipped with novel displacement‐amplified viscoelastic dampers

SummaryThe energy dissipation capacity of conventional viscoelastic dampers (VEDs) cannot be fully exerted due to the relatively small inter‐story displacement of building structures. Thus, a novel VED with a displacement amplification mechanism based on the lever principle is developed in this study to achieve small displacement but high energy dissipation ability. First, the structural layout of an amplified viscoelastic damper (AVED) system is briefly introduced, and then the displacement amplification effect is described in detail. According to the working principle of the AVED and the relationship of force and geometric displacement in an actual frame structure, the restoring force theoretical formula of the corresponding amplified damper is derived. Based on the restoring force of the AVED and in combination with the secondary development function of the ABAQUS unit, a VUEL subroutine suitable for the explicit algorithm is programmed with the FORTRAN language. Then, the correctness of the subroutine is verified through a comparative analysis of the ABAQUS simulation and theoretically calculated results. Consequently, the vulnerability analysis of a high‐rise steel frame structure is conducted by using the incremental dynamic analysis (IDA) method, and the influence of the AVED on the seismic performance of the steel frame structure is quantitatively analyzed from the perspective of probability statistics. The analysis results show that compared with the VED structure, the failure probability of the AVED‐2 and AVED‐3 structures reaching the ultimate failure state at all levels is reduced by approximately 43% and 57%, respectively, and the collapse margin ratio (CMR) of structures under large earthquakes is increased by approximately 35% and 68%, respectively. This indicates that the AVED structures with displacement‐amplified dampers have a better effect on the seismic stability of tall steel frame structures under random seismic excitations. This study aims to provide comprehensive information for the seismic‐resistant design of tall buildings in earthquake‐prone regions.

Vulnerability Assessment of Groundwater Influenced Ecosystems in the Northeastern United States

Groundwater-influenced ecosystems (GIEs) are increasingly vulnerable due to groundwater extraction, land-use practices, and climate change. These ecosystems receive groundwater inflow as a portion of their baseflow or water budget, which can maintain water levels, water temperature, and chemistry necessary to sustain the biodiversity that they support. In some systems (e.g., springs, seeps, fens), this connection with groundwater is central to the system’s integrity and persistence. Groundwater management decisions for human use often do not consider the ecological effects of those actions on GIEs. This disparity can be attributed, in part, to a lack of information regarding the physical relationships these systems have with the surrounding landscape and climate, which may influence the environmental conditions and associated biodiversity. We estimate the vulnerability of areas predicted to be highly suitable for the presence of GIEs based on watershed (U.S. Geological Survey Hydrologic Unit Code 12 watersheds: 24–100 km2) and pixel (30 m × 30 m pixels) resolution in the Atlantic Highlands and Mixed Wood Plains EPA Level II Ecoregions in the northeastern United States. We represent vulnerability with variables describing adaptive capacity (topographic wetness index, hydric soil, physiographic diversity), exposure (climatic niche), and sensitivity (aquatic barriers, proportion urbanized or agriculture). Vulnerability scores indicate that ~26% of GIEs were within 30 m of areas with moderate vulnerability. Within these GIEs, climate exposure is an important contributor to vulnerability of 40% of the areas, followed by land use (19%, agriculture or urbanized). There are few areas predicted to be suitable for GIEs that are also predicted to be highly vulnerable, and of those, climate exposure is the most important contributor to their vulnerability. Persistence of GIEs in the northeastern United States may be challenged as changes in the amount and timing of precipitation and increasing air temperatures attributed to climate change affect the groundwater that sustains these systems.

Analysis of landscape pattern vulnerability in Dasi river basin at the optimal scale

Since the reform and opening up in 1978, the Dasi River Basin within Jinan’s startup area from replacing old growth drivers with new ones (startup area) has experienced rapid urbanization and industrialization, and the landscape pattern has changed significantly, resulting in a series of eco-environmental problems. In order to more accurately identify the vulnerable areas of landscape pattern, understand their cause mechanism and changing laws, and provide a theoretical basis for the implementation of sustainable landscape pattern planning and management in the region. Four Landsat images of 2002, 2009, 2015 and 2020 were taken as data sources, and the optimal granularity of landscape pattern analysis was determined from the perspective of landscape level and class level by using the coefficient of variation method, granularity effect curve and information loss model, and the optimal amplitude was determined by using the grid method and semi-variance function. Then, the landscape vulnerability assessment model was constructed based on the optimal scale, and its spatiotemporal evolution characteristics and spatial autocorrelation were analyzed. The result showed that: (1) The optimal granularity of landscape pattern analysis in this study area was 80 m, and the optimal amplitude was 350 × 350 m. (2) During 2002–2020, the overall vulnerability of landscape pattern in the southern part of the study area showed an increasing trend, while that in the middle and northern parts showed a decreasing trend. (3) The mean values of the vulnerability index of the overall landscape pattern in 2002, 2009, 2015 and 2020 were 0.1479, 0.1483, 0.1562 and 0.1625, respectively, showing an increasing trend year by year. In terms of land use, during 2002–2020, the average vulnerability indices of forestland and built up land increased by 23.18% and 21.43%, respectively, followed by water body and bare land, increased by 12.18% and 9.52%, respectively, while the changes of cropland and grassland were relatively small, increasing by 5.36% and 5.65%, respectively. (4) During 2002–2020, the landscape pattern vulnerability showed a significant spatial positive correlation in terms of spatial distribution. The Low-Low areas were generally transferred from the southeastern and midwestern to the middle and northern, and the High–High areas were mainly transferred from the middle to the southern. Overall, the degree of the spatial agglomeration of the landscape pattern vulnerability showed an increasing trend.

Northeast Atlantic fish stock productivity hindcasts and forecasts from a Bayesian framework reveal pronounced climate‐induced dynamics

AbstractClimate change continues to exert pressure on ocean ecosystems. The fisheries‐related responses, such as altered body growth, recruitment and spatial distribution of the targeted stock(s), have generally been reasonably well investigated. Nevertheless, there are still important knowledge gaps in how biophysical drivers impact stock productivity and thereby sustainable harvest levels. Considering this, we investigated 26 fish stocks in the Northeast Atlantic, a region characterized by accelerated climate change effects and a diverse set of fisheries. A novel, stepwise, Bayesian framework to quantify stock productivity was established to identify shared trends and project future patterns, aiming at determining essential baselines for adaptive fishery management in the face of climate change. Despite variation among large marine ecosystems and stocks, an overall declining trend in productivity over the past four decades was observed, especially in high‐latitude areas. These hindcast results were mainly attributed to higher temperatures posing negative effects on productivity, which was dependent on the stock's thermal preference. Contrastingly, the proxy for food availability – gross secondary production – exhibited less consistent impacts. In the forecast, the applied Shared Socio‐economic Pathways (SSPs) indicated that most stocks are likely to encounter adverse effects, with the worst cases expected to occur under SSP2‐4.5 in the 2050s, and under SSP5‐8.5 in the 2090s. Thus, this study generally not only supports earlier climate vulnerability assessments (‘scorings’) of experts but also provides evidence for revised directional effects under climate change, underlining the complexity of processes affecting stock productivity.

Comparative Analysis of Flood Estimation using Log-Pearson Type III and Gumbel Max Models in the Cauvery River, India

Flooding is one of the most destructive global disasters in scale, geographical extent, property and life loss, and population displacement. The Cauvery River is one of the flood vulnerable rivers in the Peninsular region of India. At-site flood frequency analysis is performed using flow data obtained at the Kodumudi gauged site in the Cauvery River. Log Pearson Type III and Gumbel Max distribution models are used in the present study to estimate peak floods for different return periods. The Central Water Commission provides the annual maximum discharge for the Kodumudi gauged site over 39 years (1980-2018). The goodness of fit test employing the Kolmogorov-Smirnov and Anderson- Darling tests, reveals that Log-Pearson Type III best estimates peak floods in the study area. The peak floods predicted by Log-Pearson Type III for return periods 2, 5, 10, 25, 50, 100, 200, and 500 years are approximately 929, 1886, 2998, 5303, 8002, 11929, 17633, and 29228 cumecs. Hydraulic structures can be designed in the region based on 100-year flood. The present research could help with flooding management approaches, vulnerability analyses, and hydraulic structure design in the study region.

Optimal design of chevron braced friction damper for mainshock–aftershock vulnerability control

This study proposes the optimum design of chevron braced friction dampers (CBFDs) for the vulnerability control of steel moment–resisting frames (SMRFs) under mainshock-aftershock (MS-AS) sequences. First, the optimum parameters of the CBFD systems installed in the stories of an inelastic SMRF are found through minimizing the maximum damage index of stories averaged over seven scaled earthquake excitations. The uniform distribution of the story damage along the height of the controlled SMRF is adopted as constraint in the optimization procedure. The damage index is calculated based on the Park-Ang damage model which is expressed based on a linear combination of deformation, moment, and absorbed hysteretic energy of structural elements imposed by an earthquake excitation. Results reveal that the optimized CBFDs-equipped SMRF exhibits better distribution of the story damage than that of the uncontrolled SMRF. Finally, the vulnerability assessment of the optimized CBFDs-equipped SMRF under MS and MS-AS ground motions is investigated by the fragility curves. The fragility assessment emphasize that the optimized CBFDs effectively mitigate the seismic vulnerability of the controlled SMRF under MS-AS sequences at different damage states.

Assessment of Groundwater Vulnerability to Seawater Intrusion Using GALDIT, SITE and SIVI Methods in Laspias River Coastal Aquifer System, NE Greece

This paper presents the investigation of groundwater vulnerability to seawater intrusion of the aquifer system in the coastal area of Laspias River, NE Greece, for the year 2023, by applying the GALDIT, SITE and SIVI methods, in the context of the groundwater management of the area. The relevant research works include the collection and analysis of data and information regarding the geological and geomorphological environment, as well as the hydrogeological system of the area. The calculation of the GALDIT, SITE and SIVI indices values is described, and the results from the application of the methods are presented, as well as the design of relevant groundwater vulnerability maps of the study area. This paper concludes with findings and proposals useful for the reliable assessment of the hydrogeological regime of the wider study area.

Combining CENTURY model and vulnerability assessment index to estimate aboveground biomass and ecological vulnerability of grassland: An analysis in Northwest Sichuan Plateau

Evaluating the impact of climate change on grassland productivity using grassland ecological models is of great significance for the sustainable use of grasslands. Based on meteorological, soil, and grassland data, this study employed the Grassland Ecosystem Model (CENTURY) to scrutinize the spatiotemporal distribution characteristics of above-ground biomass (AGB) of grasslands in the northwest Sichuan Plateau (NWSP) and established a spatial distribution pattern of grassland vulnerability levels in the NWSP. Utilizing five on-site verification points, the CENTURY model worked well in simulating the AGB of grasslands in the NWSP and was suitable for investigating the impact of climate change on grassland productivity in the NWSP. Simulation outcomes revealed a zonal distribution pattern of the annual average AGB in grasslands across the NWSP, with the central region exhibiting higher levels surpassing 800 g m−². From 1961 to 2020, the AGB of grasslands showed a significant increase trend, with growth rates ranging from 14.2 to 25.9 g m−2·(10a)−1. Overall, the northern and central regions of the NWSP experienced substantial climate impacts, coinciding with a marked increase in biomass. From 1961 to 2020, the overall vulnerability of grasslands in the NWSP was relatively low, with areas exhibiting moderate or lower vulnerability levels accounting for 83.8 %. The overall spatial distribution pattern showed low vulnerability in the north and central regions, and high vulnerability in the eastern and southwestern edges.

A vehicle firmware security vulnerability: an IVI exploitation

AbstractIn the last years, the increasing vehicular technology has led to a surge in cybersecurity attacks, particularly regarding connected vehicles and their vulnerable infotainment systems. This paper explores the vulnerabilities within an In-Vehicle Infotainment (IVI) system firmware, focusing on the Gen5W_L multimedia device utilized in Hyundai, Kia, and Genesis vehicles. Leveraging reverse engineering techniques, the study uncovers several security issues within the firmware, allowing for the creation and installation of custom firmware. The paper introduces Chimaera, a reverse engineering attack targeting the IVI system firmware, which exploits a vulnerability introduced by statically compiling the mbedtls library. After a reverse engineering analysis and injecting malicious assembly code directly in the IVI firmware, the attack enables the extraction of sensitive information from the firmware files like the cryptographic keys to install a customized firmware. The research shows that exploiting these vulnerabilities facilitates the installation of insecure firmware, granting attackers unauthorized access to vehicle functionalities. This includes the possibility to inject CAN bus messages, potentially compromising critical vehicle systems such as radio controls and safety features. The findings underscore the need for robust cybersecurity measures within automotive systems and highlight the significance of vulnerability assessment to mitigate security risks in connected vehicles.

Precondition Study of a Sponge City: Comprehensive Assessment of the Vulnerability of an Urban Rainwater System

This study introduces the concept of urban rainwater system vulnerability and identifies the indicator factors that affect the vulnerability of rainwater systems. Using the analytic hierarchy process (AHP), an index system for the vulnerability assessment of the rainwater system was established, and a vulnerability assessment model for the rainwater system was constructed. By integrating vulnerability degree, recurrence period, and water depth of ponding, a vulnerability assessment framework for urban rainwater systems was developed. Taking a newly developed urban area in the Suzhou High-Tech Zone as an example, we calculated the vulnerability degree of the urban rainwater system in this area to be 0.6497, indicating a high level of vulnerability and poor system safety. When encountering rainfall with a recurrence period p > 5 years, the city is likely to experience severe waterlogging. Through the analysis and evaluation of the rainwater system’s vulnerability, while clarifying the current state of the rainwater system, it can provide a scientific reference basis for the system’s upgrade, transformation, and optimized operation and management. Although the selection of factors may not be entirely comprehensive, this method allows for adjustments based on the composition and operation of different rainwater systems.

Building pose detection for the characterization of reinforced concrete buildings

SummaryThe automated identification of building characteristics for seismic vulnerability remains a challenge for governments due to the high number of buildings in cities. The diverse architectural styles of these buildings complicate the automated identification of building information (e.g., number of stories, structural system, and material type). Deep learning techniques lose accuracy as they generalize information, while the visual contents of a building exhibit a considerable range and diversity. This study leverages the pose detection technique to tackle such issues by focusing on a common construction style: reinforced concrete buildings representing columns, beams, or floors on the façade. With an aim to enable the assessment of seismic vulnerability, the technique developed herein is conceived for buildings with up to six stories that are more likely to be moment‐frame buildings. The AI‐enabled proposed framework starts with collecting building images and categorizing those containing this specific building type. A bounding box detector is then used to isolate building facades, for the subsequent identification of the structural frame with the High‐Resolution Network (HR‐Net). For demonstration, we illustrate this technique by identifying the structural frame on concrete buildings with a sample dataset developed based on buildings found in Mexico City in a pre‐earthquake event state.

Framework development for the physical vulnerability assessment index of hand-dug Wells in Are-Ekiti, Southwestern Nigeria.

The article presents a comprehensive framework for assessing the physical vulnerability of hand-dug wells within the Are Community, Southwestern Nigeria. The study spans from March to April 2023 and meticulously examines 90 wells, focusing on critical parameters such as well collar, well cover, and well lining information. The analysis reveals significant variations in well collar construction materials and dimensions, emphasizing the community's adaptive strategies. The Well Collar Height Index (WCi), Well Cover Index (WCOi), Well Lining Index (WLi), and the derived Vulnerability Index categorize wells into vulnerability classes, offering a nuanced understanding of susceptibility levels. Notably, the study identifies wells with Very High vulnerability that demand urgent attention, as well as wells with effective protective measures categorized as Very Low vulnerability. The article emphasizes the need for a nuanced understanding of local practices and materials, highlighting the variability in well collar construction. It discusses the implications of well cover conditions and the critical role of well linings in assessing groundwater vulnerability. The Vulnerability Index combines these parameters, guiding targeted interventions based on risk severity. The study lays the groundwork for future interventions to enhance the safety and sustainability of water sources within the Are Community. It recommends immediate comprehensive measures for highly vulnerable wells, ongoing monitoring, community engagement, and knowledge sharing. The future scope includes incorporating geochemical analysis, targeted interventions, regular maintenance, community training, and exploring alternative water sources for sustainable improvements.

Variable climatic conditions dominate decreased wetland vulnerability on the Qinghai‒Tibet Plateau: Insights from the ecosystem pattern-process-function framework

Wetlands are of global importance in providing essential ecosystem services but are also sensitive to climate change and human activities. Monitoring and assessing wetland vulnerability are crucial for ecological conservation and management strategies. However, the framework of wetland vulnerability assessment and the underlying mechanisms have not been well studied. In this study, the spatiotemporal variations in wetland vulnerability on the Qinghai‒Tibet Plateau (QTP) between 1990 and 2020 were investigated based on the ecosystem pattern-process-function framework. The key driving factors were identified by partial least squares structural equation modelling (PLS-SEM) and multiscale geographically weighted regression (MGWR) models. Our results showed that the wetland ecosystem pattern index (EPI), ecosystem process index (EPOI), ecosystem function index (EFI), and wetland vulnerability index (WVI) all demonstrated an increasing pattern from northwest to southeast. Between 1990 and 2020, the mean WVI values gradually decreased from 0.616 to 0.588, indicating a steady improvement in the wetland ecosystem on the QTP. Rapid urbanization increased the EPOI, while rugged topography increased both the EPI and EPOI, and the increase in hydrological abundance enhanced the EFI, which in turn contributed to an increase in the WVI. Conversely, climatic conditions led to a reduction in the EPI, which in turn resulted in a significant decrease in the WVI. Therefore, although urbanization and topographical and hydrological factors have somewhat exacerbated the WVI on the QTP, variable climatic conditions have driven the decline in wetland vulnerability in the last three decades. Furthermore, our results indicated that the proposed framework could provide a comprehensive approach for wetland vulnerability assessment and useful implications for wetland conservation and management.

A rapid approach to assessing the vulnerability of Mozambican fisheries’ species to climate change

Mozambique is amongst the most vulnerable of Western Indian Ocean (WIO] countries to the impacts of climate change on its marine fisheries. We used rapid assessment methods to evaluate sensitivity, exposure and vulnerability of fisheries species to climate change, appropriate for data-deficient, developing countries in the region. Species were selected based on their importance in industrial and artisanal fisheries’ landings, further prioritized by local experts. Species’ attributes likely to be sensitive to climate change were identified and scored, utilizing life history or biological characteristics. Sea Surface Temperature (SST] was the most prominent climate exposure factor and for which we could confidently predict likely future change. Most species had low or medium overall sensitivity to climate change, with only eight considered highly sensitive. Climate exposure (SST] scores were high off northern Mozambique, while the central and southern regions were generally of medium exposure. Ten species received a High vulnerability score, 14 were Medium, and 16 had a Low vulnerability score. The highly vulnerable species were all fishes, apart from one crustacean; 4 of the 9 were strongly estuarine-associated; the most vulnerable species was the parrotfish Scarus ghobban. This is the first attempt to use a rapid, semi-quantitative, specialist- and trait-based vulnerability assessment of the anticipated effect of climate change on marine fisheries species in the WIO. Challenges experienced were data paucity, limited resources, the large study area, and the complex oceanography of the region. However, a simple methodology was developed, derived from efforts elsewhere, and which can be used to undertake similar assessments for other WIO countries. Raised awareness of climate change among small-scale fishing communities is a necessity, combined with adaptation by promoting fisheries co-management. Also required is support from government to ensure that people can be flexible to change.

Electrical resilience assessment of a building operating at low voltage

Resilience is becoming increasingly important in power systems, microgrids (MG) and buildings. It evaluates their performance against disruptive events. The approaches mainly correspond to high-impact, low-probability events such as natural disasters and intentional attacks affecting the electrical systems infrastructure. However, resilience can encompass medium and low-impact events such as minor civil structural accidents, light faults and supply disturbances. Some resilience assessment advances are in buildings at the low-voltage (LV) level. They include vulnerability to natural disasters, reliability of supply, and service quality. These works usually use approaches independent of each other, leaving a gap between their relationship and interpretation. Therefore, there is a need to consolidate a resilience assessment strategy to guide the analysis of vulnerabilities and strengths in the same direction. This paper proposes a comprehensive approach to evaluate electrical resilience for buildings. It compiles quantitative strategies for studying electrical resilience, focusing on LV systems. It proposes a methodology for integrating the electrical system infrastructure's vulnerability, the supply's continuity and the voltage service's quality. Implementing this approach in a university building equipped with smart metering demonstrates the effectiveness of the proposed methodology for assessing electrical resilience. The results show a comprehensive resilience analysis and the possibility of extending the methodology to MG and LV distribution networks.

Vulnerability assessment of Taxus wallichiana in the Indian Himalayan Region to future climate change using species niche models and global climate models under future climate scenarios

Vulnerability assessment of Taxus wallichiana in the Indian Himalayan Region to future climate change using species niche models and global climate models under future climate scenarios

A novel framework for the spatiotemporal assessment of urban flood vulnerability

Considering the pressing Urban Flood (UF) challenges faced by developing countries, the assessment of Urban Flood Vulnerability (UFV) assumes paramount importance in comprehending the detrimental impacts of UF on urban environments, thereby facilitating effective UF management. Addressing a notable gap in previous UFV research, which predominantly focused on spatial characteristics while overlooking temporal dynamics, we introduce a novel framework for spatiotemporal UFV assessment, by presenting a multiplicative equation to elucidate the interaction between Urban Flood Susceptibility (UFS) and Vulnerable Entities (VE). Employing this framework in the Great Bay Area (GBA), by considering the composition of the UFV database, we leveraged Machine Learnings and the Urban Vitality Index for quantifying the UFS and VE, respectively. SHapley Additive exPlanations was employed to quantify the local contributions of various factors to UFV. We found (1) a discernible upward trajectory in UFV across the GBA from 2012 to 2020, coupled with an expansion in spatial scope, indicative of persistent challenges in the future, and (2) the impervious surface percentage emerges as the primary contributor to UFV, exhibiting spatial heterogeneity reflective of regional environments. We believe this study has the potential to significantly contribute to addressing UF challenges and fostering the development of sustainable cities.

PROPUESTA DE ANÁLISIS DE VULNERABILIDAD SOCIAL A LA CALIDAD DEL AIRE BASADO EN SISTEMAS DE INFORMACIÓN GEOGRÁFICA (SIG) Y SU APLICACIÓN EN VITORIA-GASTEIZ

Despite the fact that air pollution is one of the main environmental concerns in Europe, causing more than 400,000 premature deaths each year, and affecting certain groups in particular, there are no known specific analyses of the social vulnerability of this pollutant that would allow us to guide policies to improve air quality in the different municipalities. For this reason, a first approximation of an analysis of social vulnerability to air quality has been developed to guide municipal policies in this area. The proposal proposes a zonal analysis of exposure in GIS in which the modelled information on air pollution is cross-referenced with the location of buildings housing the main vulnerable groups. The buildings have been classified according to the type of vulnerable population using them and their degree of vulnerability. The results indicate that this proposal allows a visual and simple identification of the levels of air pollution to which each sensitive building is exposed, facilitating the possible identification of those with levels higher than the current legislation or the recommendations of the WHO. Based on the exposure on the façade of the buildings, the proposal presented allows four levels of severity with respect to air pollution to be established, establishing the first steps of a prioritisation of improvement needs. This first prioritisation can be adjusted according to the type of population housed in each sensitive building and the vulnerability of the groups it houses. The proposed GIS-based social vulnerability analysis is particularly interesting when available resources are scarce, but it must be complemented by detailed analyses of the social vulnerability of the prioritised sensitive buildings before the implementation of improvement actions. Keywords: urban planning, social vulnerability, social vulnerability, air quality, GIS, modelling