Low Vulnerability Research Articles

APPLICATION OF K-MEANS AND FUZZY C-MEANS ALGORITHMS TO DETERMINE FLOOD VULNERABILITY CLUSTERS (CASE STUDY: KUTAI KARTANEGARA REGENCY)

Flooding show situation where areas that are not usually inundated, such as farmland and settlements, and city district areas, become inundated due to water. Floods can to occur when the flow of water on rivers or waste channels overrun its normal measurements. This study describes the K-Means and Fuzzy C-Means Algorithm methods for clustered flood-prone areas built on Districts in Kutai Kartanegara Regency. This research begins with data collection in the character of rainfall, land elevation, the number of victims affected, the quantity of damaged houses, the quantity of damage to facilities and the quantity of flood events. Before the data is processed using these two methods, data normalization will be carried out in a dataset which aims to shape the data into positional values from the same range. K-Means and Fuzzy C-Means are accustomed to identifying groups in each sub-district in Kutai Kartanegara Regency that have a level of vulnerability to floods. At this stage, 3 initial clusters were carried out, namely high, medium, and low vulnerability clusters. The validity test produces a Silhouette Index value of 0.574283589 and a Partition Coefficient Index of 0.78905. The outcome of the K-Means method with the standard deviation within and between clusters are 0.5131 and the Fuzzy C-Means method for the standard deviations within and between clusters is 0.3489. based uppon value of the silhouette index, partition coefficient index and standard deviation within and between clusters it results that Fuzzy C-Means is the best method of this study.

Predicting the dynamics of per- and polyfluoroalkyl substances in coastal regions of Africa: vulnerability index and adverse ecological pathways from remote-sensed variables.

This study aimed to predict the dynamics of per- and polyfluoroalkyl substance (PFAS) contamination and ecological vulnerability within coastal regions of Africa utilizing time-averaged remote-sensed data patterns from 2020 to 2023. The analysis identified PFAS contamination hotspots along the coast of Africa, particularly in western Africa around Nigeria and in areas spanning Equatorial Guinea and Guinea-Bissau, with risk influenced by eastward wind patterns, overland runoff, and elevated aerosol optical depth (AOD) values. Regional trends indicated that variations in solar energy absorption and surface air temperature could influence PFAS dynamics in North Africa, South Africa, East Africa, and West Africa. In North Africa, intermediate overland runoff and lower sea-surface temperatures were observed. In South Africa, there were intermediate runoff levels and warmer sea-surface temperatures. East Africa experienced intermediate runoff as well. In West Africa, there was increased susceptibility to high overland runoff and aerosol-related PFAS contamination. From the weighted vulnerability index, significant disparities in environmental conditions across African coastal regions revealed that North Africa had relatively lower vulnerability, while West Africa had the highest susceptibility to per- and polyfluoroalkyl substance (PFAS) contamination. This study emphasizes the necessity for region-specific vulnerability index models and targeted mitigation strategies to address diverse ecological and health risks from PFAS contamination along the African coast. Regional and international collaboration, spearheaded by organizations such as the AU and ECOWAS, is essential, with tailored policies aligned with the SDGs, Agenda 2063, and NEPAD crucial for effective environmental management, urging policymakers to prioritize cooperation and resource sharing for comprehensive sustainability goals.

Characteristics of healthcare personnel with SARS-CoV-2 infection: 10 emerging infections program sites in the United States, April 2020-December 2021.

Understanding characteristics of healthcare personnel (HCP) with SARS-CoV-2 infection supports the development and prioritization of interventions to protect this important workforce. We report detailed characteristics of HCP who tested positive for SARS-CoV-2 from April 20, 2020 through December 31, 2021. CDC collaborated with Emerging Infections Program sites in 10 states to interview HCP with SARS-CoV-2 infection (case-HCP) about their demographics, underlying medical conditions, healthcare roles, exposures, personal protective equipment (PPE) use, and COVID-19 vaccination status. We grouped case-HCP by healthcare role. To describe residential social vulnerability, we merged geocoded HCP residential addresses with CDC/ATSDR Social Vulnerability Index (SVI) values at the census tract level. We defined highest and lowest SVI quartiles as high and low social vulnerability, respectively. Our analysis included 7,531 case-HCP. Most case-HCP with roles as certified nursing assistant (CNA) (444, 61.3%), medical assistant (252, 65.3%), or home healthcare worker (HHW) (225, 59.5%) reported their race and ethnicity as either non-Hispanic Black or Hispanic. More than one third of HHWs (166, 45.2%), CNAs (283, 41.7%), and medical assistants (138, 37.9%) reported a residential address in the high social vulnerability category. The proportion of case-HCP who reported using recommended PPE at all times when caring for patients with COVID-19 was lowest among HHWs compared with other roles. To mitigate SARS-CoV-2 infection risk in healthcare settings, infection prevention, and control interventions should be specific to HCP roles and educational backgrounds. Additional interventions are needed to address high social vulnerability among HHWs, CNAs, and medical assistants.

The impact of air pollution on household vulnerability to poverty: An empirical study from household data in China

Understanding the relationship between air pollution and poverty is essential for improving livelihoods and fostering common prosperity. While existing studies have concentrated on the impact of extreme climate and natural disasters on poverty, the adverse effects of air pollution are neglected. Using the China Family Panel Studies (CFPS) from 2016 to 2018, this study investigates air pollution's effect on household vulnerability to poverty, including the mechanisms and heterogeneity. Results shows that air pollution significantly heightens household vulnerability to poverty. This effect stems from air pollution lowering incomes and increasing healthcare burden. Heterogeneity analysis shows that air pollution negatively impacts households with low wealth, poorly educated, weak social networks, and those in developing, non-coastal, and high-terrain cities. Furthermore, air pollution more severely affects households with high consumption volatility and low wealth compared to those with low vulnerability. We also discover that the adverse effects of air pollution on household vulnerability to poverty diminish with increased physical capital. Local governments are encouraged to intensify efforts in reducing emissions through improved environmental regulations, protecting residents from pollution-induced harm.

Low functional redundancy revealed high vulnerability of the subtropical evergreen broadleaved forests to environmental change

Anthropogenic-induced environmental changes threaten forest ecosystems by reducing their biodiversity and adaptive capacity. Understanding the sensitivity of ecosystem function to loss of diversity is vital in designing conservation strategies and maintaining the resilience of forest ecosystems in a changing world. Here, based on unique combinations of ten functional traits (termed as functional entities; FEs), we quantified the metrics of functional redundancy (FR) and functional vulnerability (FV) in 250 forest plots across five locations in subtropical evergreen broadleaved forests. We then examined the potential impacts of species loss on functional diversity in subtropical forest communities along environmental gradients (climate and soil). Results showed that the subtropical forests displayed a low level of functional redundancy (FR < 2). Over 75 % of the FEs in these subtropical forest communities were composed of only one species, with rare species emerging as pivotal contributors to these vulnerable FEs. The number of FEs and functional redundancy both increased with the rise in species richness, but functional vulnerability decreased with increasing species richness. Climatic factors, especially mean diurnal range, played crucial roles in determining the functions that the forest ecosystem delivers. Under variable temperature conditions, species in each plot were packed into a few FEs, leading to higher functional redundancy and lower functional vulnerability. These results highlighted that rare species contribute significantly to ecosystem functions and the highly diverse subtropical forest communities could show more insurance effects against species loss under stressful environmental conditions.

Utilizing Geological and Geoelectrical methods in a GIS-based DRASTIC model of the Probable Groundwater Vulnerability in the Southern Nigerian Raffia Metropolis of Ikot Ekpene and its Surroundings

The city of Ikot Ekpene is facing a significant issue with groundwater contamination. This is due to the rising amount of home and industrial waste caused by the increasing human population and various business operations in the area. This study seeks to evaluate the susceptibility of groundwater in the metropolis of Ikot Ekpene and its surrounding areas in southern Nigeria. It will utilize integrated geoelectrical and geological approaches within the GIS-based DRASTIC model. A total of twenty vertical electrical soundings (VES) were conducted in the region using the Schlumberger array. Based on the geological drilling data, the interpretation of the VES data suggests that the area consists of 3-4 geoelectric layers. The lithological succession in the area exhibits a range of sediment types, including fine and coarse sand as well as gravelly sands. Additionally, there are localized occurrences of clay intercalations. The third geoelectric layer, located at a depth of 9.0–86.6 m, is the primary aquifer that can be utilized in the region. The DRASTIC model included seven environmental parameters, including depth to the water table, net recharge, aquifer medium, topography, impact of vadose zone, and hydraulic conductivity, with the purpose of conducting a vulnerability assessment. The assessment of groundwater vulnerability ratings (GVR) reveals that 75% of the research region is classified as high vulnerability, 20% as moderate vulnerability, and the remaining 5% as low vulnerability. The studied area is predominantly characterized by moderate to high Groundwater Vulnerability Rating (GVR), which is likely attributed to the generally gentle topography and the presence of highly permeable geomaterials in the upper levels of the water table.

Biodiversity and Wetting of Climate Alleviate Vegetation Vulnerability Under Compound Drought‐Hot Extremes

AbstractGlobal warming has intensified the intensity of compound drought‐hot extremes (CDHEs), posing more severe impacts on human societies and ecosystems than individual extremes. The vulnerability of global terrestrial ecosystems under CDHEs, along with its key influencing factors, remains poorly understood. Based on multiple remote sensing data, we construct a Vine Copula model to appraise vegetation vulnerability under CDHEs, and attribute it to climatic and biotic factors for five different vegetation types. High vulnerability is detected in central and southern regions of North America, eastern and southern regions of South America, Southern Africa, northern and western Europe, and northern and eastern Australia. The drier the climate, the higher will be the vulnerability. Furthermore, biodiversity and biomass are key biotic factors influencing the vulnerability of various vegetation types, such that ecosystems with richer biodiversity and higher biomass have lower vulnerability to CDHEs. The findings deepen understanding of terrestrial ecosystem response to CDHEs.

Productivity susceptibility analysis in extremely data-poor scenarios: The case of Peruvian coastal groundfish

Coastal small-scale fisheries remain largely unassessed and unregulated worldwide, which leads to a high risk of overfishing. Availability and quality of data are major barriers to performing model-based assessments, particularly in low and middle-income countries. In that context, alternative assessment methods are key to defining priorities, as well as prompting and guiding management actions. In this study, we assessed the vulnerability to overfishing of 10 extremely data-poor species of coastal groundfish in Peru, by applying an adapted Productivity Susceptibility Analysis (PSA). We classified fisheries-related Susceptibility attributes and streamlined a process to assess and integrate multiple fisheries and gears into a single score for each attribute. The data quality scores regarding productivity and susceptibility were between “limited” and “no data”, across all stocks. Therefore, expert knowledge was key for completing the assessment. Stocks of four species presented extremely high Vulnerability to overfishing: broomtail grouper (V=2.57), grape-eye seabass (V=2.50), pacific goliath grouper (V=2.28) and galapagos sheephead wrasse (V=2.24). Three showed high Vulnerability to overfishing: black snook (V=2.13), harlequin wrasse (V=2.05) and chino (V=2.01). Two showed medium Vulnerability to overfishing: mulata (V=1.89) and pacific beakfish (V=1.89). Only the stock of bumphead parrotfish showed low Vulnerability to overfishing (V=1.73). We contrasted the resulting Vulnerability scores with the limited available information on the statuses of these stocks, to evaluate the accurateness of the overfishing probability thresholds proposed in PSA literature. We found that Vulnerability scores were mostly consistent with contrasted information and that the thresholds remain useful to inform fisheries management in extremely data-poor contexts. Our results shed light on the need for the implementation of fishing regulations and the generation of biological and fishery-related data on coastal groundfish in Peru.

Mangrove untuk Ketahanan Iklim berdasarkan Indeks Kerentanan Pesisir, Penerapan di Mempawah, Kalimantan Barat

Coastal areas are particularly vulnerable to climate change. The primary objective of this study is to use the Geographic Information System (GIS) approach to assess the level of vulnerability in the coastal area of Mempawah Regency, West Kalimantan, Indonesia, by utilizing the Coastal Vulnerability Index (CVI) and analyzing the role of mangrove land cover in explaining the coastal vulnerability based on land cover characteristics. From 41 surveyed grids, a substantial 65.83% are classified under the category of very low vulnerability, while 34.14% fall within the range of low vulnerability, in Mempawah. The validation of the mangroves' role as a defense mechanism in mitigating climate phenomena within coastal areas was validated through various approaches such as Normalized Difference Vegetation Index (NDVI) and land cover

Association of county-level provider density and social vulnerability with colorectal cancer-related mortality

BackgroundHealth care providers play a crucial role in increasing overall awareness, screening, and treatment of cancer, leading to reduced cancer mortality. We sought to characterize the impact of provider density on colorectal cancer population-level mortality. MethodsCounty-level provider data, obtained from the Area Health Resource File between 2016 and 2018, were used to calculate provider density per county. These data were merged with county-level colorectal cancer mortality 2016–2020 data from the Centers for Disease Control and Prevention. Multivariable regression was performed to define the association between provider density and colorectal cancer mortality. ResultsAmong 2,863 counties included in the analytic cohort, 1,132 (39.5%) and 1,731 (60.5%) counties were categorized as urban and rural, respectively. The colorectal cancer-related crude mortality rate was higher in counties with low provider density versus counties with moderate or high provider density (low = 22.9, moderate = 21.6, high = 19.3 per 100,000 individuals; P < .001). On multivariable analysis, the odds of colorectal cancer mortality were lower in counties with moderate and high provider density versus counties with low provider density (moderate odds ratio 0.97, 95% confidence interval 0.94–0.99; high odds ratio 0.88, 95% confidence interval 0.86–0.91). High provider density remained associated with a lower likelihood of colorectal cancer mortality independent of social vulnerability index (low social vulnerability index and high provider density: odds ratio 0.85, 95% confidence interval 0.81–0.89; high social vulnerability index and high provider density: odds ratio 0.93, 95% confidence interval 0.89–0.98). ConclusionRegardless of social vulnerability index, high county-level provider density was associated with lower colorectal cancer-related mortality. Efforts to increase access to health care providers may improve health care equity, as well as long-term cancer outcomes.

Oral Delivery of Liraglutide-Loaded Zein/Eudragit-Chitosan Nanoparticles Provides Pharmacokinetic and Glycemic Outcomes Comparable to Its Subcutaneous Injection in Rats.

Liraglutide (LIRA) is a glucagon-like peptide-1 (GLP-1) receptor agonist renowned for its efficacy in treating type 2 diabetes mellitus (T2DM) and is typically administered via subcutaneous injections. Oral delivery, although more desirable for being painless and potentially enhancing patient adherence, is challenged by the peptide's low bioavailability and vulnerability to digestive enzymes. This study aimed to develop LIRA-containing zein-based nanoparticles stabilized with eudragit RS100 and chitosan for oral use (Z-ERS-CS/LIRA). These nanoparticles demonstrated a spherical shape, with a mean diameter of 238.6 nm, a polydispersity index of 0.099, a zeta potential of +40.9 mV, and an encapsulation efficiency of 41%. In vitro release studies indicated a prolonged release, with up to 61% of LIRA released over 24 h. Notably, the nanoparticles showed considerable resistance and stability in simulated gastric and intestinal fluids, suggesting protection from pH and enzymatic degradation. Pharmacokinetic analysis revealed that orally administered Z-ERS-CS/LIRA paralleled the pharmacokinetic profile seen with subcutaneously delivered LIRA. Furthermore, in vivo tests on a diabetic rat model showed that Z-ERS-CS/LIRA significantly controlled glucose levels, comparable to the results observed with free LIRA. The findings underscore Z-ERS-CS/LIRA nanoparticles as a promising approach for oral LIRA delivery in T2DM management.

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.

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.

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.

The Association Between Food Insecurity and Census Tract-Based Indexes in an Urban Academic Reproductive Clinic: Can Residence Predict Food Insecurity in Reproductive Patients? [ID 2683613

INTRODUCTION: Identifying food-insecure patients remains a priority in reproductive clinics given nutrition’s effect on maternal health. We sought to determine the association between self-reported food insecurity with census tract-based indexes including the Childhood Opportunity Index (COI), Social Vulnerability Index (SVI), and the U.S. Department of Agriculture (USDA) low-income and low-food access areas (LILAs), to identify which indexes can help identify at-risk patients. METHODS: This is a cross-sectional survey study (UMBHP-00099693) of patients presenting for reproductive care at one urban academic center. Food insecurity was scored as greater than 0 on the 6-Item USDA Food Security Module, and living within a LILA was collected from the 2019 USDA database. We categorized social vulnerability as moderate/low/very low vulnerability or high/very high vulnerability using the SVI. We categorized childhood opportunity using the COI as very low/low and moderate/high/very high. RESULTS: Of the 179 participants in the study, 84 (47%) reported food insecurity. The following proportions lived in a: LILA 96 (54%); high/very high vulnerability tract 138 (77%); and low/very low childhood opportunity (CO) tract 144 (86%). Living within a LILA was associated with an increased odds of experiencing food insecurity (odds ratio [OR] 1.8 [1.0, 3.4]). Living within a high/very high vulnerability tract was not significantly associated with food insecurity (OR 1.2 [0.6, 2.4]), nor was living within a low/very low CO tract (OR 1.6 [0.8, 3.5]). CONCLUSION: Residence within a LILA could be associated with food insecurity in patients seeking reproductive care, which can inform the development of future clinical and geographic interventions. As one in two patients were food insecure, we recommend universal screening of all patients at reproductive appointments.

Assessment of Flood Vulnerability Levels in the Lower Orashi River, Niger Delta Region, Nigeria

Flooding is one of the most frequent and widespread of all environmental hazards and of various types and sizes. This study investigated the flood vulnerability levels in the lower Orashi River, Niger Delta Region, Nigeria. The study considered the landuse, soil texture, elevation, slope, stream power index (SPI), rainfall, drainage density and proximity to river channels as factors determining flood. The components of these factors were reclassified as lowly, moderately and highly vulnerable areas with assigned numbers 1, 2 and 3 respectively. All the maps were overlaid using the UNION module for the final flood vulnerability levels. Descriptive statistics and inferential statistics were used in the data analysis. Results showed that the very low flood vulnerability levels covered spatial extent of 244.4 sq km (7.31%), low flood vulnerability covered 901.31 sq km (26.95%), moderate flood vulnerability level 1240.18 sq km (37.08%), high flood vulnerability level 846.47 sq km (25.31%) and very high had 112.11 sq km (3.35%). It can be concluded that more than 65% of the entire lower Orashi River are highly and moderately vulnerable to flood. It is therefore recommended among others that periodic studies should be carried out in lower Orashi River to monitor the factors that can cause flood in the area.

Pemetaan Kerawanan Bencana Longsor Menggunakan Teknik UAV (Studi Kasus: Jalur Sitinjau Lauik Padang – Solok)

One of the most common natural disasters in Indonesia is landslides Heavy rains have caused several landslides in various regions, causing a large impact every year. Landslides caused by rainfall have also become a global problem in many regions, leading to large-scale landslides. Landslides that occur in Sitinjau Lauik, Padang City are influenced by high rainfall with very steep slopes (70˚-80˚), making this area very prone to landslides. One of the techniques used in mapping landslide vulnerability is the Unmanned Aerial Vehicle (UAV) technique, which is a flying machine controlled by a remote controller. The data obtained will be processed using ArcGIS with Weighted Overlay technique, and factors affecting landslides have been conditioned based on Multi Influencing Factor (MIF). This research aims to achieve: 1) the landslide vulnerability level of Sitinjau Lauik Padang-Solok, 2) determine the landslide prone zones in Sitinjau Lauik. The type of research used in this research is quantitative research with spatial approach. The data required are primary data and secondary data. Primary data consists of aerial photographs taken using drones and processed to produce slope, elevation, aspect, and TWI. The secondary data used is the Landsat 8 image in 2023 which is used to determine the vegetation index. This research resulted in 1) The landslide vulnerability level of Sitinjau Lauik is divided into four classes, namely, low landslide vulnerability level with an area of 4342m or 10.81%. Medium landslide vulnerability level with an area of 24575m or 61.16%. High landslide vulnerability level with an area of 11,294m or 28%. And very high landslide vulnerability level with an area of 14m or 0.03%. 2) Landslide vulnerability zonation based on slope condition is divided into 3 zones: Zone A with an area of 20,901m, Zone B with an area of 4642m. And Zone C with an area of 14,614m.

Fuzzy comparison of drought vulnerability based on the analytical hierarchy process

The vulnerability represents the level to which any ecosystem experiences impairment due to natural distress. One such distress is drought, a prolonged phase of deficient rainfall that causes the depletion of water resources. The possibility of the influences of drought principally depends on the vulnerability of the affected area. The predominantly arid climate of Pakistan and the dependence of its economy on agriculture make it vulnerable to climate change. Rahim Yar Khan and Tharparkar have similar environmental conditions, but Tharparkar experiences more droughts. Vulnerability factors observed by the two districts among the regions are different even with similar climate conditions. The system vulnerability to drought was observed for two districts by using the analytical hierarchy process (AHP) and drought vulnerability index (DVI). The drought vulnerability index (DVI) was used to assess the meteorological, agricultural, hydrological, and socio-economic indicators to build the hierarchy for these inconsistence factors and evaluate the most vulnerable and affecting cause among the meteorological, agricultural, hydrological, and socio-economic indicators. The selected measures specify the hypotheses and the relativity of the indicators to the overall vulnerability of the system. The evaluated weights for each variable are derived from the analytical hierarchy process by comparing the variables of the selected indicators. Due to different meteorological, agricultural, and socio-economic conditions, the weights for the DVI were not the same in both study districts, i.e., Rahim Yar Khan and Tharparkar. The classification of vulnerability depending upon the drought vulnerability index with AHP suggests that the DV indexation is favorable in assessing the regional drought vulnerability. The drought vulnerability assessment of Tharparkar indicates that Tharparkar is highly vulnerable to drought, i.e., DVI = 0.066, as it is highly dependent on irrigation resources for its agriculture and livestock. The unavailability of hydrological resources has increased the drought vulnerability of the Tharparkar, which corresponds to a high level of agricultural damage due to droughts. However, the district of Rahim Yar Khan with developed irrigation resources has a lower drought vulnerability index (DVI = 0.011). It is necessary for Tharparkar to establish countermeasures to mitigate the drought vulnerability through the development of water resources. Future studies are needed to be focused on more indicators for assessing particular drought vulnerability issues in order to reduce the drought vulnerability of Tharparkar.

Groundwater salinization risk assessment using combined artificial intelligence models.

Assessing the risk of groundwater contamination is of crucial importance for the management of water resources, particularly in arid regions such as Menzel Habib (south-eastern Tunisia). The aim of this research is to create and validate artificial intelligence models based on the original DRASTIC vulnerability methodology to explain groundwater salinization risk (GSR). To this end, several algorithms, such as artificial neural networks (ANN), support vector regression (SVR), and multiple linear regression (MLR), were applied to the Menzel Habib aquifer system. The results obtained indicate that the DRASTIC Vulnerability Index (VI) ranges from 91 to 141 and is classified into two categories: low and moderate vulnerability. However, the correlation between groundwater total dissolved solids (TDS) and the Vulnerability Index is relatively weak (r < 0.5). Indeed, the original DRASTIC index needs some improvements. To improve it, some adjustments are required, notably by incorporating the TDS-groundwater salinization risk (GSR) indicator. The seven parameters of the original DRASTIC model were used as inputs for the artificial intelligence models, while the GSR values were used as outputs. Performance indicators, such as the correlation coefficient (r) and the Willmott Agreement Index (d), showed that the ANN model outperformed the SVR and MLR models. Indeed, during the training phase, the ANN model obtained r values equal to 0.89 and d values of 0.4, demonstrating the superiority, robustness, and accuracy of ANN-based methodologies over the original DRASTIC model. The findings could provide valuable information to guide management of groundwater contamination risks, especially in arid regions.

Assessment and spatialization of vulnerability of Benin coast to sea level rise using composite/blended approach

Climate change, particularly sea level rise, poses significant challenges to global coastal regions, necessitating a profound understanding of their vulnerability for effective mitigation and adaptation strategies. This study focuses on enhancing scientific insight into West African coastal vulnerability, aiming to assist policymakers and coastal managers in developing sustainable coastal zone management strategies. The methodology employed combines Geographic Information System (GIS) and remote sensing techniques with the Coastal Vulnerability Index (CVI) formula. Parameters such as slope, topography, distance to shoreline, population density, accessibility, land cover, and soil and vegetation types are assessed for their contribution to physical and socio-economic changes induced by sea level rise. These parameters undergo weighting using the Analytic Hierarchy Process (AHP). The socio-economic vulnerability is quantified using the Community-Based Risk Screening Tool-Adaptation and Livelihoods (CRiSTAL). The assessment of the Benin coast reveals significant vulnerability, with very high vulnerability (36.69–70.4, indicated by red cells) and high vulnerability (30.84–36.69, indicated by orange cells) observed in all coastal municipalities (Grand-Popo, Ouidah, Abomey-Calavi, Cotonou, Sèmè-Kpodji), encompassing 40 % and 21 % of the study area, respectively. Moderate (25.69–30.84) and low (10.87–25.69) vulnerability areas are situated at higher elevations inland, covering 35 % and 4 % of the total study area, respectively. No areas of very low vulnerability have been identified. This research contributes significantly to coastal management decisions, adaptation strategies, and climate change policies in Benin by advancing scientific understanding of coastal vulnerability and facilitating the development of sustainable strategies.