Vulnerable Zones Research Articles

Assessing coastal aquifer vulnerability to seawater intrusion: adaptation of the DCG method and application to the Dradère–Souière coastal aquifer in northern Morocco

Context Seawater intrusion into coastal aquifers represents a major global environmental challenge, leading to salinisation of these water resources. Aims This study aims to protect coastal aquifers from marine salinisation by assessing their vulnerability to seawater intrusion. Methods The DCG method was adapted by considering the weighted sum of the following three critical parameters controlling seawater intrusion: distance from saltwater (D), aquifer hydraulic conductivity (C) and the hydraulic gradient (G). Thereby, the weights assigned to these parameters were objectively determined through sensitivity tests. Key results The DCG map of the Dradère–Souière coastal aquifer shows that vulnerability increases near the sea, with a high to extreme vulnerability zone extending parallel to the coastline up to 5000 m inland. These findings are corroborated by a correlation analysis with the electrical conductivity map. Conclusion This study highlighted the adaptation of the DCG method for assessing the vulnerability of coastal aquifers to seawater intrusion and its successful application to the Dradère–Souière coastal aquifer. Implications The DCG method could be extended to other coastal regions as a strategic tool for protecting against seawater intrusion. Further improvements could be achieved by correlating it with other approaches and integrating it with GIS technologies.

Multi-Scale Supply and Demand Relationships of Ecosystem Services Under Multiple Scenarios and Ecological Zoning to Promote Sustainable Urban Ecological Development in Arid Regions of China

Predicting and analyzing the supply and demand relationship of ecosystem services provides theoretical support for the improvement of the ecological environment. This paper takes Bortala, a typical oasis city with a fragile ecological environment in the arid northwest region, as a case study. Based on the GMOP-PLUS-InVEST coupled model, it predicts the coupling coordination and matching degree of the supply and demand connection of ecosystem services such as habitat quality (HQ), carbon storage (CS), water yield (WY), and soil erosion (SD) under four scenarios. The findings indicate that from 2020 to 2035, HQ, CS, and WY have basically achieved coupling coordination at both scales. However, there is a notable disparity in the supply and demand of water resource production and carbon emission production. To ensure the long-term balance of ecosystem service supply and demand (ESSD), the research area was ultimately divided into five ecological zones: ecological conservation zone, ecological agriculture zone, ecological moderate development zone, ecological improvement zone, and ecological protection zone. It could offer insights for guiding the sustainable growth of ecologically vulnerable zones in the future.

Monitoring groundwater vulnerability for sustainable water resource management: A DRASTIC-based comparative assessment in a newly township area of Bangladesh

Groundwater is a vital source of freshwater in our daily lives. Global and local groundwater quality are degrading due to rapid urbanization, human interference, and policy variations, which is prominent in developing nations like Bangladesh. The major purpose of this research is to analyze aquifer vulnerability in Bangladesh's north-central area (Mymensingh) using conventional and modified DRASTIC modeling. Seven influencing hydrogeological factors were employed to develop and integrate conventional DRASTIC modeling: soil media, net recharge, aquifer depth, aquifer media, topography, hydraulic conductivity, and influence of vadose zone, while land use and lineament density were used with them for modified DRASTIC modeling. The findings from four vulnerability analysis detected 29.56% (93.35 sq.km), 22.24% (83.12 sq. km), 28.52 (106.93 sq. km), and 37.6% (140.55 sq.km) of the study area as high to very high vulnerable zones for groundwater pollution. Lower groundwater depth, higher hydraulic conductivity, moderate to high groundwater recharge, dense lineaments, dense settlement, agricultural land, and inland waterbodies together might indicate a high vulnerability in the research area. The validation results based on EC and nitrate levels show that conventional (r = 0.884, p ≤ 0.01; r = 0.951, p ≤ 0.01) and modified DRASTIC models (r = 0.868, p ≤ 0.01; r = 0.840, p ≤ 0.01) have a stronger association with unconfined aquifers, than confined aquifers. Modification with both additional parameters showed more accuracy compared to the conventional one. Frequent monitoring of groundwater quality in high and moderately vulnerable zones is recommended for earlier detection and prevention of potential aquifer degradation.

Electric Eyes

In 1977, U.S. Border Patrol Pilot George Watson praised the latest addition to the agency’s fleet in a photo-essay for INS Reporter. “A new dimension in enforcement capability began with the Hughes 500 helicopter,” he vowed. To illustrate the fruits of modernization, Watson included aerial shots of an arrest in the San Ysidro desert. “Before,” he explained, “aliens” would “sweep across” the border. Now, “Fox Trot’s light in the sky is bad news. Migrants hit the deck. They cannot escape.” Less than a decade later, the magazine admitted that, for the first time, one million “illegals” had been apprehended in a single year. Despite the slew of surveillance technologies at its disposal—helicopters, infrared scopes, night-vision goggles, low-light television systems, and “electric eye” ground sensors—the Border Patrol was outmatched. This article mines interviews, memoirs, promotional materials, and archival photographs from the United States Citizenship and Immigration Services (USCIS) History Office and Library to flesh out the intimate links between visuality, surveillance, border policing, and xenophobic nationalism. Amid hysteria over unauthorized migration in the wake of the Bracero Program (1942–1964), the Border Patrol began to represent sovereignty on the U.S.–Mexico line as a visual project. It resurrected rudimentary tools (e.g. sign cutting) and adopted increasingly sophisticated optical devices. To advertise its vigilance, the agency turned to the camera. Via publicity and commemorative projects, the Border Patrol crafted an institutional iconography that showcased its prescient, scientific oversight even as it displayed the U.S.–Mexico boundary’s persistent insecurity. Throughout, it positioned the undocumented as invasive enemies. Ultimately, the Border Patrol leaned on a visual culture that glorified surveillance to justify the state’s sovereign right to police mobility. Insidiously, it fueled xenophobia by othering Mexican migrants. And it reimagined the U.S.–Mexico border as the site of a forever war: a perpetually vulnerable zone where perfected observation was a required—but never finished—pursuit.

Enhancing Road Safety with Smart Infrastructure: Development and Implementation of Advanced Zebra Crossings and Speed Breaking

Abstract: This study addresses a critical issue in road safety by proposing innovative solutions to mitigate accidents caused by speeding and reckless driving, particularly in high-risk areas such as highways, hospitals, and schools. With road traffic accidents accounting for approximately 1.3 million fatalities annually, along with 20 to 50 million injuries or disabilities, the inefficacy of traditional traffic control systems is a growing concern. Factors such as poor visibility, adverse weather, and driver distractions further compromise the effectiveness of conventional signs and signals. This research introduces a "smart zebra crossing" system that integrates ultrasonic sensors and embedded LED lights to provide real-time alerts to both drivers and pedestrians, thereby enhancing visibility and safety, especially under low-light conditions. Additionally, a "smart speed breaking" system is proposed, which dynamically adjusts its height based on vehicle speed, detected through ultrasonic sensors, prompting drivers to decelerate when necessary. Both systems are linked to a central traffic management network, facilitating real-time adjustments in speed limits and providing alerts to connected vehicles. The integration of these technologies represents a significant advancement in road safety, offering an adaptive, intelligent solution for improving traffic management and reducing the risk of accidents, particularly in vulnerable zones.

Identifying the spatial pattern and driving factors of nitrate in groundwater using a novel framework of interpretable stacking ensemble learning

Groundwater nitrate contamination poses a potential threat to human health and environmental safety globally. This study proposes an interpretable stacking ensemble learning (SEL) framework for enhancing and interpreting groundwater nitrate spatial predictions by integrating the two-level heterogeneous SEL model and SHapley Additive exPlanations (SHAP). In the SEL model, five commonly used machine learning models were utilized as base models (gradient boosting decision tree, extreme gradient boosting, random forest, extremely randomized trees, and k-nearest neighbor), whose outputs were taken as input data for the meta-model. When applied to the agricultural intensive area, the Eden Valley in the UK, the SEL model outperformed the individual models in predictive performance and generalization ability. It reveals a mean groundwater nitrate level of 2.22 mg/L-N, with 2.46% of sandstone aquifers exceeding the drinking standard of 11.3 mg/L-N. Alarmingly, 8.74% of areas with high groundwater nitrate remain outside the designated nitrate vulnerable zones. Moreover, SHAP identified that transmissivity, baseflow index, hydraulic conductivity, the percentage of arable land, and the C:N ratio in the soil were the top five key driving factors of groundwater nitrate. With nitrate threatening groundwater globally, this study presents a high-accuracy, interpretable, and flexible modeling framework that enhances our understanding of the mechanisms behind groundwater nitrate contamination. It implies that the interpretable SEL framework has great promise for providing valuable evidence for environmental management, water resource protection, and sustainable development, particularly in the data-scarce area.

Integration of SPEI and machine learning for assessing the characteristics of drought in the middle ganga plain, an agro-climatic region of India.

Drought, as a natural and intricate climatic phenomenon, poses challenges with implications for both natural ecosystems and socioeconomic conditions. Evaluating the characteristics of drought is a significant endeavor aimed at mitigating its impact on society and individuals. This research paper explores the integration of the Standardized Precipitation Evapotranspiration Index (SPEI) and machine learning techniques for an assessment of drought characteristics in the Middle Ganga Plain, a crucial agro-climatic region in India. The study focuses on evaluating the frequency, intensity, magnitude, and recurrence interval of drought events. Various drought models, including Random Forest (RF), Artificial Neural Networks (ANN), and an ensemble model combining ANN and RF, were employed to analyze and predict drought patterns at different temporal scales (3-month, 6-month, and 12-month). The performance of these models was rigorously validated using key metrics such as precision, accuracy, proportion incorrectly classified, over-all area under the curve (AUC), mean absolute error (MAE), and root mean square error (RMSE). Furthermore, the research extends its application to delineating drought vulnerability zones by establishing demarcations for high and very high drought vulnerability areas for each model and temporal scale. Results indicate that the south-western part of the middle Ganga plain falls under the highly drought-vulnerable zone, which averagely covers 40% of the study region. The core and buffer regions of drought vulnerability have also been identified. The south-western part of the study area is identified as the core region of drought. Ground verification of the drought-vulnerable area has been done by using soil moisture meter. Validation metrics show that the ensemble model of ANN and RF exhibits the highest accuracy across all temporal scales. This research's findings can be applied to improve drought preparedness and water resource management in the Middle Ganga Plain. By identifying high-risk drought zones and utilizing accurate prediction models, policymakers and farmers can implement targeted mitigation strategies. This approach could enhance agricultural resilience, protect livelihoods, and optimize water allocation in this vital agro-climatic region.

Manure contribution to rural livelihoods at farm and landscape levels: a systemic approach in semi-arid Central Tunisia

ABSTRACT Manure valorization through on-farm use or market transactions is an ancient and widespread practice in the mixed crop-livestock systems of the semi-arid areas of North Africa. While research has long focused on the manure contribution to soil fertility at the plot level, little has been done concerning livelihood conditions. The present paper aims to assess the contribution of manure use and exchange on the livelihoods of rural communities using an original dataset collected in 2021 among 150 farmers in Central Tunisia. This analysis is carried out within the analytical agroecology framework combined with factor analysis methods. Results showed that manure use and valorization differ along the watershed, from a socioeconomic perspective in small farms operating under rainfed tree-pastoral systems, to an environmental and agronomic perspective in the mixed rainfed-irrigated systems downstream. Manure flow analysis confirmed that on-farm manure balance is positively correlated to economic wealth. However, the manure fluxes questioned the environmental sustainability of the vulnerable zones. Its use and management could significantly impact livelihood discrepancies in the future, with the increasing of demand and use of manure in more favorable zones such as irrigated lands at the detriment of the rainfed zones.

Delineating the drought vulnerability zones in Bangladesh

The research aims to explore the vulnerability of Bangladesh to drought by considering a comprehensive set of twenty-four factors, classified into four major categories: meteorological, hydrological, agricultural, and socioeconomic vulnerability. To achieve this, the study utilized a knowledge-based multi-criteria method known as the Analytic Hierarchy Process (AHP) to delineate drought vulnerability zones across the country. Weight estimation was accomplished by creating pairwise comparison matrices for factors and different types of droughts, drawing on relevant literature, field experience, and expert opinions. Additionally, online-based interviews and group discussions were conducted with 30 national and foreign professionals, researchers, and academics specializing in drought-related issues in Bangladesh. Results from overall drought vulnerability map shows that the eastern hills region displays a notably high vulnerability rate of 56.85% and an extreme low vulnerability rate of 0.03%. The north central region shows substantial vulnerability at high levels (35.85%), while the north east exhibits a significant proportion (41.68%) classified as low vulnerability. The north west region stands out with a vulnerability rate of 40.39%, emphasizing its importance for drought management strategies. The River and Estuary region displays a modest vulnerability percentage (38.44%), suggesting a balanced susceptibility distribution. The south central and south east regions show significant vulnerabilities (18.99% and 39.60%, respectively), while the south west region exhibits notable vulnerability of 41.06%. The resulting model achieved an acceptable level of performance, as indicated by an area under the curve value of 0.819. Policymakers and administrators equipped with a comprehensive vulnerability map can utilize it to develop and implement effective drought mitigation strategies, thereby minimizing the losses associated with drought.

Geospatial analysis of alarmingly increasing flood vulnerability and disaster risk within the northeast himalaya region of India

Geoenvironmetally the eastern part of the Himalaya region is highly vulnerable to flood and other natural disasters as it consists of fragmented and tectonically active geology and geomorphology, very high monsoon rainfall (>360 cm) and subsequent runoff, rugged hilly terrain with high ranges of elevation and slope, dense drainage density etc. Other hand, the unplanned developmental activities keep going and scaling up this vulnerability and risk to floods and other disasters. Addressing this burning issue, a geospatial technology-based case study of the Kohima district, Nagaland state (India), is presented here. The geospatial "technology-based" analyses employed in the study are thematic GIS mapping of flood hazard, vulnerability and risk controlling factors; and performing overlay operation using the AHP model in GIS software to generate spatio-temporal map layers of flood vulnerability and disaster risk. Results reveal that the region is under a high rate of monsoon climate change (increasing temperature, rainfall, rainy days, rainfall events and flood events with an annual rate of 0.35 %, 1.12 %, 0.36 %, 2.67 % and 4 % respectively), land use degradation (increasing built-up area with 0.60 %, annual rate decreasing forest, shrubs and water bodies with 0.80 % accumulated annual rates respectively) and demographic changes (increasing urban as well and rural population density with 0.53–2.10 % and 0.55–2.14 % respectively). Accumulated impacts of climate change, land use degradation and demographic changes causing an increase in flood hazard, vulnerability and disaster risk. Flood hazard zones and vulnerability zones extending with 0.50 % (4.89 km2) and 0.84 % (8.16 km2) annual rates respectively, subsequently the flood risk zones categorized as a moderate, high and very high potential risk, have been spreading out with a yearly rate of 0.07 % (0.65 km2), 0.13 % (1.31 km2) and 0.03 % (0.33 km2) respectively. It decreases the area under low and very low-risk zones by 0.17 % (1.63 km2) and 0.07 % (0.65 km2) annual rates respectively. Following up on these annual rates, the spatial distribution of flood hazard, vulnerability and risk zones for the next decade (2031–2040) have also been projected, revealing alarming situations, if flood disaster risk reduction (F-DRR) measures were not implemented in timely. It is strongly believed that the proposed study will be very useful for district-level planners and administrators to implement sustainable development planning, for the scientific fraternity to enhance their research work in the field of flood disaster management and for individuals for their safety in terms of life and property.

Measurement and impact analysis of social vulnerability to geological disasters in Guizhou Province, China

Investigating social vulnerability is a crucial aspect of attaining an in-depth understanding of disasters and disaster risk. This study developed a measurement framework for social vulnerability to geological disasters, obtained a comprehensive social vulnerability index, and compared the spatial distribution patterns of fatalities, social vulnerability, and geological disaster-prone zones. These efforts assisted in determining the strength and character of the relationship between geological disaster fatality risk and social vulnerability at the county level. The findings show that: (1) the social vulnerability to geological disasters index varies significantly between counties. High social vulnerability is primarily concentrated in Bijie City, Guizhou province, which shows concentrated clustering. Conversely, low social vulnerability is mainly concentrated in Guiyang City: (2) the spatial distribution patterns reveal the limitations of disaster exposure in explaining fatality risk and demonstrate the ability of social vulnerability to amplify disaster risk; (3) the zero-inflated negative binomial regression model fit the data significantly better than the negative binomial regression model, suggesting that for every one unit increase in the social vulnerability index, there is a 6.33% increase in the risk of fatalities, holding all other variables constant. This study establishes a specific framework for measuring social vulnerability to geological disasters and provides new evidence of how social vulnerability influences disaster risk intensity. The county-level spatial measurement results can further assist disaster management personnel in formulating more localized mitigation strategies. The findings will further support the identification of core remediation sites and the implementation of management and relocation (avoidance) projects during Guizhou Province’s 14th Five-Year Plan for geological disaster prevention and control.

Analisis Tingkat Kerawanan Banjir di Sub Daerah Aliran Sungai (DAS) Kampar Kiri di Kecamatan Kampar Kiri

This study aims to describe and analyze the flood vulnerability level in the Kampar Kiri Sub-Watershed, Kampar Kiri District, as well as the extent of flood-prone areas impacting settlements in the region. The primary focus of this research is to understand the flood risk of the area and its effects on the existing settlements. The method applied in this study is Multi-Criteria Evaluation (MCE) using a Geographic Information System (GIS) approach. MCE is used to determine the weights of parameters affecting flood vulnerability and to select appropriate methods for analysis. This approach has proven effective and efficient in flood risk analysis, as demonstrated in previous studies. The parameters analyzed include slope, elevation, rainfall, soil type, land use, and distance from rivers, which are calculated using scoring methods and overlaid to produce a flood vulnerability map. The results indicate that the flood vulnerability level in the Kampar Kiri Sub-Watershed is categorized into three classes: not vulnerable, vulnerable, and highly vulnerable. The areas for each class are: not vulnerable with 16,854 hectares, vulnerable with 58,543 hectares, and highly vulnerable with 11,506 hectares. The extent of settlements in the vulnerability zones includes: vulnerable zone with an area of 277 hectares (approximately 20.83%), and highly vulnerable zone with an area of 1,054 hectares (approximately 79.17%). Based on these findings, it is recommended that the Kampar Kiri District government enhance land use planning to reduce flood risks, collaborate with the Kampar Public Works and Spatial Planning Office, and improve infrastructure such as drainage channels and flood protection embankments.

Exploring a GIS-based analytic hierarchy process for spatial flood risk assessment in Egypt: a case study of the Damietta branch

Floods are the most common and costly disasters worldwide, while spatial flood risk assessment is still challenging due to fewer observations and method limitations. In this study, the flood risk zonation in the Nile districts of the Damietta branch, Egypt, is delineated and assessed by integrating remote sensing with a geographic information system, and an analytical hierarchy process (AHP). Twelve thematic layers (elevation, slope, normalized difference vegetation index, topographic wetness index, modified normalized difference water index, topographic positioning index, stream power index, modified Fournier index, drainage density, distance to the river, sediment transport index, and lithology) are used for producing flood susceptibility zonation (FSZ) and six parameters (total population, distance to hospital, land use/land cover, population density, road density, and distance to road) are utilized for producing flood vulnerability zonation. Multicollinearity analysis is applied to identify highly correlated independent variables. Sensitivity studies have been used to assess the effectiveness of the AHP model. The results indicate that the high and very high flood risk classes cover 21.40% and 8.26% of the area, respectively. In 14.07%, 27.01%, and 29.26% of the research area, respectively, flood risk zones classified as very low, low, and moderate are found. Finally, FSZ is validated using the receiver operating characteristics curve and area under curve (AUC) analysis. A higher AUC value (0.741) in the validation findings demonstrated the validity of this AHP approach. The results of this study will help planners, hydrologists, and managers of water resources manage areas that are susceptible to flooding and reduce potential harm.

Assessment of soil erosion risk and vulnerability in the transboundary Sio-Malaba-Malakisi watershed in Kenya and Uganda

Persistent soil erosion poses a significant threat to water quality, ecosystem viability and soil health in many regions of the world. Addressing this challenge requires a comprehensive understanding of local soil erosion rates, including the identification of vulnerable areas, to facilitate effective and integrated environmental management. In East Africa, however, many affected regions are data poor and lack measured hydrological data from which soil erosion estimates can be derived. This study used the physically based Revised Universal Soil Loss Equation (RUSLE) model to estimate the annual rate of soil erosion in the transboundary Sio-Malaba-Malakisi catchment, straddling Kenya and Uganda. Soil erosion events were quantified by integrating input factors derived from physical datasets using a Geographical Information System (GIS). The Analytical Hierarchy Process (AHP) technique was then used to assess the importance of selected physical factors influencing the soil erosion process in order to identify regions of increasing environmental vulnerability. The results obtained indicate a wide range of soil erosion rates across the region, with an estimated mean annual rate of 250 t ha−1 yr−1 for the whole catchment. Upstream areas characterized by intensive agricultural activity had erosion rates of up to 2000 t ha−1 yr−1, while downstream areas recorded erosion rates below 600 t ha−1 yr−1. Areas with intensive agriculture, unprotected soils, and a soil loss tolerance value above 12 t ha−1 yr−1 were found to be most vulnerable. Rainfall and vegetation cover were identified as key factors influencing erosion susceptibility. Regions with soil erosion rates above 50 t ha−1 yr−1 were identified as high priority regions for targeted soil and water conservation measures. The identification of vulnerability zones, including the classification of their severity, provides an opportunity to prioritize sustainable environmental management interventions; a process that can be replicated for such affected regions elsewhere.

Assessing Groundwater Vulnerability to Pollution in a Rapidly Urbanizing River Basin Using a Modified DRASTIC Land Use–Lineament Density Method

ABSTRACTGroundwater quality assessment is crucial for ensuring safe drinking water, protecting public health, and maintaining sustainable water resources for agricultural and industrial uses. The Awash River basin faces significant groundwater quality challenges due to rapid population growth, high urbanization, large‐scale irrigation, and industrial pollution. The main objective of this study is to evaluate the intrinsic vulnerability of aquifers to pollution in the Awash Basin and identify hotspots requiring urgent intervention using a modified DRASTIC overlay analysis method. In addition to the seven parameters considered in the generic DRASTIC overlay analysis (depth to the water table, recharge, aquifer media, slope, soil media, vadose zone, and hydraulic conductivity), we incorporated land use/land‐cover (LULC) and lineament density (LD) distributions (DRASTIC‐LU‐LD). This modification allowed us to produce more realistic groundwater vulnerability maps for the basin. To identify the most influential parameters in the overlay, sensitivity analysis was conducted using Map Removal Sensitivity Analysis (MRSA) and Single Parameter Sensitivity Analysis (SPSA). Initially, the generic DRASTIC index in the area ranges from 69 to 181, categorizing the area into four vulnerability zones: very low (21%), low (51%), medium (27%), and high (1%). After incorporating LU and LD, the index values ranged from 90 to 240. Based on the percentage of the total area studied, the inclusion of LU decreased the very low and low vulnerability zones from 72% to 44% and the inclusion of LD increased the high‐ and very‐high‐vulnerability zones from 14% to 27%. The areas most vulnerable to groundwater pollution are in the western (upper Awash), middle Awash, and northwestern regions, particularly in city centers where groundwater abstraction is significant. These high‐vulnerability zones coincide with municipal, industrial, and agricultural pollution sources. The vadose zone parameter has the highest impact in both MRSA and SPSA, with a variation index value of 3.08% and a mean effective weight of 27.93%, respectively. By identifying areas vulnerable to groundwater pollution, this study provides a valuable basis for informed decision‐making and the development of effective strategies for protecting groundwater from urban, industrial, and agricultural pollution sources.

RC dapped-end beams with various reinforcement layouts: An experimental investigation

Reinforced Concrete (RC) discontinuity regions (D-regions), such as dapped ends, can represent vulnerable zones in existing RC structures since they can exhibit a brittle failure mechanism. In common design practice, the ultimate strength of D-regions is assessed through Strut and Tie (S&T) models. Current design codes recommend two resistant mechanisms for dapped ends but do not provide information about the identification of steel bars involved in the resistant mechanism when the reinforcement is formed by distributed bars. An experimental campaign on dapped-end beams with various reinforcement layouts, including configurations without diagonal bars or with one or multiple layers of diagonal bars, has been carried out at the Structures and Material Testing Laboratory of the Department of Civil and Environmental Engineering in Florence. Results allow for identifying the influence of different reinforcement layouts on the crack pattern at the Service Limit State (SLS) and on the post-peak response. Both the strain on bars and the crack opening displacements are investigated until failure. The work highlights that layouts with distributed diagonal bars reduce the crack widths at the SLS compared to other configurations, increase the ductility, and allow for the timely detection of damaged dapped ends during in situ inspections.

Climate-induced coastal occupational vulnerability and livelihood insecurity: Insights from coastal Bangladesh

The livelihoods of the fishing communities residing in the geographically vulnerable coastal zone are constantly threatened by escalating coastal disasters. The communities face persistent challenges, including livelihood failure, poverty, high exposure and sensitivity, and lower adaptive capacity, yet little attention has been paid to comprehending their multifaceted livelihood vulnerabilities amid climate-induced disasters. This study bridges that gap by employing several techniques to address the challenge. It adopts a mixed-method analysis and investigates the Livelihood Assessment Index (LAI), Livelihood Vulnerability Index (LVI), and Climate Vulnerability Index (CVI) to assess the livelihood vulnerability of fishermen communities residing in the new and old fishery ghats (riverside locations where fishing-related activities take place) in Chattogram district in southern Bangladesh. Findings reveal that the fishing communities experience higher exposure levels and moderate vulnerability in the face of escalating climate-induced disasters. The overall LAI indicates a relatively low level of livelihood satisfaction, suggesting potential challenges or deficiencies in aspects contributing to well-being. Despite socioeconomic and demographic similarities, as LVI values present, the exposure varies between the two study locations. Both locations are characterized by moderate sensitivity, while the new fishery ghat showed slightly higher adaptive capacity, contributing to greater resilience. The CVI values indicated higher vulnerability for the new fishery ghat fishing community, suggesting increased challenges related to climate-induced threats, and the old ghat community exhibited lower vulnerability, showcasing better resilience to disasters. Factors influencing livelihood vulnerability include limited access to education and healthcare in the new fishery ghat, while the old fishery ghat benefits from better provisions, communication, social networks, and education facilities. The study advocates for context-specific decision-making and targeted interventions to support vulnerable fishing communities in coastal zones globally, emphasizing the need for improved social safety nets and alternative livelihood options. Addressing these occupational vulnerabilities is crucial for long-term development in climate-risk countries like Bangladesh.

Flood vulnerability analysis using geographic information system in the core zone of the Lore Lindu biosphere reserve, Indonesia

Floods are caused by the accumulation of several factors, such as global warming, climatological characteristics, hydrology, and physical conditions of an area. The purpose of this study was to map the level of flood vulnerability in the core zone of the Lore Lindu Biosphere Reserve using geographic information system (GIS) based spatial analysis with scoring and overlay. The research parameters consisted of rainfall, elevation, slope, soil type, land cover, and distance from the river. This research was conducted in the core zone divided into 13 subdistricts and 2 regencies. The results of the classification of flood vulnerability levels are divided into 4 (four) categories: not prone, low vulnerability, moderate vulnerability, and high vulnerability. The results of the analysis show that the core zone of the Lore Lindu biosphere reserve is dominated by a non-hazardous site with an area of 145,018’28 ha (67.23%), a low vulnerability zone of 65,430.10 ha (30.33%), a moderate vulnerability zone of 5,025.29 ha (2.33%), and a high vulnerability zone of 245.99 ha (0.11). Areas with a high level of vulnerability are at low elevations with flat to gentle slopes. Most land use is dominated by water, mining, and open land without vegetation and is located around rivers.

Analysis of changes and driving forces of landscape pattern vulnerability at Qianping Reservoir in Central China.

Reservoir projects often have significant impacts on ecosystems. The resulting environmental problems hinder the ecologically sustainable development of project areas. Research focusing on landscape pattern vulnerability could shed light on ecological restoration in disturbed sites. However, few studies have specifically examined reservoir areas in this context. This study investigates the spatial distribution characteristics, change rules, spatial autocorrelation, and driving forces of landscape pattern vulnerability in the Qianping Reservoir area (3859.16 hm2) from 2000 to 2020 using land use data. The findings reveal several key points: (1) Over the study period, cultivated land, grassland, and forest land are the key landscape types, covering more than 90% of the area. Cultivated land decreased by 481.57 hm2 as other land use types expanded. (2) Vulnerability remained stable in the first decade but sharply increased from 2010 to 2020, showing a trend of spatial aggregation. Reservoir construction and simultaneous ecological restoration efforts led to shifts in vulnerability zones across the landscape. (3) Spatial distribution of landscape pattern vulnerability shows a positive correlation, which strengthened by 2020 compared to earlier years. (4) Man-made factors, particularly land use changes, significantly influence landscape pattern vulnerability, with their impact growing over time. These findings not only provide a scientific basis for ecological restoration and landscape reconstruction in the Qianping Reservoir area but also offer insights applicable to similar environments. Overall, this study enhances theoretical understanding of reservoir landscape pattern vulnerability and contributes valuable perspectives on ecological restoration strategies for reservoir areas.

Numerical Groundwater Model to Assess the Fate of Nitrates in the Coastal Aquifer of Arborea (Sardinia, Italy)

The Arborea plain in Sardinia (Italy) is classified as a nitrate vulnerable zone (NVZ). In the present study, the individual work steps that are necessary to progress from the existing 3D hydrogeological model to a 3D numerical groundwater model using the interactive finite-element simulation system FEFLOW 7.4 are shown. The results of the transient flow model highlight the influence of the drainage network on the overall groundwater management: the total water volume drained by the ditches accounted for approximately 58% of the annual outflow volume. The numerical transport simulations conducted from 2012 to 2020 using hypothetical field-based nitrate input scenarios globally underestimated the high concentrations that were observed in the NVZ. However, as observed in the field, the computed nitrate concentrations in December 2020 still varied strongly in space, from several mg L−1 to several hundreds of mg L−1. The origin of these remaining local hotspots is not yet known. The modeling of rainfall fluctuations under the influence of climate change revealed a general long-term decline in the groundwater level of several tens of centimeters in the long term and, in conjunction with a zero-nitrate scenario, led to a significant decrease in nitrate pollution. Although hotspots were attenuated, the concentrations at several monitoring wells still exceeded the limit value of 50 mg L−1.