Groundwater Vulnerability Assessment Research Articles

Incorporating hydraulic gradient and pumping rate into GALDIT framework to assess groundwater vulnerability to salinity in coastal aquifers: a case study from Urmia Plain, Iran.

The critical role of groundwater in meeting diverse needs, including drinking, industrial, and agricultural, highlights the urgency of effective resource management. Excessive groundwater extraction, especially in coastal regions including Urmia Plain in NW Iran, disrupts the equilibrium between freshwater and saline boundaries within aquifers. Influential parameters governing seawater intrusion-groundwater occurrence (G), aquifer hydraulic conductivity (A), the height of groundwater level above the mean sea level (L), distance from the shore (D), impact of the existing status of seawater intrusion (I), and thickness of the saturated aquifer (T)-merge to shape the GALDIT vulnerability index for coastal aquifers. This study enriches the GALDIT framework by incorporating two additional hydrogeological variables: hydraulic gradient (i) and pumping rate (P). This expansion produces seven distinct vulnerability maps (GALDIT, GAiDIT, GAiDIT-P, GALDIT-i, GALDIT-iP, GALDIT-P, GAPDIT). In the Urmia Plain, the traditional GALDIT index reveals vulnerability values ranging from 2 to 8.1, categorized into six classes from negligible to very high vulnerability. However, the modified indices, GAiDIT and GAiDIT-P, yield a three-class categorization, ranging from low to high vulnerability. The introduction of the "i" and "P" parameters in GALDIT-i and GALDIT-iP enhances the precision of vulnerability mapping, altering class distribution and intensifying vulnerability ratings. The eastern, central, and coastal areas of the Urmia Plain demonstrate high to very high vulnerability levels, in contrast to the lower vulnerability observed in the western regions. Both the GALDIT-P (r = 0.82) and GALDIT-iP (r = 0.81) indices show strong correlations with Cl concentration, thereby improving mapping accuracy over the traditional GALDIT index (r = 0.72). A sensitivity analysis highlights the critical influence of the "i" parameter, suggesting its weighting should be revised. Parameter recalibration serves to amplify the significance of "G," "L," "D," and "i" parameters, while diminishing others. The integration of multiple hydrogeological variables considerably enhances the precision of groundwater vulnerability assessments.

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

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

A three-step modification of the DRASTIC model using spatial multi criteria decision making methods to assess groundwater vulnerability

Groundwater vulnerability assessment, as a key tool, is essential for assisting decision-makers and experts in identifying highly vulnerable areas and devising efficient pollution reduction strategies. The widely utilized DRASTIC model for assessing groundwater vulnerability incorporates seven key geological and hydrological parameters. To address the limitations of the DRASTIC model, this study proposes a novel three-step modification by introducing an extra parameter, adjusting default weights, and utilizing alternative aggregation methods. These modifications aim to capture the unique characteristics of a specific region more accurately. The first step involves incorporating the Land Use (LU) parameter as the eighth parameter in the DRASTIC model, resulting in an updated 8-parameter model. The second step involves integrating the Analytic Hierarchy Process (AHP) to adjust parameter weights based on input from local experts. Lastly, while the Weighted Linear Combination (WLC) technique has conventionally been used for aggregating layers in the GIS environment, this study suggests employing the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). Furthermore, to consider decision makers' risk attitudes, the Ordered Weighted Averaging (OWA) method is utilized.To assess its effectiveness, the modified model was applied to Khoy County in Iran. Then, the results were compared to the DRASTIC model using correlation analysis based on nitrate concentrations. The results indicated a correlation coefficient of 0.67 for the modified model compared to 0.47 for the DRASTIC model. This suggests that the proposed modified model is an enhanced and highly effective approach for evaluating groundwater vulnerability.

Improving groundwater vulnerability assessment in structurally controlled hard rock aquifer: insight from lineament density and land use/land cover pattern.

A comprehensive seasonal assessment of groundwater vulnerability was conducted in the weathered hard rock aquifer of the upper Swarnrekha watershed in Ranchi district, India. Lineament density (Ld) and land use/land cover (LULC) were integrated into the conventional DRASTIC and Pesticide DRASTIC (P-DRASTIC) models and were extensively compared with six modified models, viz. DRASTIC-Ld, DRASTIC-Lu, DRASTIC-LdLu, P-DRASTIC-Ld, P-DRASTIC-Lu, and P-DRASTIC-LdLu, to identify the most optimal model for vulnerability mapping in hard rock terrain of the region. Findings were geochemically validated using NO3- concentrations of 68 wells during pre-monsoon (Pre-M) and post-monsoon (Post-M) 2022. Irrespective of the applied model, groundwater vulnerability shows significant seasonal variation, with > 45% of the region classified as high to very high vulnerability in the pre-M, increasing to ̴67% in post-M season, highlighting the importance of seasonal vulnerability assessments. Agriculture and industries' dominant southern region showed higher vulnerability, followed by regions with high Ld and thin weathered zone. Incorporating Ld and LULC parameters into DRASTIC-LdLu and P-DRASTIC-LdLu models increases the 'Very High' vulnerability zones to 17.4% and 17.6% for pre-M and 29.4% and 27.9% for post-M, respectively. Similarly, 'High' vulnerable zones increase from 32.5% and 25% in pre-M to 33.8% and 35.3% in post-M for respective models. Model output comparisons suggest that modified DRASTIC-LdLu and P-DRASTIC-LdLu perform better, with accurate estimations of 83.8% and 89.7% for pre-M and post-M, respectively. However, results of geochemical validation suggest that among all the applied modified models, DRASTIC-LdLu performs best, with accurate estimations of 34.4% and 20.6% for pre-M and post-M, respectively.

Integrated assessment of groundwater vulnerability in arid areas combining classical vulnerability index and AHP model.

Groundwater is the main source of water for agriculture, industry, and families in arid areas. At present, there is an urgent need to protect groundwater due to human activities. In this study, the Qingshui River Basin was selected as the study area. Based on the DRASTIC model, the DRASTIC-Land use type (DRASTICL) model and the analytic hierarchy process-DRASTICL (AHP-DRASTICL) model were constructed by optimizing the indicators and weights. And the three models were applied to calculate the groundwater vulnerability index (GVI), and the groundwater vulnerability map (GVM) was drawn. The validation results of Spearman correlation coefficient show that the DRASTICL model and the AHP-DRASTICL model have higher correlation, which indicates that the optimized model is more accurate. Among them, the AHP-DRASTICL model has the highest correlation coefficient (ρ = 0.92), which is more in line with the actual situation. The results of this study can provide scientific guidance for the protection and utilization of groundwater in the Qingshui River Basin. And it is of guiding significance for the study of groundwater vulnerability, especially for groundwater management in arid and semi-arid areas.

A multi-method approach for assessing groundwater vulnerability of shallow aquifers in the Marchfeld region (Austria)

Study regionMarchfeld region (Austria) Study focusA multi-method and multi-scale assessment of the intrinsic groundwater vulnerability to generic pollutants was carried out. At the regional scale, a parametric method, to assess the intrinsic groundwater vulnerability, and a transfer function model, to assess the travel time of a generic and non-reactive pollutant through the unsaturated zone, were applied. At the site-specific scale, the travel time of the peak concentration was evaluated by using a physically-based hydrological model. The comparison of results of different approaches allowed mutual validation and advanced the knowledge about the assessment of groundwater vulnerability. New hydrogeological insights for the regionTo assess the groundwater vulnerability, a detailed hydrogeological map of the study area was reconstructed. A large variability of hydrogeological, morphological and anthropic conditions was recognized. Alluvial aquifers formed by high-permeability deposits hosting shallow groundwater circulation are characterized by the highest groundwater vulnerability. Contrarily, lower groundwater vulnerability was recognized for aquifers formed by low-permeability deposits, favoring a reduction of infiltration processes and a major attenuation of pollutants’ potential effects. The presented multi-method approach revealed how comparing the results of a DRASTIC-like method and two process-based models can deliver hints regarding their suitability, different spatial densities and quality of required inputs, and effectiveness. Finally, the potential strong impact of some agricultural practices was confirmed.

Delineation of groundwater vulnerable zone for sustainable development in the southwestern part of Bihar, India

In the face of the global groundwater crisis and climate change challenges, the groundwater potential (GWP) and quality (GWQ) assessment for tackling the depletion and contamination of aquifers are imperative for India's sustainable development of groundwater resources. This study explores the GWP and GWQ in the southwestern part of Bihar state, located in the declining groundwater of the lower Indo-Gangetic plain, where population growth, rapid urbanization, and escalating agricultural demands have strained aquifer systems. This study uses the Analytical Hierarchy Process and weighted average techniques in the GIS framework to assess groundwater vulnerability. Our results reveal that over 82% of the area exhibits good groundwater potential, except for the southern part. The presence of Vindhyan mountains in the southern part has different geology, elevation, and land use and land cover, leading to poor groundwater potential. Considering the desirable and acceptable limits by BIS (2012) and Who (2022), it has been found that 89% and 18% of the study area falls under the poor to unsuitable groundwater category, affecting a staggering 7.7 million and 1.6 million individuals, respectively despite substantial groundwater potential. Findings from this investigation indicate that groundwater contamination resulted from anthropogenic and geogenic factors; however, it remains suitable for agricultural purposes. Our research will assist policymakers in implementing sustainable management strategies to ensure a lasting and reliable supply for domestic and agricultural uses of groundwater.

Groundwater vulnerability and risk assessment coupled with hydrogeochemical analysis in the Taza aquifer (Morocco)

This study assesses the vulnerability of aquifers to increased contamination, influenced by rapid peri-urbanization and deficient sanitary infrastructure. The research focuses on the Taza aquifer in northeastern Morocco, where we applied the DRASTIC and GOD models. We further enhanced the DRASTIC method by the addition of a Fracture Index (F) ‘’DRASTICF‘’ to incorporate the effects of tectonics and geological discontinuities on groundwater behavior. The vulnerability mapping was performed for two distinct dry and wet periods of 2016 and 2021 respectively. Moreover, the use of hydrogeochemical analysis of 22 groundwater samples helped to identify potential sources of pollution and to understand the hydrogeological process. The results indicate a dynamic in vulnerability between these two periods due to changes in the recharge parameter and groundwater depth. The comparison between obtained vulnerability maps and nitrate concentrations reveals vulnerable zones that closely resemble regions affected by nitrate pollution. This area is predominantly classified as of high vulnerability at 27 %, associated with an estimated pollution level of 36%. The findings underscore also the importance of integrating the fracture index into the assessment of aquifer vulnerability alongside the different models. This integration offers an enriched perspective for effectively managing risks associated with groundwater contamination. The risk maps of groundwater contamination were also established by overlapping the vulnerability map with the land use layer. The main hydrogeochemical facies determined in the Piper Diagram allowed classifying the waters as Ca–Mg–HCO3 type. The significant correlations indicated that groundwater mineralization in the study area originates from the dissolution of limestone and evaporated formations. The water quality within the study area shows substantial variability, ranging from excellent to unsuitable, primarily due to the leaching of fertilizers and wastewater.The different results can be very helpful to the farmers, and local authorities for better groundwater sustainable management.

Enhanced groundwater vulnerability assessment to nitrate contamination in Chongqing, Southwest China: Integrating novel explainable machine learning algorithms with DRASTIC-LU

ABSTRACT Groundwater vulnerability to nitrate assessment serves as a measure of potential groundwater nitrate pollution in a target area. This study applies the DRASTIC-LU framework, nitrate distribution data, and three machine learning models (RF, XGB, SVM) to classify nitrate levels (exceeding 10 mg/L as nitrogen) in Chongqing, China. Model evaluation uses accuracy and F1 score metrics, with RF achieving the highest accuracy (92.9%), kappa (0.857), and AUC (0.948) on test dataset. Furthermore, the SHAP interpreter revealed that aquifer conductivity, lithology, agricultural activities, areas with high-intensity development, and groundwater recharge are the most influential indicators of groundwater vulnerability. The final groundwater vulnerability level distribution map, with a resolution of 1 km × 1 km, reveals that high and extremely high vulnerability levels are concentrated in areas with high-intensity urban development and karst trough valleys in the southeastern, northeastern, and central urban areas. This work represents the first attempt of using machine learning models for groundwater vulnerability assessment in the Chongqing region. It provides theoretical support for the construction layout of groundwater monitoring stations and the prevention and control of groundwater pollution in the future.

An integrated groundwater vulnerability and artificial recharge site suitability assessment using GIS multi-criteria decision making approach in Kayseri region, Turkey

Groundwater resources worldwide face significant challenges that require urgent implementation of sustainable measures for effective long-term management. Managed aquifer recharge (MAR) is regarded as one of the most promising management technologies to address the degradation of groundwater resources. However, in urban aquifers, locating suitable areas that are least vulnerable to contamination for MAR implementation is complex and challenging. Hence, the present study proposes a framework encapsulating the combined assessment of groundwater vulnerability and MAR site suitability analysis to pinpoint the most featured areas for installing drywells in Kayseri, Turkey. To extrapolate the vulnerable zones, not only the original DRASTIC but also its multi-criteria decision-making (MCDA)–based modified variants were evaluated with regard to different hydrochemical parameters using the area under the receiver operating characteristic (ROC) curve (AUC). Besides, the fuzzy analytical hierarchy process (FAHP) rationale was adopted to signify the importance level of criteria and the robustness of the framework was highlighted with sensitivity analysis. In addition, the decision layers and the attained vulnerability layer were combined using the weighted overlay (WOA). The findings indicate that the DRASTIC-SWARA correlates well with the arsenic (AUC = 0.856) and chloride (AUC = 0.648) and was adopted as the vulnerability model. Groundwater quality parameters such as chloride and sodium adsorption ratio, as well as the vadose zone thickness, were found to be the most significant decision parameters with importance levels of 16.75%, 14.51%, and 15.73%, respectively. Overall, 28.24% of the study area was unsuitable for recharge activities with high to very high vulnerability, while the remaining part was further prioritized into low to high suitability classes for MAR application. The proposed framework offers valuable tool to decision-makers for the delineation of favorable MAR sites with minimized susceptibility to contamination.

Sensitivity Analysis and GIS Tools for Groundwater Vulnerability Assessment. (Application in the Middle Chellif Plain, Algeria)

Contamination due to rapid urban development, industrialization, and agricultural sources is increasingly threatening the groundwater resources of the plioquaternary phreatic aquifer of the Middle Western Cheliff. An intrinsic vulnerability assessment was carried out based on the DRASTIC method on parameters involved in the vertical transfer of pollution from the soil surface. The vulnerability maps obtained showed a high extension of areas of medium vulnerability (54%). On the other hand, areas of low vulnerability occupied about 36%. The high and very high vulnerability was mainly related to low water depth values (8% and 2%, respectively). The results of a sensitivity analysis using the two tests—the single parameter sensitivity analysis and the map removal sensitivity analysis—show that every parameter is, without fail, required for the computation of the vulnerability index. The validation of the vulnerability map produced by the DRASTIC method confirmed the evolution of this sensitivity which decreases towards the S.W. of the plain with nitrate concentrations between 30 and 120 mg/L. Planners can use the produced risk maps as tools to make a preliminary choice of priority locations for various forms of environmental sustainability.

Introducing a novel approach for assessment of groundwater salinity hazard, vulnerability, and risk in a semiarid region

The application of machine learning approaches to improve groundwater salinity risk mapping is limited despite all potential advantages. Therefore, there is an ongoing need for investigations that present new techniques, like machine learning, validated against conventional methods. These advances are particularly important for arid and semiarid regions, such as the Bakhtegan Basin (southern Iran), where groundwater use may far outweigh recharge, but groundwater management improvements are essential. To address these needs, groundwater salinity hazard, vulnerability, and risk maps were investigated using an integrated application of statistical (i.e., frequency ratio and statistical index models), machine learning (i.e., random forest and classification and regression trees algorithms), and decision-making models (fuzzy analytic hierarchy process (FAHP)). Results showed that the risk of groundwater salinity was high in the central areas of the region as well as at the margins of Bakhtegan Lake and irrigated farming lands. Based on the modeling results in the testing phase, it was found that the frequency ratio and random forest models exhibited better performance, with Nash–Sutcliffe efficiency metrics of 0.73 and 0.70, respectively, compared to the classification and regression trees and statistical index models, which had Nash–Sutcliffe efficiency metrics of 0.65 and 0.63, respectively. The innovative techniques developed in the current work accurately identified variables such as normalized difference salinity index, distance from mines, and land use associated with the highest weight values (0.59, 0.14, and 0.11, respectively) compared to other variables to identify groundwater salinity areas of vulnerability. The application of the fuzzy analytic hierarchy process method in developing vulnerability maps, integrating them with hazard maps, and developing groundwater salinity risk maps was innovative in this study. The innovative approach is transferrable for groundwater salinity susceptibility, vulnerability, and risk assessments globally in the study area and similar settings.

Groundwater vulnerability assessment of elevated heavy metal contamination related health hazard in coastal multi-aquifers of Sundarban Biosphere Reserve, India

The concept of groundwater (GW) vulnerability emerged as a response to the escalating contamination of GW globally. Over recent decades, both scholars and policymakers have extensively utilized GW vulnerability assessments to safeguard groundwater from pollution. Within the Sundarban Biosphere Reserve (SBR), inhabitants residing near coastal aquifers face significant challenges, notably the scarcity of fresh water during the hot and dry season. Furthermore, there is a concern regarding the presence of heavy metals (HMs) in this region, adversely impacting GW quality. In both Indian and global contexts, HM contamination, including arsenic (As), fluoride (F‾), and nitrate (NO3–), and its repercussions on human health (HH) in coastal districts, represent critical issues. In light of these challenges, this study aims to assess GW vulnerability and its implications for HH in SBR utilizing the Hazard Quotient (HQ) approach. Fifteen hydro-geochemical parameters have been selected for this research endeavor. Various statistical indices, such as “groundwater quality index (GWQI)”, “degree of contamination (CD)”, “index of ecological risk (ERI)”, and “human health hazard index (HHHI)”, have been employed to accomplish the study objectives. Piper's and Box plot diagrams were utilized to assess hydrogeochemical properties and GW quality. The findings reveal average concentrations of HMs, such as As, NO3–, and F‾ in the study area, to be 0.204 mg/l, 6.28 mg/l, and 0.79 mg/l, respectively. Among all variables, a positive correlation of 0.876 is observed between electrical conductivity (EC) and sodium ions (Na+). Eventually, the outcomes of this study can provide valuable insights for planners and policymakers to make informed decisions regarding the sustainable management of water resources.

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.

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.

DRASTIC-FS Model for Assessment of Groundwater Vulnerability in Alluvial Region between Mahi and Narmada Rivers, India

DRASTIC-FS Model for Assessment of Groundwater Vulnerability in Alluvial Region between Mahi and Narmada Rivers, India

Comprehensive quantitative determination of aquifer confinement based on tidal response of well water level and its application in North China

Aquifer confinement represents a pivotal property that significantly influences the vulnerability and contamination risk of groundwater resources. Several methods have been proposed for determining aquifer confinement by analyzing the response of well water level to Earth tides and atmospheric tides. In this study, we evaluated the performance of the existing single methods and put forward an optimized comprehensive approach. We compared the determination results of the three single methods with those of a comprehensive method using water-level data from 39 earthquake precursor monitoring wells in North China. The results demonstrate that the comprehensive method effectively determined aquifer confinement, significantly reducing the uncertainty associated with the three single methods. The application of the comprehensive method in North China reveals that aquifer confinement may undergo temporal variations during long-term continuous observation, especially in areas where the confining properties of aquifers may vary due to human activities and earthquakes. In such areas, the comprehensive method facilitates accurate assessment of groundwater vulnerability, as well as the potential dispersion of underground pollutants.

Spatio-temporal prediction of groundwater vulnerability based on CNN-LSTM model with self-attention mechanism: A case study in Hetao Plain, northern China

Located in northern China, the Hetao Plain is an important agro-economic zone and population centre. The deterioration of local groundwater quality has had a serious impact on human health and economic development. Nowadays, the groundwater vulnerability assessment (GVA) has become an essential task to identify the current status and development trend of groundwater quality. In this study, the Convolutional Neural Network (CNN) and Long Short-Term Memory (LSTM) models are integrated to realize the spatio-temporal prediction of regional groundwater vulnerability by introducing the Self-attention mechanism. The study firstly builds the CNN-LSTM model with self-attention (SA) mechanism and evaluates the prediction accuracy of the model for groundwater vulnerability compared to other common machine learning models such as Support Vector Machine (SVM), Random Forest (RF), and Extreme Gradient Boosting (XGBoost). The results indicate that the CNN-LSTM model outperforms these models, demonstrating its significance in groundwater vulnerability assessment. It can be posited that the predictions indicate an increased risk of groundwater vulnerability in the study area over the coming years. This increase can be attributed to the synergistic impact of global climate anomalies and intensified local human activities. Moreover, the overall groundwater vulnerability risk in the entire region has increased, evident from both the notably high value and standard deviation. This suggests that the spatial variability of groundwater vulnerability in the area is expected to expand in the future due to the sustained progression of climate change and human activities. The model can be optimized for diverse applications across regional environmental assessment, pollution prediction, and risk statistics. This study holds particular significance for ecological protection and groundwater resource management.

Оценка уязвимости карстовых подземных вод к загрязнению на основных массивах Горного Крыма с использованием региональной методики

Introduction. Assessment of groundwater vulnerability to contamination is an effective tool for scientific substantiation of the sanitary protection zones for drinking water sources. Karst ground waters of the Mountain Crimea form the main resources for water supply in the Crimean Peninsula. This study has a purpose to perform the assessme nt and mapping of karst ground waters resource vulnerability to contamination on such representative massifs of the Crimean Mountains as Chatyrdag, Dolgorukovsky, Karabi and Ay-Petri . Materials and methods. Assessment of karst ground waters vulnerability is conducted by use of Mountain -Crimean method. It has been developed on the base of some wide-tested European methods (COP-method and Slovene approach) with methodological modification and adaptation to regional conditions of the Mountain Crimea. The input data for assessment is spatial information about ground waters vulnerability factors: protective layers in vadose zone, flow concentration by streams, sinkholes and caves, precipitation regime etc. The collected spatial information was converted into attributed geo data layers, which were subsequently subjected to overlay operations in Arc GIS 10 software according to assessment scheme. Results. According to the assessment results, approximately 34 and 14% of the Chatyrdag massif area gained the category of high and very high vulnerability, on the Karabi massif – 14 and 17%, on the Dolgorukovsky massif – 14 and 2%, on the Ay-Petri massif – 19 and 7% of total area respectively. The result ing vulnerability maps demonstrate significant mosaics and contrast, which is associated with discrete distribution of protective covers and high differentiation of ground water recharge conditions within the catchments of karst massifs. Discussion. Analysis of the resulting vulnerability maps have revealed that the leading factors determining areas of high and very high vulner ability of karst waters are runoff concentration factors, while the factors of protective cover mainly determine the areas with low vulnerability. The zones of high vulnerability on the Chatyrdag and Karabi massifs are mainly coincide with areas of high density of karst forms (sinkholes and caves), while high vulnerability zones of the Ay-Petri and Dolgorukovsky massifs are predominantly associated with areas near permanent and temporary watercourses. In general, the obtained maps of groundwater vulnerability are quite consistent with the known data on the hydro-geological conditions of the assessed massifs. Conclusions. The identified differences in the area ratio and spatial distribution of ground waters vulnerability categories between the assessed massifs are a consequence of local geological, geo-morphological and hydrological features. The obtained results confirm high applicability of the Mountain-Crimean regional method for groundwater vulnerability assessment, at least for the karst massifs of the Mountain Crimea. Suggestions for practical application and direction for future research. The produced groundwater vulnerability maps create a scientific basis for delineation of water protection zones, assessing the risks of groundwater pollution and developing the territorial planning schemes within studied areas. The next stage of study is an assessment of groundwater source vulnerability for individual karst springs used in water supply.

Application of the fuzzy analytic hierarchy process for water resources in the Wadi AlHasa catchment, Jordan

This article introduces a groundwater vulnerability assessment model that utilises the fuzzy analytic hierarchy process (FAHP) in the Wadi AlHasa catchment, Jordan. The assessment takes into account both geomorphological and hydrogeological variables, employing a comprehensive methodology that integrates various parameters. To evaluate the catchment, the study employs remote sensing and Geographic Information System (GIS) techniques. The analysis of the digital elevation model enables the creation of a map illustrating the diverse geomorphology of the catchment. This geomorphology significantly influences drainage density, direction, and the spatial distribution and intensity of flash flood events. Moreover, the study develops and maps a fuzzy FAHP DRASTIC vulnerability index, which proves to be a valuable tool for assessing the susceptibility of groundwater resources to contamination. The unique feature of the index is its ability to incorporate uncertain or subjective data, providing a means to evaluate the significance of various influencing factors. This information serves as critical support for decision-making and management efforts geared towards safeguarding and enhancing groundwater resources. Within the study area, the DRASTIC vulnerability index values span from 0.08325 to 0.28409, with 18% of the site exhibiting a high vulnerability rate. Additionally, the article implements a managed aquifer recharge model (MAR), with 31% of the area falling into MAR classes. Among these, 22.1% are classified as a high MAR class, while 0.7% belong to a very high MAR class. These findings underscore the feasibility of MAR projects in regions with limited water resources.