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.

Groundwater serves as a primary water source for various purposes. Therefore, aquifer pollution poses a critical threat to human health and the environment. Identifying the aquifer\'s highly vulnerable areas to pollution is necessary to implement appropriate remedial measures, thus ensuring groundwater sustainability. This paper aims to enhance groundwater vulnerability assessment (GWVA) to manage aquifer quality effectively. The study focuses on the El Orjane Aquifer in the Moulouya basin, Morocco, which is facing significant degradation due to olive mill wastewater. Groundwater vulnerability maps (GVMs) were generated using the DRASTIC, Pesticide DRASTIC, SINTACS, and SI methods. To assess the effectiveness of the proposed improvements, 24 piezometers were installed to measure nitrate concentrations, a common indicator of groundwater contamination. This study aimed to enhance GWVA by incorporating new layers, such as land use, and adjusting parameter rates based on a comprehensive sensitivity analysis. The results demonstrate a significant increase in Pearson correlation values (PCV) between the produced GVMs and measured nitrate concentrations. For instance, the PCV for the DRASTIC method improved from 0.42 to 0.75 after adding the land use layer and adjusting parameter rates using the Wilcoxon method. These findings offer valuable insights for accurately assessing groundwater vulnerability in areas with similar hazards and hydrological conditions, particularly in semi-arid and arid regions. They contribute to improving groundwater and environmental management practices, ensuring the long-term sustainability of aquifers.

A vulnerability assessment of the aquifers in the agricultural area of Zacharo in SW, Peloponnese, Greece, was conducted using the DRASTIC index and the susceptibility index (SI). Sensitivity analysis was conducted and thematic maps for each parameter were generated to analyse the impact of individual parameter on the collective groundwater vulnerability. Results derived from the DRASTIC and SI maps revealed that the extremely highly vulnerable zones are concentrated at three coastal sites in the western part of the study area. Data from these maps also indicate low vulnerability areas throughout the eastern part of the region. The distribution of nitrate concentrations in groundwater is better correlated with the DRASTIC (79.2%) compared to SI (60.2%). Neither method takes into consideration the impact of dilution and nitrate to ammonium reduction, on the nitrate content of groundwater, thus overestimating the vulnerability index. Moreover, the SI method overestimates the impact of olive groves\' land use type on the susceptibility index, thus resulting to a lower correlation with the observed nitrate concentrations.

The quality of groundwater in the study watershed has worsened because of industrial effluents and residential wastes from the urbanized cities; therefore, there is an important need to explore the aquifer vulnerability to pollution for sustainable groundwater management in the Irrigated Indus Basin (IIB). This study proposed a novel methodology to quantify groundwater vulnerability using two fully independent methodologies: the first by reintroducing an improved recharge factor (R) map and the second by incorporating three different weight and rating schemes into a traditional DRASTIC framework to improve the performance of the DRASTIC approach. In the current study, we composed a recharge map from Soil and Water Assessment Tool (SWAT) output (namely SWAT recharge map) with a drainage density map to retrieve an improved composite recharge map (SWAT-CRM). SWAT-CRM along with other thematic layers was combined using weightage overlay analysis to prepare the maps of groundwater vulnerability index (VI). The weight scale (w) and rating scale (r) were assigned based on a survey of available literature, and we then amended them using the analytical hierarchy process (AHP) and a probability frequency ratio (PFR) technique. Results depicted that the region under high groundwater vulnerability was found to be 5-22% using traditional recharge maps, while those are 9-23% using improved SWAT-CRM. The area under the curve (AUC) revealed that groundwater vulnerability zones predicted with SWAT-CRM outperformed the DRASTIC model applied with the traditional recharge map. Groundwater electrical conductivity (EC) was>2500 mS/cm in the high groundwater vulnerability zones, while it was <1000 mS/cm in the low groundwater vulnerability zones. The outcomes of this study can be used to improve the sustainability of the groundwater resources in IIB through proper land-use management practices.

Recognizing the vulnerable areas for contamination is a feasible way to protect groundwater resources. The main contribution of the paper is developing a hybrid statistical decision-making model for evaluating the vulnerability of Shiraz aquifer, southern Iran, with modified DRASTIC (depth to the water table, net recharge, aquifer media, soil media, topography, impact of the vadose zone, and hydraulic conductivity) by using the genetic algorithm (GA), the analytical hierarchy process (AHP) method, and factorial analysis (FA). First, considering the variation of the uncertain parameters, 32 scenarios were defined to perform factorial analysis. Then using the AHP method and GA, DRASTIC parameters were rated and weighted in all scenarios. To achieve the optimal weights for parameters, the objective function in GA was maximizing the correlation coefficient between the vulnerability index and the nitrate concentration. The single and interactive effects of parameters on groundwater vulnerability were analyzed by factorial analysis. The results revealed that the net recharge had the highest single effect, and the resulted effect between net recharge and hydraulic conductivity was the most significant interactive effect on the objective function. Besides, the variation of aquifer media does not change the objective function. The application of the proposed method leads to a precise groundwater vulnerability map. This research provides valuable knowledge for assessing groundwater vulnerability and enables decision-makers to apply groundwater vulnerability information in future water resources management plans.

Groundwater vulnerability assessment using the fuzzy logic technique is attempted in this study. A hierarchical fuzzy inference system is created to serve the selected objective. The parameters considered in this study are similar to the seven parameters used in conventional DRASTIC methods; however, the effect of land use and land cover is studied by including it as an additional parameter in a model. A hierarchy is created by comparing two input parameters, say (D and R), and the output of the same is paired as an input with the third parameter (A) and so on using the fuzzy toolbox in MATLAB. Thus, the final output of fuzzy inference systems six and seven (FI6 and FI7) is defuzzified and mapped using ArcGIS to obtain the groundwater vulnerability zones by fuzzy DRASTIC and fuzzy DRASTIC-L. Each map is grouped into five vulnerability classes: very high, high, moderate, low, and very low. Further, the results were validated using the observed nitrate concentration from 51 groundwater sampling points. The receiver operating curve (ROC) technique is adopted to determine the best suitable model for the selected study. From this, area under the curve is estimated and found to be 0.83 for fuzzy DRASTIC and 0.90 for fuzzy DRASTIC-L; the study concludes that fuzzy DRASTIC-L has a better value of AUC suits best for assessing the groundwater vulnerability in Thoothukudi District.

Nangasai basin is a semi-arid watershed where agriculture is the main source of economy. In present day, increasing population demands increase in food productivity which leads to increase use of fertilizers and chemical pesticides in agriculture. These fertilizers on the other hand mix up with the groundwater and increase the pollution, which affects human health adversely. So, for controlling the groundwater contamination risk proper water resource management and assessment of groundwater vulnerability is extremely important. Total 7 hydrogeological parameters have been considered for this study, and the final groundwater vulnerability map has been prepared by overlay weighted method with the help of DRASTIC index, which is classified into 5 vulnerable classes (very high, high, moderate, low, and very low). In the south and south-eastern regions of the basin namely Deghi, Bankada, Baram, Macha, Katin, Tilabani high groundwater contamination is been observed. For validating the model, the water quality parameters-nitrate and TDS have been used with the accuracy of 89% and 86% respectively. Using effective as well as scientifically approved methods, the anthropogenic and agricultural contamination can be controlled and managed which will lower the risk of contamination. This map can be further utilized as a base map for management of groundwater pollution and its planning.

Groundwater protection against agricultural diffuse nitrate pollution is of paramount importance for safeguarding groundwater-dependent aquatic ecosystems and protecting human health by securing clean groundwater for drinking water production. Nitrate vulnerability assessment of aquifers is the core of a scientifically sound strategy for management and protection of groundwater by authorities. A multitude of methods exists for assessing intrinsic aquifer vulnerability. The objective of this paper is to develop a nitrate-specific groundwater vulnerability assessment method based on the globally recognized DRASTIC method, which was developed by the US Environmental Protection Agency in the 1980s. We propose a new method \"DRASTIC-N″ for assessing aquifer nitrate vulnerability, which for the first time expands the seven original geological and hydrogeological parameters with a geochemical parameter for redox condition. The development of DRASTIC-N is based on the longstanding Danish practice of performing detailed groundwater mapping based on dense sampling of geophysical, geological, and geochemical data. DRASTIC-N is compared to the widely used and documented Danish nitrate vulnerability assessment method SCANVA in a study area where the primary aquifer used for drinking water production is composed of heterogeneous sandy glacial deposits. Both SCANVA and DRASTIC-N result in vulnerability maps, which show similar patterns of nitrate vulnerability with a fair overall agreement of 71%. DRASTIC-N provides a framework for systematic and transparent application, which can facilitate stakeholder involvement and help authorities in groundwater protection and decision-making with regards to nitrate pollution. DRASTIC-N is suitable for nitrate vulnerability assessments of glacially deposited sandy aquifers, an abundant and important water resource worldwide, potentially threatened by nitrate pollution from anthropogenic activities.

Shallow groundwater vulnerability mapping of the southwestern Nigeria sedimentary basin was assessed in this study with the aim of developing a regional-based vulnerability map for the area based on assessing the intrinsic ability of the aquifer overlying beds to filter and degrade migrating pollutant. The mapping includes using the established seven parameter-based DRASTIC vulnerability methodology. Furthermore, the developed vulnerability map was subjected to sensitivity analysis as a validation approach. This approach includes single-parameter sensitivity, map removal sensitivity, and DRASTIC parameter correlation analysis. Of the Dahomey Basin, 21% was classified as high-vulnerability and at risk of pollution, 61% as moderate vulnerability, and 18% as low vulnerability. Low vulnerability areas of the basin are characterised by thick vadose zones, low precipitation, compacted soils, high slopes, and high depth to groundwater. High-vulnerability areas which are prone to pollution are regions closer to the coast with flat slopes and frequent precipitation. Sensitivity of the vulnerability map show the greatest impact with the removal of topography, soil media, and depth to groundwater and least impact with the removal of the vadose zone. Due to the subjectivity of the DRASTIC method, the most important single parameter affecting the rating system of the Dahomey Basin DRASTIC map is the impact of the vadose zone, followed by the net recharge and hydraulic conductivity. The DRASTIC vulnerability map can be useful in planning and siting activities that generate pollutants (e.g., landfill, soak away, automobile workshops, and petrochemical industries) which pollute the environment, groundwater, and eventually impact the environmental health of the Dahomey Basin\'s inhabitants.

Effects of pollution caused by seawater intrusion into groundwater in coastal aquifers cannot be ignored. Identification of areas exposed to this pollution by preparing vulnerability maps is one way of preventing aquifer pollution. In its primary section, the present study compared three different index ranking methods of DRASTIC, GALDIT, and SINTACS to select an optimal model for determining vulnerability of the Gharesoo-Gorgan Rood coastal aquifer. Initial results led to selection of the GALDIT model for vulnerability assessment of the selected coastal aquifer. Since this type of models use a rating system, the model must be modified and optimized in various regions to show the vulnerable areas more accurately. In the next step, and for the first time, the ratings in this index were modified using the Wilcoxon nonparametric statistical method and its weights were optimized employing particle swarm optimization (PSO) and single-parameter sensitivity analysis (SPSA) methods. Finally, in order to select the best hybrid model, the total dissolved solids (TDS) parameter was used to determine correlation coefficients. Results indicated that the GALDT model modified by the Wilcoxon-PSO method has the strongest correlation (0.77) with the TDS parameter. Moreover, the correlations of the Wilcoxon-GALDIT and Wilcoxon-SPSA models were 0.66 and 0.73, respectively. Final results of the Wilcoxon-PSO model revealed that the northwestern and western areas of the study region needed considerable protection against pollution. In general, we can conclude that by combining statistical, mathematical, and metaheuristic methods, we can obtain more accurate results for preparing vulnerability maps.