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Vulnerability maps of groundwater provide an efficient means of identifying environmental trends and prioritizing regions for prevention plans. The GIS-based DRASTIC method, however, does not consider the impact of contamination, so there is a need to modify it according to the specifics of the region and its contamination load. The aim of this study is to investigate a suitable DRASTIC modification for vulnerability assessment by changes in its rating and weighting systems. The goal is to explore and compare the impact of both objective and subjective weighting methods in the vulnerability assessment of a smaller aquifer situated beneath agricultural land. The frequency ratio (FR) method is used to adjust the DRASTIC index rates based on nitrate contamination as the main contamination from fertilizers extensively used in the study area. The DRASTIC parameters' weights are determined using two objective and subjective methods, including Shannon entropy and single-parameter sensitivity analysis (SPSA), respectively. In total, five frameworks, including FR-DRASTIC, DRASTIC-Entropy, DRASTIC-SPSA, FR-SPSA, and FR-Entropy are developed and evaluated. We validate these proposed vulnerability indices based on the nitrate concentrations in 14 samples. The results show that the vulnerability map obtained from the FR-Entropy framework is superior, showing a 0.85 correlation with nitrate concentrations. Notably, Shannon entropy as an objective weighting method outperformed the subjective SPSA approach. [ABSTRACT FROM AUTHOR]

Determining optimal exploitation from aquifers is always a major challenge, especially for aquifers facing a drop in their groundwater level. In aquifers with artificial recharge, more complex algorithms are required to determine the optimal exploitation amount. Therefore, in this study, the optimal amount of harvest from the exploitation wells has been determined using a combined simulation–optimization model considering the artificial recharge in Yasouj aquifer in Iran. The model is based on a combination of MODFLOW code and gene expression programming (GEP) simulator tool to simulate the aquifer and particle swarm optimization (PSO) to maximize the total exploitation from the aquifer. The simulation results showed that the artificial recharge was ineffective in maximum exploitation from the aquifer. As a result, considering several constraints, including the maximum pumping rate from the aquifer and the permissible drop in the groundwater level, the maximum exploitation from the aquifer was defined as the objective function. The optimization results showed that the optimal exploitation rate is equal to 8.84 million cubic meters (MCM) per year, and only 74% of the water from artificial recharge can be used based on this amount. Additionally, the most appropriate locations to exploit this amount of water are the northwest and east of the aquifer. According to the findings, it is suggested to ban exploitation from the central and southern parts of the aquifer due to the low groundwater level. The results of the sensitivity analysis show that the reduction in the maximum exploitation rate along with a 50% drop in the groundwater level play an effective role in decreasing the optimal exploitation amount. [ABSTRACT FROM AUTHOR]

The shortage of freshwater and salinization are considered two major development problems in arid and semi-arid regions. The growth of population, development of industry and agriculture, and climate change cause over-extraction of groundwater resources; consequently, the quality and quantity of groundwater decreased, especially in the arid and semi-arid areas. The present study investigates the reasons for salinization of the Kashan aquifer. In this study, 53 observation wells located in the aquifer were examined for qualitative study. A total of 80 samples were collected from selected wells over a period of 5 years (2005–2009) and analyzed for 9 chemical parameters (electrical conductivity (EC), pH, total dissolved solids (TDS), sodium (Na+), potassium (K+), calcium(Ca2+, magnesium (Mg2+), chlorine (Cl−), and bicarbonate (HCO−3)). Groundwater table study shows that the direction of groundwater flow throughout the aquifer is often from the west to the east of the aquifer, except for the northeastern part of the aquifer, where a backflow from the northeast (salt lake) into the aquifer is visible. Results of ion analysis in different areas of the aquifer indicate the occurrence of upconing phenomenon in the center and south regions and the occurrence of saline water intrusion phenomenon in northeast regions. To simulate the condition of the Kashan aquifer for the next 50 years, a model of the quantity and quality of the aquifer was developed using the SEAWAT code. According to the results, the salinization of the Kashan plain aquifer should occur due to two main reasons: irregular groundwater extraction and upconing phenomenon and the intrusion of saline water from the salt lake towards the aquifer. The Kashan aquifer salinization forecast results show that the continuation of the current pumping activities for the next 50 years should increase the numbers of wells affected by salinity. Considering the critical situation of the Kashan aquifer and the existing serious threats, serious decisions and measures for the proper management of groundwater and aquifer protection are vital. [ABSTRACT FROM AUTHOR]

Climatic and environmental stresses on water resources, increasing water demands, and farmers' adverse economic conditions are significant drivers of increased conflicts between farmers and water managers. These conflicts remain a major hurdle in sustaining water resources, which should be addressed using sustainable development concepts. A non-cooperative game model is developed to address these conflicts and to reduce the stress on an aquifer in the arid zone using sustainable development criteria (environmental, social, and economic dimensions). The multi-indicator game model extends the asymmetric Nash bargaining solution for solving conflicts using aquifer sustainability and socioeconomic indicators as satisfaction indicators for water resources managers and the farmers, respectively. Quantitative and qualitative sustainability indicators were assessed for aquifer restoration strategies. A social satisfaction indicator was also evaluated for each strategy by using a questionnaire. Groundwater withdrawal reduction, improving the artificial recharging system, optimizing the cropping pattern, and combining these strategies in two states with and without financial incentives to the farmers were assessed using a non-cooperative game to restore the aquifer. The strategy of optimizing the cropping pattern and the combined strategy of a 1% reduction in groundwater withdrawal and improving the artificial recharging were the first and second priorities, respectively. In the selected strategy, quantitative sustainability indictor, qualitative sustainability indicator and economical indictor were obtained for the government 0.53, 0.08 and 0.69 respectively. In this strategy, social satisfaction and economic indicators were 0.7 and 0.71 for farmers. The sensitivity analysis of the developed game model showed that by increasing the power of water resource managers, the groundwater withdrawal reduction strategies become the equilibrium point for the conflict solution. This result can be used to resolve conflicts and to achieve quantitative and qualitative sustainability in aquifer management. [ABSTRACT FROM AUTHOR]

In this study, after simulating 5 years of saltwater intrusion with SEAWAT package in Astaneh–Kouchesfahan coastal aquifer, Iran, 19 strategies, including managerial, structural, and combined strategies, were investigated to reduce the saltwater intrusion. Since managerial solutions cause users' dissatisfaction and structural solutions increase the costs, two-player game theory was used to identify the most appropriate solution. According to the results obtained from game theory, the two strategies of implementing artificial recharge and the construction of an underground dam had the greatest impact on preventing the saltwater intrusion with the highest satisfaction of stakeholders, and these strategies decreased the extent of saltwater intrusion into the aquifer from 740 m by 150 and 300 m, respectively, after 5 years. Therefore, the combined simulator–optimizer method presented in this study can be used to evaluate various solutions, and the most appropriate solution can be proposed with the lowest cost and maximum satisfaction for the sustainable management of coastal aquifers. [ABSTRACT FROM AUTHOR]

A new approach, developed for coastal aquifers, consists of determination of saltwater-freshwater interface as well as obtaining map of groundwater vulnerability, for which a number of methods have been provided, including index method and numerical modelling. In the previous studies, the common vulnerability methods such as DRASTIC have not took the coastal regions into account, or that method of GALDIT, proposed for coastal regions, assumed the saltwater intrusion fixed. The vulnerability of coastal aquifer is determined in two distinct regions (coastal and non-coastal areas) using two distinct methods (Index and Numerical modelling) and finally they are combined together. The results of this study in coastal aquifer in north of Iran suggest that due to overexploitation, the intrusion of saltwater from coastline into centre of aquifer is as deep as 720 m, inducing very high vulnerability in coastal regions. The correlation of DRASTICSea method with qualitative parameter is obtained 68%. [ABSTRACT FROM AUTHOR]

This study proposes a new approach to establish a multi-parameter risk mapping method by employing the K-Means clustering technique. Accordingly, spatial assessment of arsenic (As), nitrate (NO3) and total dissolved solids (TDS) were carried out based on the type of land use to estimate contamination potential in an aquifer. Since risk mapping is always associated with the occurrence probability of a phenomenon, pollution occurrence probability was then obtained using the fuzzy C-means clustering. The results reveal that NO3 and As contamination levels increase from the first cluster (C1), covers 22.3% of the aquifer, to C5 encompassing 35.1% of the aquifer devoted to extensive industrial and agricultural activities. Fuzzy clustering results show that the pollution occurrence probability in each aquifer cell varied from less than 30 to more than 90%. Moreover, the results show, industrial and agricultural land uses cover about 70% of the areas with high risk of contamination. [ABSTRACT FROM AUTHOR]

The main objective of this study is to integrate adaptive neuro-fuzzy inference system (ANFIS), support vector machine (SVM) and artificial neural network (ANN) to design an integrated supervised committee machine artificial intelligence (SCMAI) model to spatially predict the groundwater vulnerability to seawater intrusion in Gharesoo-Gorgan Rood coastal aquifer placed in the northern part of Iran. Six hydrological GALDIT parameters (i.e., G groundwater occurrence, A aquifer hydraulic conductivity, L level of groundwater above sea level, D distance from the shore, I impact of the existing status of seawater intrusion in the region, and T thickness of the aquifer) were considered as inputs for each model. In the training step, the values of GALDIT's vulnerability index were conditioned by using the values of TDS concentration in order to obtain the conditioned vulnerability index (CVI). The CVI was considered as the target for each model. After training the models, each model was tested using a separate TDS dataset. The results indicated that the ANN and ANFIS algorithms performed better than the SVM algorithm. The values of correlation were obtained as 88, 87, and 80% for ANN, ANFIS, and SVM models, respectively. In the testing step of the SCMAI model, the values of RMSE, R2, and r were obtained as 6.4, 0.95, and 97%, respectively. Overall, SCMAI model outperformed other models to spatially predicting vulnerable zones. The result of the SCMAI model confirmed that the western zones along the shoreline had the highest vulnerability to seawater intrusion; therefore, it seems critical to consider emergency protection plans for study area. [ABSTRACT FROM AUTHOR]

One of the significant challenges in applying vulnerability methods is their dependence on the same weights and ranks for each parameter. Therefore, to modify these methods, a clustering technique independent of ranks and weights and based only on the nature of data was used in the first step in this study for vulnerability mapping. Moreover, Principal Component Analysis (PCA) was employed to consider all parameters and select the effective ones. After reviewing the literature on different vulnerability assessment methods, 14 parameters involved in determining the vulnerability of the Varamin Aquifer in Iran were selected. The principal component analysis revealed that seven of them were the major ones. In the next step, the vulnerability map of the aquifer was prepared by using the C-Means, the K-Medoids, and the K-Means clustering methods. It was found that the fuzzy C-Means clustering method outperformed others with a CI of 260. [ABSTRACT FROM AUTHOR]

Hybrid and integrated techniques can be used to investigate intrinsic uncertainties of the overlay and index groundwater vulnerability assessment methods. The development of a robust groundwater vulnerability assessment framework for precise identification of susceptible zones may contribute to more efficient policies and plans for sustainable managements. To achieve an overall view of the groundwater pollution potential, the DRASTIC framework (Depth to the water table, net Recharge, Aquifer media, Soil media, Topography, Impact of the vadose zone, and hydraulic Conductivity) can be used for intrinsic vulnerability assessment. However, the unreliability of this index is because of its inherent drawbacks, including the weight and rating assignment subjectivity. To modify the rating range, this study recommended a new DRASTIC modification using a recently introduced Multi-Criteria Decision-Making (MCDM) method, namely the Stepwise Weight Assessment Ratio Analysis (SWARA); in addition, the Entropy and Genetic Algorithm (GA) methods were employed to alter the relative weights of DRASTIC parameters. To improve the DRASTIC index, nitrate concentration data from 50 observation wells in the study site were used. To assess the models' overall performance, the datasets obtained from new observation wells, receiver operating characteristic (ROC) curve, and area under the ROC curve (AUC) were studied. The experiments were carried out in the aquifer of the Qazvin Plain in Iran. The results indicated the higher performance of the modified DRASTIC framework, manifested as an increase in the AUC value from 0.58 for generic DRASTIC to 0.68 for the SWARA-Ent framework and 0.74 for the SWARA-GA framework. The application of the SWARA technique, as an effective MCDM method, resulted in the DRASTIC rating system enhancement. The generic DRASTIC optimization by integrating SWARA and GA provided an effective framework to assess groundwater vulnerability to nitrate contamination in the Qazvin Plain. [ABSTRACT FROM AUTHOR]

Identification of the uncertain parameters, which affecting on the qualitative behavior of the aquifer, and determining their effect on the uncertainty of the simulated nitrate concentration (NC) is one of the major challenges in the qualitative monitoring of aquifers. In this study, in order to determine the quantitative amount of uncertainty related to the simulated nitrate, an approach based on a hybrid of Groundwater Modeling System (GMS) model and Fuzzy Vertex Method (FVM) method was developed using the developed code for the relationship between aquifer simulation model and MATLAB environment. In this model, hydraulic conductivity, NC in aquifer recharge sources, longitudinal dispersivity coefficient, and specific storage parameters were considered as uncertain parameters in the distributed simulation model of the Ardabil aquifer. In the proposed approach, first the quantitative and qualitative (QQ) model of the aquifer was prepared using the GMS model and calibrated. Then, using the FVM method and developed MATALB code, the uncertain values appropriate for each of the aquifer active cells were determined. The results obtained from the monthly NC uncertainty show that with increasing the level of uncertainty, the uncertainty of the simulated NC increases significantly. For example, can be mentioned a 14-fold increase in the number of cells with variation of NC less than 10% in the September month. Also, the lowest and highest variation in the deterministic amount of NC is related to the months of Nov. and Sep. with concentration variations equal to [− 8.5, 8.35] and [− 23.43, 19.8] mg/L, respectively. The findings of this study show that the application of at least 10% uncertainty in the deterministic values of the simulated NC is necessary to provide a suitable view for quality monitoring of aquifer. A quantitative amount of monthly uncertainty in areas with nitrate concentrations greater than 50 mg/L indicates that the amount of uncertainty in these areas is higher than areas with nitrate concentrations less than 50 mg/L. This leads to errors in the monitoring of contaminated areas to eliminate contamination and quality restoration. Also, centralization of uncertainty is mainly concentrated in the northeastern, western and southwestern parts of Ardabil plain and the severity of uncertainty in the mentioned areas increases with the intensification of uncertainty and continues to the central areas. Finally, it must be said that hydraulic conductivity and NC in aquifer recharge sources, respectively, play the most important role in creating uncertainty and is necessary to be considered in the NC simulation models. [ABSTRACT FROM AUTHOR]

Improving the groundwater governance structure can help reduce groundwater decline and improve the state of an aquifer. This study develops an approach to modify groundwater governance based on a participatory, water-food-energy (WFE) nexus. Given the need for the participation of actors in the decision-making for the WFE nexus, we identified and selected some powerful nexus actors. Using the actor's viewpoints, factors that led to excessive withdrawal of groundwater resources in each sector were identified as governance challenges. Using the DPSIR (Driving Force-Pressure-State-Impact-Response) approach, the actors assessed the cause-and-effect relationships of the groundwater governance challenges and proposed modification in the groundwater governance. Thirteen groundwater governance scenarios were defined. Then, the impact of scenarios on WFE sectors was evaluated by the participation of nexus actors and the nexus assessment ranking of the scenarios. The results show that, out of the 13 groundwater governance scenarios, only seven scenarios had positive effects in all three sectors (WFE). The scenario of developing and enforcing region-specific cropping patterns and value-chain management has the highest rank. This paper highlights the need for the participation of actors in decision-making and the use of WFE nexus in modifying the groundwater governance system. [ABSTRACT FROM AUTHOR]

One of the major shortcomings with GALDIT model is the difficulty in specifying numerical constant values for the rating and weighting system of parameters of interest. The frequency ratio (FR) and genetic algorithm (GA) methods were applied in this research for the first time to improve the rates and weights of the GALDIT model. FR model was used to modify the rates of this model. Additionally, genetic algorithm was used to optimize the weights of GALDIT model based on the hydrological characteristics of the aquifer and the values of TDS parameter. The correlation between hybrid models of GALDIT-FR and GALDIT-GA were obtained as 0.69 and 0.61, respectively, while this correlation was increased up to 0.76 after combining the rates modified by FR statistical method and optimal weights of the genetic algorithm. The results of this model showed that the northwest and west parts of the study area have the highest vulnerability to seawater intrusion. So, it was concluded that a combination of meta-heuristic algorithm and statistical method provides more accurate result in the study region. [ABSTRACT FROM AUTHOR]

Distributed modeling provides for mapping of spatial and temporal patterns of highly stressed regions, and it offers local solutions to reduce stress in aquifers. In this study, the groundwater stress index (GWSI) is evaluated based on the groundwater footprint index over the Varamin aquifer in Iran. Using ArcGIS software, all necessary layers were produced and then input into the Groundwater Modeling System software to evaluate GWSI. The results show that distributed modeling offers a more accurate assessment of GWSI than water budget analysis. The minimum and maximum values of the GWSI calculated by the distributed model are 2.4 and 1.4 times, respectively, higher than those values obtained in previous studies. Besides, a significant agreement was observed between highly stressed areas and agricultural land use. Furthermore, the results obtained from comparison between stress pattern and land subsidence indicated that only 10% of the area under subsidence was caused by groundwater stress. Applying appropriate scenarios in the future can be useful to reduce water stress and its increasing trend. [ABSTRACT FROM AUTHOR]

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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. [ABSTRACT FROM AUTHOR]

Recently, groundwater vulnerability assessment of coastal aquifers using the GALDIT framework has been widely used to investigate the process of groundwater contamination. This study proposes multi-attribute decision-making (MADM) entropy and Wilcoxon non-parametric statistical test methods to improve the vulnerability index of coastal aquifers. The rates and weights of this framework were modified using Wilcoxon non-parametric and entropy methods, respectively, and a combined framework of GALDIT-entropy, Wilcoxon-GALDIT, and Wilcoxon-entropy was obtained. Pearson correlation coefficients between the mentioned vulnerability indices and total-dissolved solids (TDS) of 0.51, 0.66 and 0.75, respectively, were obtained. According to the results, the Wilcoxon-entropy index had the highest correlation with TDS. Generally, it can be concluded that the proposed frameworks provide a more accurate estimation of vulnerability distribution in coastal aquifers. [ABSTRACT FROM AUTHOR]

In recent years, environmental assessments of groundwater resources have resulted in the development of models that help identify the vulnerable zones. An aquifer is investigated using both GALDIT and DRASTIC indices. The GALDIT model is developed to determine the vulnerability of coastal aquifers in terms of saltwater intrusion whereas the DRASTIC model is generally applicable to all aquifers. Having compared the results of both the GALDIT and DRASTIC models with quality parameters, the salinity model proved to be more appropriate in identifying the vulnerability of coastal aquifers. The results show a Pearson correlation coefficient between TDS and the GALDIT vulnerability map of 0.58 while the corresponding value for the DRASTIC index is 0.48. EDITOR D. Koutsoyiannis ASSOCIATE EDITOR A. Fiori [ABSTRACT FROM AUTHOR]

In this study the vulnerability of aquifer is investigated by fuzziness of the different layers. The vulnerable potential of different location within the basin by most accuracy was traced. In this method by the use of max lambda the weights of parameters were become fuzzy and quantity weights parameters has been fuzzy by the use of membership function. The quality weights were done by the discrete functions became fuzzy. The final map showed that some parts of north and northeast parts of the aquifer were most vulnerable locations. The correlation coefficient of vulnerability and nitrate concentration by standard method was estimated 49 percent and in the fuzzy method 53 percent that showed fuzzy method is more realistic. In FAHP method 13.87% of the plain area was by the low vulnerability, 11.96% by low to moderate vulnerability, 41.24% by moderate to high vulnerability, and 32.92% by high vulnerability. [ABSTRACT FROM AUTHOR]

The objective of this research is to indicate how the vulnerability potential to pollution may be assessed more accurately by correcting both the ratings and weights of the parameters used in the popular EPA DRASTIC method. In order to demonstrate the applicability of the proposed method, the Astaneh Aquifer located in northern Iran was selected. Nitrate concentrations were used to correlate the pollution potential in the aquifer to the DRASTIC index. The results indicated that the modified DRASTIC was significantly superior to the original method. [ABSTRACT FROM PUBLISHER]

[Display omitted] • Applying DPSIR-GOF combined framework in order to remedy the groundwater. • Using both technical and economic indicators to prioritize proposed scenarios. • Using MODFLOW model for groundwater molding and prioritizing the proposed scenarios. With increasing exploitation of groundwater resources, integrated assessment of aquifers is an essential step to maintain aquifers' sustainability. The DPSIR-GOF (Drivers, pressures, states, impacts, responses-Goal oriented framework) combined approach is used in this study to conceptualize and identify various factors affecting the Najafabad aquifer system in Iran. Neither DPSIR nor GOF frameworks, when used separately, can consider a specific prioritization for the solutions and the proposed scenarios nor can provide a comprehensive view of the system from the past to the future. Therefore, the unique combination of the DPSIR and GOF frameworks in this study is used to conceptualize and evaluate the aquifer system from the past to the future, considering the environmental, economic and social dimensions of sustainable development. To implement this combined approach hydrological data (groundwater level, evaporation rate, precipitation rate, temperature rate, etc.) and economic and social data (population rate, employment status, income level, literacy level, etc.) were used. After identifying the links and dimensions of the DPSIR-GOF framework, some scenarios are proposed to improve the aquifer's state. Furthermore, evaluation indicators including technical indicators (aquifer sustainability and dryness) and economic indicators (productivity and cost-benefit analysis) are used to determine the performance of management scenarios and prioritize their effectiveness in restoring and sustaining the aquifer. Finally, the scenarios of 5% (R1) and 10% (R2) reduction in groundwater exploitation, as well as 10% (C1) and 20% (C2) reduction of cultivated area were introduced. Results show that a decrease in exploitations over 30 years effectively maintained the aquifer balance in all four scenarios. Scenario R2 , with crop per drop, benefit per drop, and CBA of 1.62 , 9.3 , and 0.39 , respectively, was preferred to other scenarios during the 30 years of the simulation period. Based on a 41-year sustainability index, scenario R2 performed better in reducing the impact of drought than other scenarios. Sources of uncertainties involved in this study were hydrological data including aquifer inputs and outputs, agricultural costs and crop production based on region's inflation rate. The findings can help decision-makers and managers choose the most appropriate approach and policy to obtain sustainable groundwater resource systems and maintain economic and social security. [ABSTRACT FROM AUTHOR]

In this study, a hybrid multiple criteria decision-making (HMCDM) model was proposed for prioritizing scenarios for managing groundwater use from an aquifer. Three scenarios, including the construction of subsurface dams, the use of artificial recharge and reducing groundwater use by 5% and 10% were considered to assess the most sustainable development approach. The examined MCDM models were: simple additive weighting (SAW); and MTAHP which is a hybridization of the modified TOPSIS and the analytic hierarchy process models. The criteria proposed for determining the order preference of the scenarios included the sustainable development index (IU) and a modified water exploitation index as well as economic, social and environmental indices. To assess the technical and economic impacts of the management scenarios, modeling of the aquifer was simulated for a 3-year period using these scenarios. The results of the assessment indicated that the scenario of water withdrawal reduction by 10% was the best scenario determined in MTAHP followed by a reduction in groundwater withdrawal by 5%, the use of artificial recharge and the construction of a subsurface dam, respectively. The difference between the results of MTAHP and SAW models was in their first and third ranks, in such a way artificial recharge scored the first rank in SAW model and the third rank in MTAHP model, also withdrawal reduction by 10% scored third rank in SAW model and first rank in MTAHP model. The results of these two models have demonstrated that the construction of a subsurface dam in Shahrekord aquifer is not an appropriate management option. According to the results of this study, MTAHP models can be applied for ranking feasible management scenarios in aquifers using the redefined sustainable development and modified groundwater exploitation indices introduced in this study. [ABSTRACT FROM AUTHOR]

Highlights • Proposing soil mulching for enhancing groundwater resources and a model to assess it. • Assessing the use of various mulches in increasing deep percolation of rainfalls. • Deep percolation rate is higher in precipitations with shorter time intervals. Abstract In this paper, a model is proposed for the assessment of the effectiveness of various mulches in increasing deep percolation of rainfalls for enhancing arid zones aquifers. For this purpose, 8 precipitations were selected from the Intensity-Duration-Frequency (IDF) curves of the study area with a return period of 2 and 5 years. The deep percolation of these precipitations were examined in lysimeters with gravel, sand and mixed mulches and without any mulch. Then 192 data of soil moisture, daily maximum air-temperature and deep percolation were measured for driving empirical equations. Moreover, the efficiency and accuracy of these empirical equations were investigated using Coefficient of Determination (CD) and Nash–Sutcliffe Efficiency Coefficient (NSEC). The results showed that the obtained empirical equations could estimate deep percolation and evaporation with an acceptable accuracy. Using these equations and the soil-water balance equation, a soil moisture model was developed for the assessment of deep percolation. Then it was examined to evaluate the efficiency of the mulched soils in increasing soil moisture and aquifer recharging of three years' precipitations in Shahrekord plain, Iran. The results showed that the deep percolation increased in all examined mulched soils compared to unmulched soil, its maximum and cumulative increase were in gravel mulch with 21.3% and 30%, respectively. Furthermore, groundwater modeling results showed that the mulching could improve groundwater level as 0.34 m over a three year period. Finally, this paper proposes soil mulching for enhancing groundwater resources and a model to assess it. [ABSTRACT FROM AUTHOR]

Aquifer salinization has recently increased significantly due to human activity and has caused irreparable environmental and economic effects. In this research, a new method is proposed for modeling the vulnerability to salinity for the Ghaemshahr-juybar aquifer. Specifically, the GALDIT (Sea water intrusion) and TAWLBIC (Saltwater up-coning) indices were combined to produce a map of vulnerability (Comprehensive Salinity Index or CSI) to seawater intrusion of a region near the coast and saltwater up-coning away from the coast, respectively. Single parameter and removal layer sensitivity analysis were performed in order to identify the sensitive parameters and achieve optimal weights (through the single-parameter method) of contributing factors in all three methods. The three optimized methods produced were GALDIT-Opt, TAWLBIC-Opt and CSI-Opt. To assess the accuracy of the original maps and optimal ones, the Pearson correlation was used. Results indicated that the Pearson correlation of the optimized GALDIT, TAWLBIC and CSI model was better than GALDIT, TAWLBIC and CSI. The results show that the increase in correlation between EC (Electrical Conductivity), TDS (Total Dissolved Solids) and SAR (Sodium Adsorption Ratio) from the GALDIT model to the CSI-Opt model from values of 0.64, 0.56 and 0.68 has improved to values of 0.81, 0.88 and 0.91, respectively. The highest concentration of EC, with a value of 7050 µs/cm, is sampled in the areas of the east and northwest of the Ghaemshahr-juybar aquifer, which are classified in the CSI-Opt model as high and very high vulnerability levels. The highest concentration of TDS and SAR has been found in the east, northwest and northeast of the Ghaemshahr-juybar aquifer with a value of 4724 ppm for TDS and 14 mg/l for SAR that have been modeled in the CSI-Opt index as highly vulnerable areas. Eventually, CSI mapping can be used as an efficient tool in prioritizing in terms of the vulnerability to aquifer salinity, carrying out adjustments, recharge, and adaptation policies for this issue. [ABSTRACT FROM AUTHOR]

[Display omitted] • DRASTIC performed better than SINTACS and GODS for an intrinsic vulnerability assessment. • Use of a new MADM method for DRASTIC rates and weights improvement: SWARA. • Use of a new hybrid evolutionary algorithm for optimizing groundwater vulnerability assessment framework: PSO.GA. • The hybrid SWARA-PSO-GA method has the most predictive power. Limited hydrogeological data accessibility leads scholars to improve the robustness of present qualitative groundwater vulnerability assessment methods using mathematical techniques. In the present study, we implemented three GIS-based groundwater vulnerability assessment indices, namely DRASTIC (Depth to water table, net Recharge, Aquifer media, Soil media, Topography, Impact of vadose zone, and hydraulic Conductivity), SINTACS (Soggicenza, Infiltrazione, Non saturo, Tipologia della copertura, Acquifero, Conducibilità, and Superficie topografica), and GODS (Groundwater confinement, Overlying strata, Depth to groundwater, and Soil media) to assess the groundwater vulnerability levels. Although DRASTIC results showed better performance with respect to the nitrate concentration data from 50 observation wells in the study site, the index is still unreliable due to its inherent drawbacks, including subjectivity. Hybrid PSO-GA method is a successful optimization algorithm gathering the advantages of Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) while avoiding their shortcomings. The DRASTIC weighting system is optimized using PSO-GA optimization algorithm. Also, Step-wise Weight Assessment Ratio Analysis (SWARA) as a Multi-Attribute Decision Making (MADM) method is applied for changing ranges of DRASTIC rates and weights. The vulnerability indices obtained from SWARA-SWARA, DRASTIC-PSO-GA, and SWARA-PSO-GA frameworks are evaluated and compared with generic DRASTIC regarding the nitrate concentration dataset by employing Area Under the ROC Curve (AUC) and Grey relational analysis methods. Results show a noticeable improvement of correlation between indices and observed nitrate concentration after modifications and optimizations. The new hybrid SWARA-PSO-GA framework is the most effective framework in assessing the vulnerability of the present study area. [ABSTRACT FROM AUTHOR]

• Applying the GWO algorithm to optimize the weights of GALDIT framework. • Using Genetic Algorithm for optimization GALDIT's weights. • Comparison meta -heuristic algorithms for evaluation coastal aquifer vulnerability. • Using the spearman correlation as an objective function. Creating a reliable groundwater vulnerability map is a key solution for protecting the groundwater resources and further planning in coastal aquifers. The GALDIT framework, which is an abbreviation for six parameters of Groundwater occurrence, Aquifer hydraulic conductivity, Level of groundwater above sea level, Distance from the shoreline, Impact of the existing status of seawater intrusion, and Thickness of the aquifer, is a well-known framework for evaluating the groundwater vulnerability in coastal zones. In this study, two meta -heuristic algorithms of Grey Wolf Optimizer (GWO) and Genetic Algorithm (GA) were proposed to optimize the weights of GALDIT framework. This framework was tested in the Gharesoo-Gorgan Rood coastal aquifer located in the north of Iran. The GALDIT index illustrated poor evaluation of vulnerability to seawater intrusion. Contrariwise, GALDIT-GWO and GALDIT-GA frameworks provided results that are more reasonable. Both vulnerability maps showed a close similarity in terms of vulnerability to seawater intrusion. The vulnerability maps demonstrated that the west and northwest parts of the study area suffer from seawater intrusion. Additionally, the values of Spearman's rank correlation coefficient between the indices of GALDIT, GALDIT-GWO and GALDIT-GA and the parameter of Cl/HCO 3 were obtained as 0.31, 0.53, and 0.49 and the corresponding values for the parameter of TDS were obtained 0.45, 0.64 and 0.60, respectively. Therefore, it can be concluded that the proposed optimization models are able to provide accurate results. Furthermore, these models reduce the subjectivity and increase the capability of the GALDIT index. [ABSTRACT FROM AUTHOR]