Population growth and increasing demand for water have posed a significant challenge to access to... more Population growth and increasing demand for water have posed a significant challenge to access to safe water resources. Climate change and land use in the not-too-distant future add to the complexity of this challenge. Therefore, it is essential to achieve reliable methods for predicting changes in aquifer storage to plan for the sustainable use of groundwater resources. This study aimed to investigate the management, protection, and sustainable use of groundwater resources under climate change and land use change conditions. In this regard, groundwater supply and demand in one of the important plains in Iran (Hashtgerd plain) for 2020 as the base year was simulated to forecast the trends until 2050 by considering climate change and land use to develop management scenarios to adapt to these conditions using the WEAP model. First, climate change prediction was performed using the HadGEM2-ES model under two emission scenarios, RCP2.6, and RCP8.5, of the IPCC Fifth Assessment Report. The LARS-WG model was used to downscale the climatic data, while land use mapping was performed using Landsat satellite images of 1990, 2005, and 2020 in ENVI 5.3 software. Then, the Markov chain method implemented in TerrSet software was used to model land use change for 2050. The effect of climate change and land use on the decrease of groundwater level was then simulated using the MODFLOW model for the period 2020-2050. In order to manage the water allocation in the area, the information obtained from MODFLOW was transferred to the WEAP model using Link Kitchen interface software. The effects of various management scenarios such as increasing irrigation efficiency, reducing the loss of drinking water distribution networks, and allocating water from the transmission line were evaluated on the adaptation to climate change and land use for a 30-year period. The results showed that with the simultaneous consideration of climate change and land use in the most critical state, the average drop in groundwater level would reach 58 m during the study period, and aquifer reserves will be reduced by more than 50%. The evaluation of management scenarios showed that their implementation not only will protect aquifer reserves but, in addition to meeting 100% of the water needs, will result in sustainable exploitation of groundwater resources.
In this study, after simulating five years of saltwater intrusion with SEAWAT package in Astaneh-... more In this study, after simulating five 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 artificial recharge and underground dam had the greatest impact on preventing the saltwater intrusion with the highest satisfaction of stakeholders, so that they decreased the saltwater intrusion from 740 m by 150 and 300 m, respectively, after five years. Therefore, the combined simulator-optimizer method presented in this study can evaluate various solutions, and the most appropriate solution can be proposed with the lowest cost and maximum satisfaction for the sustainable managem...
Forecasting the groundwater level is crucial to managing water resources supply sustainably. In t... more Forecasting the groundwater level is crucial to managing water resources supply sustainably. In this study, a simulation–optimization hybrid model was developed to forecast groundwater levels in aquifers. The model uses the PSO (Particle Swarm Optimization) algorithm to optimize SVR (Support Vector Regression) parameters to predict groundwater levels. The groundwater level of the Zanjan aquifer in Iran was forecasted and compared to the results of Bayesian and SVR models. In the first approach, the aquifers hydrograph was extracted using the Thiessen method, and then the time series of the hydrograph was used in training and testing the model. In the second approach, the time series data from each well was trained and tested separately. In other words, for 35 observation wells, 35 predictions were made. Aquifer’s hydrograph was evaluated using the forecasted groundwater level in the wells. The results showed that the SVR-PSO hybrid model performed better than other models in terms of Root Mean Square Error (RMSE) and coefficient of determination (R2\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${R}^{2}$$\end{document}) in both approaches. In the first approach, the SVR-PSO hybrid model forecasted the groundwater level in the next month with a training RMSE of 0.118 m and testing RMSE of 0.221 m. In the second approach, using the SVR-PSO hybrid model, the RMSE error was reduced in 88.57% of the wells compared to other models, and more reliable results were achieved. Based on the performance, the SVR-PSO hybrid model can be used as a tool for decision support and management of similar aquifers.
One of the major shortcomings with GALDIT model is the difficulty in specifying numerical constan... more 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.
Identification of the uncertain parameters, which affecting on the qualitative behavior of the aq... more 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.
Improving the groundwater governance structure can help reduce groundwater decline and improve th... more 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.
Landslide is a natural phenomenon which occurs on mountainous areas and causes a lot of damages e... more Landslide is a natural phenomenon which occurs on mountainous areas and causes a lot of damages every year. Decision makers, engineers, and urban planners can mitigate or prevent loss of lives as well as potential economic losses in the future through using the landslide susceptibility map. This study aims to identify the areas susceptible to landslide occurrence in Sefidrood basin located in Alborz Mountains in the north of Iran using bivariate models, i.e., frequency ratio (FR), weights of evidence (WoE), and Dempster-Shafer theory (DST), and compare them with ensemble method of multivariate logistic regression (LR) and genetic algorithm (GA). In the first step, 265 landslide locations were identified as the inventory map. From these identified landslides, 70% (186 landslide locations) was randomly selected as the training data and the remaining 30% (79 landslide locations) was used for validation purposes. In the next step, considering the region's condition and the experts' opinion, twelve discrete and continuous conditioning factors were prepared including slope angle, slope aspect, altitude, distance from streams, distance from roads, distance from faults, land use, rainfall, NDVI, lithology, profile curvature, plan curvature, and rainfall. After establishing the database, the proposed models were analyzed using conditional factors and inventory map. Finally, after preparing landslide susceptibility maps, the performance of each method was investigated and compared using ROC curve. The results from validation process showed that the area under the curve (AUC) for the models of FR, WoE, DST, and GA-LR was 0.741, 0.814, 0.826, and 0.938, respectively. According to the results, GA-LR model exhibited higher accuracy in prediction of landslide susceptibility in the study area compared with other models. Therefore, the map produced by this model can help engineers, land use planners, and crisis management personnel make more accurate decisions.
Abstract Limited hydrogeological data accessibility leads scholars to improve the robustness of p... more Abstract 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, Conducibilita, 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 Relying on the conceptual DPSIR framework and MODFLOW analysis, this study used a mixed ... more Abstract Relying on the conceptual DPSIR framework and MODFLOW analysis, this study used a mixed approach to produce groundwater resource management solutions for the Najafabad area in central Iran. According to DPSIR results, agricultural activities put the highest pressure on groundwater resources in this region. The results showed the effectiveness of reducing water withdrawal over 30 years in maintaining the aquifer in a state of equilibrium. The best scenario consisted of cutting down extraction by 10% over the said period. Output maps of the water table rise at the Najafabad aquifer clearly showed that the groundwater management scenario involving a 10% reduction of water withdrawal was the most effective solution, as it would raise the water level by 6.7 m. Regarding other scenarios, reducing cultivated area by 20% was found to raise the water table by 5.03 m on average, while cutting down water withdrawal by 5% increased the water table by 3.6 m, and a 10% reduction of the cultivated area resulted in a 1.85 m rise. The combined model proposed here can be used for similar aquifers and can aid decision-makers and managers.
Understanding interactions between surface water (SW) and groundwater (GW) is challenging because... more Understanding interactions between surface water (SW) and groundwater (GW) is challenging because of the lack of information available and the complexity of the processes involved. In this paper, SW-GW interactions are simulated using numerical modelling integrated with insights from water isotopes. Isotope analysis can be used to (i) determine the relative contribution from different sources of water into aquifer recharge and (ii) identify areas with high SW-GW interactions. The results, for the Shiraz catchment in Iran, show that (i) SWAT-MODFLOW has better performance than stand-alone SWAT (R2 improvement from 0.50 to 0.54) and (ii) SWAT-MODFLOW calibrated with insights from isotope data (SWAT-MODFLOW-ISO) has significantly better performance than SWAT-MODFLOW (R2 improvement from 0.54 to 0.68 and RMSE reduction from 1.67 to 1.33). This demonstrates that insights into SW-GW interactions that are revealed by isotopes can be used to improve hydrological modelling performance.
Most semi-distributed and distributed hydrological models can potentially be applied for comprehe... more Most semi-distributed and distributed hydrological models can potentially be applied for comprehensive catchment simulations, but these models may require modifications to capture dominant hydrological processes. The Soil and Water Assessment Tool (SWAT) ecohydrological model, an open source program, provides flexibility for modification to capture different components of hydrological processes in a given catchment. In this study, two new approaches were tested to simulate the hydrological processes of a karst system in the Zagros Mountains, Iran. The major modifications used in these two methods included adjusting the percolation rates in karst hydrologic response units (HRUs) using SWAT-Maharlu Lake (SWAT-ML), and modification of the crack flow module using SWAT-Crack Flow (SWAT-CF). Hydrological datasets from 1980 to 2013 were used for calibration and validation of surface runoff, baseflow, crop yields, and actual evapotranspiration. Both modified models outperformed the standard SWAT model in simulating runoff. The respective average Nash Sutcliffe Efficiencies of the original SWAT, SWAT-ML and SWAT-CF were 0.64, 0.68 and 0.66. Also, the results showed that higher deep aquifer infiltration values were estimated in the modified models versus the standard SWAT for a karst HRU, which reflects more accurate levels of recharge to the deep aquifer. However, the results showed that karst conditions and geometry of sinkholes in karst zones did not play a major role in creation of runoff.
Sustainable Energy Technologies and Assessments, 2021
Abstract The poor performance of surface water distribution systems in reliable, sufficient, and ... more Abstract The poor performance of surface water distribution systems in reliable, sufficient, and timely agricultural water distribution has significantly increased groundwater extraction. This has posed severe environmental challenges such as the significant decline in groundwater levels and increases in energy consumption. This study investigated the potential for automation of the surface water distribution systems to decrease groundwater extraction and energy conservation. The proposed approach was implemented in Nekoo-Abad Irrigation District, located in the arid region in Iran. The undesirable surface system’s performance results in the annual extraction of 82 Mm3 water from nearly 4181 active tubewells and the annual consumption of 236 MkWh to pump the groundwater for agricultural purposes merely. The automation improved the system performance so that annual groundwater extraction decreased by 16%. Reducing groundwater extraction decreased energy consumption by nearly 26%, 18%, and 14% in the normal and water scarcity scenarios. Moreover, the spatial analysis of research results indicated that groundwater extraction declined by 61–88% in shallow wells ( 120 m. It is expected that the entire system's automation will help achieve more of the research objectives, something which requires additional socioeconomic studies.
Environmental Science and Pollution Research, 2020
Hybrid and integrated techniques can be used to investigate intrinsic uncertainties of the overla... more 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.
Population growth and increasing demand for water have posed a significant challenge to access to... more Population growth and increasing demand for water have posed a significant challenge to access to safe water resources. Climate change and land use in the not-too-distant future add to the complexity of this challenge. Therefore, it is essential to achieve reliable methods for predicting changes in aquifer storage to plan for the sustainable use of groundwater resources. This study aimed to investigate the management, protection, and sustainable use of groundwater resources under climate change and land use change conditions. In this regard, groundwater supply and demand in one of the important plains in Iran (Hashtgerd plain) for 2020 as the base year was simulated to forecast the trends until 2050 by considering climate change and land use to develop management scenarios to adapt to these conditions using the WEAP model. First, climate change prediction was performed using the HadGEM2-ES model under two emission scenarios, RCP2.6, and RCP8.5, of the IPCC Fifth Assessment Report. The LARS-WG model was used to downscale the climatic data, while land use mapping was performed using Landsat satellite images of 1990, 2005, and 2020 in ENVI 5.3 software. Then, the Markov chain method implemented in TerrSet software was used to model land use change for 2050. The effect of climate change and land use on the decrease of groundwater level was then simulated using the MODFLOW model for the period 2020-2050. In order to manage the water allocation in the area, the information obtained from MODFLOW was transferred to the WEAP model using Link Kitchen interface software. The effects of various management scenarios such as increasing irrigation efficiency, reducing the loss of drinking water distribution networks, and allocating water from the transmission line were evaluated on the adaptation to climate change and land use for a 30-year period. The results showed that with the simultaneous consideration of climate change and land use in the most critical state, the average drop in groundwater level would reach 58 m during the study period, and aquifer reserves will be reduced by more than 50%. The evaluation of management scenarios showed that their implementation not only will protect aquifer reserves but, in addition to meeting 100% of the water needs, will result in sustainable exploitation of groundwater resources.
In this study, after simulating five years of saltwater intrusion with SEAWAT package in Astaneh-... more In this study, after simulating five 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 artificial recharge and underground dam had the greatest impact on preventing the saltwater intrusion with the highest satisfaction of stakeholders, so that they decreased the saltwater intrusion from 740 m by 150 and 300 m, respectively, after five years. Therefore, the combined simulator-optimizer method presented in this study can evaluate various solutions, and the most appropriate solution can be proposed with the lowest cost and maximum satisfaction for the sustainable managem...
Forecasting the groundwater level is crucial to managing water resources supply sustainably. In t... more Forecasting the groundwater level is crucial to managing water resources supply sustainably. In this study, a simulation–optimization hybrid model was developed to forecast groundwater levels in aquifers. The model uses the PSO (Particle Swarm Optimization) algorithm to optimize SVR (Support Vector Regression) parameters to predict groundwater levels. The groundwater level of the Zanjan aquifer in Iran was forecasted and compared to the results of Bayesian and SVR models. In the first approach, the aquifers hydrograph was extracted using the Thiessen method, and then the time series of the hydrograph was used in training and testing the model. In the second approach, the time series data from each well was trained and tested separately. In other words, for 35 observation wells, 35 predictions were made. Aquifer’s hydrograph was evaluated using the forecasted groundwater level in the wells. The results showed that the SVR-PSO hybrid model performed better than other models in terms of Root Mean Square Error (RMSE) and coefficient of determination (R2\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${R}^{2}$$\end{document}) in both approaches. In the first approach, the SVR-PSO hybrid model forecasted the groundwater level in the next month with a training RMSE of 0.118 m and testing RMSE of 0.221 m. In the second approach, using the SVR-PSO hybrid model, the RMSE error was reduced in 88.57% of the wells compared to other models, and more reliable results were achieved. Based on the performance, the SVR-PSO hybrid model can be used as a tool for decision support and management of similar aquifers.
One of the major shortcomings with GALDIT model is the difficulty in specifying numerical constan... more 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.
Identification of the uncertain parameters, which affecting on the qualitative behavior of the aq... more 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.
Improving the groundwater governance structure can help reduce groundwater decline and improve th... more 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.
Landslide is a natural phenomenon which occurs on mountainous areas and causes a lot of damages e... more Landslide is a natural phenomenon which occurs on mountainous areas and causes a lot of damages every year. Decision makers, engineers, and urban planners can mitigate or prevent loss of lives as well as potential economic losses in the future through using the landslide susceptibility map. This study aims to identify the areas susceptible to landslide occurrence in Sefidrood basin located in Alborz Mountains in the north of Iran using bivariate models, i.e., frequency ratio (FR), weights of evidence (WoE), and Dempster-Shafer theory (DST), and compare them with ensemble method of multivariate logistic regression (LR) and genetic algorithm (GA). In the first step, 265 landslide locations were identified as the inventory map. From these identified landslides, 70% (186 landslide locations) was randomly selected as the training data and the remaining 30% (79 landslide locations) was used for validation purposes. In the next step, considering the region's condition and the experts' opinion, twelve discrete and continuous conditioning factors were prepared including slope angle, slope aspect, altitude, distance from streams, distance from roads, distance from faults, land use, rainfall, NDVI, lithology, profile curvature, plan curvature, and rainfall. After establishing the database, the proposed models were analyzed using conditional factors and inventory map. Finally, after preparing landslide susceptibility maps, the performance of each method was investigated and compared using ROC curve. The results from validation process showed that the area under the curve (AUC) for the models of FR, WoE, DST, and GA-LR was 0.741, 0.814, 0.826, and 0.938, respectively. According to the results, GA-LR model exhibited higher accuracy in prediction of landslide susceptibility in the study area compared with other models. Therefore, the map produced by this model can help engineers, land use planners, and crisis management personnel make more accurate decisions.
Abstract Limited hydrogeological data accessibility leads scholars to improve the robustness of p... more Abstract 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, Conducibilita, 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 Relying on the conceptual DPSIR framework and MODFLOW analysis, this study used a mixed ... more Abstract Relying on the conceptual DPSIR framework and MODFLOW analysis, this study used a mixed approach to produce groundwater resource management solutions for the Najafabad area in central Iran. According to DPSIR results, agricultural activities put the highest pressure on groundwater resources in this region. The results showed the effectiveness of reducing water withdrawal over 30 years in maintaining the aquifer in a state of equilibrium. The best scenario consisted of cutting down extraction by 10% over the said period. Output maps of the water table rise at the Najafabad aquifer clearly showed that the groundwater management scenario involving a 10% reduction of water withdrawal was the most effective solution, as it would raise the water level by 6.7 m. Regarding other scenarios, reducing cultivated area by 20% was found to raise the water table by 5.03 m on average, while cutting down water withdrawal by 5% increased the water table by 3.6 m, and a 10% reduction of the cultivated area resulted in a 1.85 m rise. The combined model proposed here can be used for similar aquifers and can aid decision-makers and managers.
Understanding interactions between surface water (SW) and groundwater (GW) is challenging because... more Understanding interactions between surface water (SW) and groundwater (GW) is challenging because of the lack of information available and the complexity of the processes involved. In this paper, SW-GW interactions are simulated using numerical modelling integrated with insights from water isotopes. Isotope analysis can be used to (i) determine the relative contribution from different sources of water into aquifer recharge and (ii) identify areas with high SW-GW interactions. The results, for the Shiraz catchment in Iran, show that (i) SWAT-MODFLOW has better performance than stand-alone SWAT (R2 improvement from 0.50 to 0.54) and (ii) SWAT-MODFLOW calibrated with insights from isotope data (SWAT-MODFLOW-ISO) has significantly better performance than SWAT-MODFLOW (R2 improvement from 0.54 to 0.68 and RMSE reduction from 1.67 to 1.33). This demonstrates that insights into SW-GW interactions that are revealed by isotopes can be used to improve hydrological modelling performance.
Most semi-distributed and distributed hydrological models can potentially be applied for comprehe... more Most semi-distributed and distributed hydrological models can potentially be applied for comprehensive catchment simulations, but these models may require modifications to capture dominant hydrological processes. The Soil and Water Assessment Tool (SWAT) ecohydrological model, an open source program, provides flexibility for modification to capture different components of hydrological processes in a given catchment. In this study, two new approaches were tested to simulate the hydrological processes of a karst system in the Zagros Mountains, Iran. The major modifications used in these two methods included adjusting the percolation rates in karst hydrologic response units (HRUs) using SWAT-Maharlu Lake (SWAT-ML), and modification of the crack flow module using SWAT-Crack Flow (SWAT-CF). Hydrological datasets from 1980 to 2013 were used for calibration and validation of surface runoff, baseflow, crop yields, and actual evapotranspiration. Both modified models outperformed the standard SWAT model in simulating runoff. The respective average Nash Sutcliffe Efficiencies of the original SWAT, SWAT-ML and SWAT-CF were 0.64, 0.68 and 0.66. Also, the results showed that higher deep aquifer infiltration values were estimated in the modified models versus the standard SWAT for a karst HRU, which reflects more accurate levels of recharge to the deep aquifer. However, the results showed that karst conditions and geometry of sinkholes in karst zones did not play a major role in creation of runoff.
Sustainable Energy Technologies and Assessments, 2021
Abstract The poor performance of surface water distribution systems in reliable, sufficient, and ... more Abstract The poor performance of surface water distribution systems in reliable, sufficient, and timely agricultural water distribution has significantly increased groundwater extraction. This has posed severe environmental challenges such as the significant decline in groundwater levels and increases in energy consumption. This study investigated the potential for automation of the surface water distribution systems to decrease groundwater extraction and energy conservation. The proposed approach was implemented in Nekoo-Abad Irrigation District, located in the arid region in Iran. The undesirable surface system’s performance results in the annual extraction of 82 Mm3 water from nearly 4181 active tubewells and the annual consumption of 236 MkWh to pump the groundwater for agricultural purposes merely. The automation improved the system performance so that annual groundwater extraction decreased by 16%. Reducing groundwater extraction decreased energy consumption by nearly 26%, 18%, and 14% in the normal and water scarcity scenarios. Moreover, the spatial analysis of research results indicated that groundwater extraction declined by 61–88% in shallow wells ( 120 m. It is expected that the entire system's automation will help achieve more of the research objectives, something which requires additional socioeconomic studies.
Environmental Science and Pollution Research, 2020
Hybrid and integrated techniques can be used to investigate intrinsic uncertainties of the overla... more 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.
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Papers by Saman Javadi