A Framework for Ground Water Management Based on Bayesian Network and MCDM Techniques

Groundwater resources are steadily subjected to increasing water demands. The aquifers are considered as the most accessible source of fresh water. In recent years, they have been faced with severe water withdrawal in arid and semi-arid countries like Iran and thus some aquifers was considered as forbidden aquifers that it means the water withdrawal from these aquifers is unauthorized. Given a critical situation, groundwater resources management in the form of tools such as monitoring the level of the aquifers and developing the restoring scenarios is essential. Therefore, for this purpose, a framework has been developed based on prediction of groundwater level using Bayesian Networks (BNs) model. Furthermore, Multi Criteria Decision Making methods (MCDM) techniques proposed and employed for ranking of proposed groundwater management scenarios. This framework was evaluated for restoring the Birjand aquifer in Iran in different hydrological conditions. A probabilistic Dynamic BN was proposed for groundwater level prediction under uncertainties. After analyzing the obtained results, the applicable short term scenarios for groundwater management as well as appropriate economic, social and technical criteria were defined for decision making procedure. Then, using elicitation of decision makers’ opinions on the relative importance and performance of criteria, SAW, TOPSIS and PROMETHEE-II techniques were applied to rank the scenarios and the obtained results were aggregated by Borda method for final ranking of the scenarios. Lastly, the final results demonstrates the capability of the proposed framework for groundwater resources planning and management which can be employed for reducing the risk of aquifer level declining.     

GIS-Based Groundwater Management Model for Western Nile Delta

The limited availability of renewable fresh water is a major constraint on future agriculture and urban development in Egypt. The main water resource that Egypt has been depending on is the River Nile. Nowadays, the role of groundwater is steadily increasing and will cover 20% of the total water supply in the coming decades especially in the reclaimed areas along the desert fringes of the Nile Delta and Valley. Abstraction from groundwater in Egypt is dynamic in nature as it grows rapidly with the expansion of irrigation activities, industrialization, and urbanization. One of these areas is the Western Nile Delta in which the groundwater is exploited in many localities. To avoid the deterioration of the aquifer system in this area, an efficient integrated and sustainable management plan for groundwater resources is needed. Efficient integrated and sustainable management of water resources relies on a comprehensive database that represents the characteristics of the aquifer system and modeling tools to achieve the impacts of decision alternatives. In this paper, a GIS-based model has been developed for the aquifer system of the Western Nile Delta. The GIS provides the utilization of analytical tools and visualization capabilities for pre-and post-processing information involved in groundwater modeling for the study area. The developed model was calibrated for steady state and transient conditions against the historical groundwater heads observed during the last 20 yr. The calibrated model was used to evaluate groundwater potentiality and to test two alternative management scenarios for conserving the aquifer system in Western Nile Delta. In the first scenario, reducing the surface water inflow while increasing the annual abstraction from groundwater by about 450 million m³ and improving the irrigation system could increase the net aquifer recharge by about 5.7% and reduce the aquifer potentiality by about 91%. Constructing a new canal as a second management scenario could increase the annual aquifer potentiality by about 23%. The GIS-based model has been proven to be an efficient tool for formulating integrated and sustainable management plan.     

Conjunctive Management of Large-Scale Pressurized Water Distribution and Groundwater Systems in Semi-Arid Area with Parallel Genetic Algorithm

This study develops a production well management model for the conjunctive management of water resources in semi-arid areas. The management model integrates a large-scale pressurized water distribution system and a three-dimensional groundwater model under an optimization framework. The well pump operations optimization problem is formulated as a Boolean integer nonlinear programming (BINLP) problem to optimize the periodic 24-h pump on/off operations over a 1-week operation horizon. The management model considers multiple objectives and is solved by a parallel genetic algorithm (PGA) to overcome the difficulty of solving the BINLP problem. The PGA significantly reduces computation time for a case study in Chandler, Arizona. The Chandler water distribution model is built based on EPANET, and the Chandler three-dimension groundwater model is developed using MODFLOW. The high performance computing (HPC) of the genetic algorithm makes it possible to obtain 24-h real-time operations in the 7-day forecast model. The tank reliability, resilience, and vulnerability (R-R-V) are evaluated to infer the system reliability. The Pareto curve provides compromise solutions between the two competing objectives of energy reduction and pressure violation reduction.     

Groundwater Flow Modeling of the Arlington Basin to Evaluate Management Strategies for Expansion of the Arlington Desalter Water Production

Water supply reliability in Southern California is facing serious problems because of reduction in the availability of water from the State Water Project and Colorado River, drought, and growing concerns about environmental restoration. Groundwater sources supply more than fifty-five percent of domestic demands in the Western Riverside County. Western Municipal Water District is planning to increase water supply reliability by expanding the Arlington Desalter production which requires additional groundwater pumping from the Arlington Basin. Western was concerned that increasing groundwater pumping will cause excessive decline in groundwater levels, leading to decreased yields at existing Desalter wells. Three-dimensional groundwater flow model was developed for the Arlington Basin to investigate different water management strategies. Five groundwater management scenarios were run for a 30-year time period. The five model runs were used to determine the feasibility of the Arlington aquifer system to supply groundwater to the Arlington Desalter over the 30-year life of the facility. Model simulation results showed that long-term groundwater pumping from the existing Desalter wells is not sustainable without artificial recharge. However two of the modeling scenarios which incorporated a combination of artificial recharge and new production wells, were shown to meet the increased Desalter yield requirements as well as minimize adverse impacts.     

A Decision Support System to Manage the Groundwater of the Zeuss Koutine Aquifer Using the WEAP-MODFLOW Framework

This paper describes the development of a Decision Support System (DSS) for groundwater management of the ‘Zeuss Koutine’ aquifer in southeastern Tunisia using the WEAP-MODFLOW framework. First, a monthly MODFLOW model was developed to simulate the behaviour of the studied aquifer. A conceptual model of the study area was designed and a WEAP schematic representing the real hydraulic system was developed. In addition to the studied aquifer, other water resources available in the region, such as desalination plants and groundwater, were taken into consideration in this DSS. Inputs to the hydrogeological model include natural recharge and inflow from higher neighbouring aquifers. Outputs are mainly agricultural, touristic and urban water consumption. It was shown that the DSS developed was able to evaluate water management scenarios up to 2030, especially future water consumption, transmission link flow and active cell heads of the MODFLOW model for each time step. Results for the Zeuss Koutine aquifer demonstrated that desalination plants already built in the cities of Jerba and Zarzis have contributed to decreasing the continuous drawdown observed before 1999. The use of a sea water desalination plant to supply Jerba and Zarzis in the future is a solution for reducing the Zeuss Koutine aquifer drawdown. Defining its optimal capacity over time poses a new research question.     

Simulation Modeling for Efficient Groundwater Management in Balasore Coastal Basin,India

The Balasore coastal groundwater basin in Orissa, India is under a serious threat of overdraft and seawater intrusion. The overexploitation resulted in abandoning many shallow tubewells in the basin. The main intent of this study is the development of a 2-D groundwater flow and transport model of the basin using the Visual MODFLOW package for analyzing the aquifer response to various pumping strategies. The simulation model was calibrated and validated satisfactorily. Using the validated model, the groundwater response to five pumping scenarios under existing cropping conditions was simulated. The results of the sensitivity analysis indicated that the Balasore aquifer system is more susceptible to the river seepage, recharge from rainfall and interflow than the horizontal and vertical hydraulic conductivities and specific storage. Finally, based on the modeling results, salient management strategies are suggested for the long-term sustainability of vital groundwater resources of the Balasore groundwater basin. The most promising management strategy for the Balasore basin could be: a reduction in the pumpage from the second aquifer by 50% in the downstream region and an increase in the pumpage to 150% from the first and second aquifer at potential locations.     

A New Groundwater Management Model by Coupling Analytic Element Method and Reverse Particle Tracking with Cat Swarm Optimization

The performance of groundwater management models mostly depends upon the methodology employed to simulate flow and transport processes and the efficiency of optimization algorithms. The present study examines the effectiveness of cat swarm optimization (CSO) for groundwater management problems, by coupling it with the analytic element method (AEM) and reverse particle tracking (RPT). In this study, we propose two coupled simulation-optimization models, viz. AEM-CSO and AEM-RPT-CSO by combining AEM with RPT and CSO. Both the models utilize the added advantages of AEM, such as precise estimation of hydraulic head at pumping location and generation of continuous velocity throughout the domain. The AEM-CSO model is applied to a hypothetical unconfined aquifer considering two different objectives, i.e., maximization of the total pumping of groundwater from the aquifer and minimization of the total pumping costs. The model performance reflects the superiority of CSO in comparison with other optimization algorithms. Further, the AEM-RPT-CSO model is successfully applied to a hypothetical confined aquifer to minimize the total number of contaminant sources, within the time related capture zone of the wells, while maintaining the required water demand. In this model, RPT gets continuous velocity information directly from the AEM model. The performance evaluation of the proposed methodology, illustrates its ability to solve groundwater management problems.     

A sensitivity analysis and parametric study for the evaluation of the optimal management of a contaminated aquifer

A typical groundwater remedation problem is studied by using a combined simulation-optimization model. The management procedure employs groundwater flow and contaminant transport simulation models in conjunction with linear and quadratic programming techniques. The methodology is applied to the hydrodynamic control of a contaminant plume that has to be stabilized and removed by a system of pumping wells. The paper focuses mainly upon a sensitivity analysis to the aquifer transmissivity. The effect of changes in the transmissivities of a zoned aquifer upon the optimal solutions of the management problem is examined by considering the optimal pumping rates, the time to remediation and the pumped groundwater volume as the key output variables of the remediation strategies. In addition, the influence of the dispersivities and the imposed hydraulic gradient upon the same output variables is critically evaluated. The results of the study illustrate the need for uncertainty reduction in the knowledge of the hydrogeologic parameters.     

Sustainable Groundwater Management in the Arid Southwestern US: Coachella Valley,California

Sustainable groundwater management requires approaches to assess the influence of climate and management actions on the evolution of groundwater systems. Traditional approaches that apply continuity to assess groundwater sustainability fail to capture the spatial variability of aquifer responses. To address this gap, our study evaluates groundwater elevation data from the Coachella Valley, California, within a groundwater sustainability framework given the adoption of integrative management strategies in the valley. Our study details an innovative approach employing traditional statistical methods to improve understanding of aquifer responses. In this analysis, we evaluate trends at individual groundwater observation wells and regional groundwater behaviors using field significance. Regional elevation trends identified no significant trends during periods of intense groundwater replenishment, active since 1973, despite spatial variability in individual well trends. Our results illustrate the spatially limited effects of groundwater replenishment occur against a setting of long-term groundwater depletion, raising concerns over the definition of sustainable groundwater management in aquifer systems employing integrative management strategies.

     

Stochastic and Robust Multi-Objective Optimal Management of Pumping from Coastal Aquifers Under Parameter Uncertainty

Combined simulation-optimization approaches have been used as tools to derive optimal groundwater management strategies to maintain or improve water quality in contaminated or other aquifers. Surrogate models based on neural networks, regression models, support vector machies etc., are used as substitutes for the numerical simulation model in order to reduce the computational burden on the simulation-optimization approach. However, the groundwater flow and transport system itself being characterized by uncertain parameters, using a deterministic surrogate model to substitute it is a gross and unrealistic approximation of the system. Till date, few studies have considered stochastic surrogate modeling to develop groundwater management methodologies. In this study, we utilize genetic programming (GP) based ensemble surrogate models to characterize coastal aquifer water quality responses to pumping, under parameter uncertainty. These surrogates are then coupled with multiple realization optimization for the stochastic and robust optimization of groundwater management in coastal aquifers. The key novelty in the proposed approach is the capability to capture the uncertainty in the physical system, to a certain extent, in the ensemble of surrogate models and using it to constrain the optimization search to derive robust optimal solutions. Uncertainties in hydraulic conductivity and the annual aquifer recharge are incorporated in this study. The results obtained indicate that the methodology is capable of developing reliable and robust strategies for groundwater management.     

Predictive Simulation of Flow and Solute Transport for Managing the Salalah Coastal Aquifer, Oman

A three-dimensional numerical model for flow and solute transport was used for the management of the Salalah aquifer. The model calibration procedures consisted of calibrating the aquifer system hydraulic parameters by history matching under steady and transient conditions. The history of input and output of the aquifer were reconstructed in a transient calibration from 1993 to 2005. Predictive simulation of the aquifer was carried out under transient conditions to predict the future demand of groundwater supply for the next 15 years. A baseline scenario was worked out to obtain the piezometric surface and salinity distribution for the “business as usual” conditions of the aquifer. The “business as usual” scenario was predicted and simulated for the period 2006 until 2020. The effectiveness of seven management options was proposed and assessed for comparison with the “business as usual” conditions. The established simulation model was used to predict the distribution of the piezometric surface, salinity distribution, and mass balance under the proposed scenarios for the prediction period 2006–2020. The scenarios were: (1) relocate Garziz and MAF farms far from the freshwater zone, (2) suspend the abstraction of grass production for 4 months a year, (3) changes in agricultural and irrigation system patterns, (4) establish a desalination plant, (5) combined scenario (1 + 4), (6) combined scenario (1 + 3), and (7) combining all scenarios (1 + 2 + 3 + 4). The result of the simulation shows that the best effective option in terms of aquifer groundwater levels is the fifth proposed scenario and the sixth proposed scenario is the best effective option in terms of aquifer groundwater salinity situation during the next 15 years. This project suggested the application of scenario 6 as it is environmentally sound in terms of sustainable management. A prediction has been made which shows that further actions have to be taken within the next two decades to ensure continuity of the municipal water supply. The management scenarios are examined in the case of the Salalah coastal aquifer using groundwater simulation, which can also be applied to other regions with similar conditions. The established model is considered a reasonable representation of the physical conditions of the Salalah plain aquifer, and can be used as a tool by the water and environmental authorities in the management of the groundwater in the region.     

不同降水情景下天津市地下水位的时空变化特征

为了定量模拟和评价不同降雨情景下天津市不同含水层地下水位时空变化情况,通过对天津市水文地质条件的分析和已获取的资料建立地下水系统的三维数值模拟模型,并利用已知的地下水位动态数据对模型进行拟合与检验,确定模型的可靠性。然后利用模型对常态条件下(地下水开采量维持不变,50%频率下的降水量)和极端气候条件下(地下水开采量维持不变,95%频率下的降水量)天津市地下水位的时空变化特征进行预测和评价,分析不同含水层地下水位对两种情景的动态响应机制。结果表明:两种方案下10 a后的地下水流场特征较为相近,地下水流向也基本一致,地下水位均有所下降,在开采量不变情况下,降水量的减少对承压含水层的影响较为有限。     

Numerical simulation of groundwater flow and land deformation due to groundwater pumping in cross-anisotropic layered aquifer system

In a natural aquifer, the aquifer properties are complicated, which normally vary with aquifer depth and geographic characteristics. Most previous studies have been limited to the case of isotropic aquifer with uniform characteristics. In the proposed model, the fully coupled ground water flow and land deformation due to groundwater pumping in cross-anisotropic aquifer system is used to analyze and predict. Based on this model, pumping-recovery tests in various conditions are numerically simulated to reveal the effects of cross-anisotropic aquifer behavior on hydraulic head and land deformation. Finally, the proposed method is applied to a project in Shanghai of China due to pumping of groundwater predicted. Comparing the calculated results with the measured field values indicates that the methods can be a useful tool for designing groundwater pumping projects.     

Comparative Evaluation of Genetic Programming and Neural Network as Potential Surrogate Models for Coastal Aquifer Management

Determining the optimal rates of groundwater extraction for the sustainable use of coastal aquifers is a complex water resources management problem. It necessitates the application of a 3D simulation model for coupled flow and transport simulation together with an optimization algorithm in a linked simulation-optimization framework. The use of numerical models for aquifer simulation within optimization models is constrained by the huge computational burden involved. Approximation surrogates are widely used to replace the numerical simulation model, the widely used surrogate model being Artificial Neural Networks (ANN). This study evaluates genetic programming (GP) as a potential surrogate modeling tool and compares the advantages and disadvantages with the neural network based surrogate modeling approach. Two linked simulation optimization models based on ANN and GP surrogate models are developed to determine the optimal groundwater extraction rates for an illustrative coastal aquifer. The surrogate models are linked to a genetic algorithm for optimization. The optimal solutions obtained using the two approaches are compared and the advantages of GP over the ANN surrogates evaluated.     

An Integrating Approach for Conjunctive-Use Planning of Surface and Subsurface Water System

This study proposes an integrated approach to assess the performance of a conjunctive-use surface and subsurface water system. System dynamics serves as the main framework of the proposed conjunctive-use model, simulating the interaction between surface and subsurface water and the impact of various conjunctive-use alternatives on the system as a whole. This study assumes natural groundwater recharge as a water source to the system, and estimates its volume using geographic information system (GIS) tools, a groundwater simulation model (MODFLOW), and a parameter identification model (UCODE). This study assesses various conjunctive-use alternatives and analyzes the frequency of water shortage to illustrate how the recharge rate affects water supply reliability under the conjunctive-use framework. Simulation results indicate that conjunctive-use with artificial recharge indeed reduces the frequency of extreme water shortages. Results also reveal that artificial recharge is necessary to maintain groundwater conservation without overusing river flow. Although this study focuses on southern Taiwan, the proposed concepts and procedure are applicable to other areas with a similar conjunctive-use framework.     

Planning of Groundwater Supply Systems Subject to Uncertainty Using Stochastic Flow Reduced Models and Multi-Objective Evolutionary Optimization

The typical modeling approach to groundwater management relies on the combination of optimization algorithms and subsurface simulation models. In the case of groundwater supply systems, the management problem may be structured into an optimization problem to identify the pumping scheme that minimizes the total cost of the system while complying with a series of technical, economical, and hydrological constraints. Since lack of data on the subsurface system most often reflects upon the development of groundwater flow models that are inherently uncertain, the solution to the groundwater management problem should explicitly consider the tradeoff between cost optimality and the risk of not meeting the management constraints. This work addresses parameter uncertainty following a stochastic simulation (or Monte Carlo) approach, in which a sufficiently large ensemble of parameter scenarios is used to determine representative values selected from the statistical distribution of the management objectives, that is, minimizing cost while minimizing risk. In particular, the cost of the system is estimated as the expected value of the cost distribution sampled through stochastic simulation, while the risk of not meeting the management constraints is quantified as the expected value of the intensity of constraint violation. The solution to the multi-objective optimization problem is addressed by combining a multi-objective evolutionary algorithm with a stochastic model simulating groundwater flow in confined aquifers. Evolutionary algorithms are particularly appropriate in optimization problems characterized by non-linear and discontinuous objective functions and constraints, although they are also computationally demanding and require intensive analyses to tune input parameters that guarantee optimality to the solutions. In order to drastically reduce the otherwise overwhelming computational cost, a novel stochastic flow reduced model is thus developed, which practically allows for averting the direct inclusion of the full simulation model in the optimization loop. The computational efficiency of the proposed framework is such that it can be applied to problems characterized by large numbers of decision variables.     

Management of Groundwater Resources in Eastern Saudi Arabia

Effective management of groundwater in arid countries, such as Saudi Arabia, is an important factor in sustainable development. A regional numerical simulation model of a multi-aquifer system including the Dammam and Umm Er Radhuma (UER) aquifers was developed to assess the behaviour of the aquifer system under long-term water stresses. The model was utilized to predict the responses of the aquifer system under three alternative pumping schemes over a planning horizon of 31 years (1995-2025). Model results postulate that dewatering of the Dammam aquifer will occur at low productivity sites and along the outcrop with the current trend towards increasing abstraction. The UER will exhibit significant cones of depression at large irrigation projects. Aquifer dewatering and drawdowns will be minimal with the conservation alternative. This management scheme should be adopted for the future development and protection of groundwater in the province.     

李官堡水源地地下水流场数值模拟及预测

随着工业规模的发展,各城市都面临着地下水资源如何科学利用的难题,北方缺水城市沈阳李官堡水源地就面临着新增工业造成的用水压力,如何对该水源地的水资源进行科学评价是合理取用水的前提。在对模拟区范围、边界条件和孔隙水介质进行概化和对水文地质参数及其他参数确定的基础上,将该区域地下水流系统概化为均质、各向同性、二维、潜水非稳定地下水流系统,运用GMS模型软件对研究区的地下水流场进行了数值模拟预测。通过模型识别和可靠性分析认为,所率定的模型参数符合实际且模型边界条件合理;预测认为该区域地下水资源量不能满足新增企业用水量9.8万m3/d的需求。该评价方法不仅具有应用和推广价值,而且具有为地下水资源科学规划提供科学依据的重要作用。     

A Probabilistic Multiperiod Simulation–Optimization Approach for Dynamic Coastal Aquifer Management

Combined simulation–optimization (CSO) schemes are common in the literature to solve different groundwater management problems, and CSO is particularly well-established in the coastal aquifer management literature. However, with a few exceptions, nearly all previous studies have employed the CSO approach to derive static groundwater management plans that remain unchanged during the entire management period, consequently overlooking the possible positive impacts of dynamic strategies. Dynamic strategies involve division of the planning time interval into several subintervals or periods, and adoption of revised decisions during each period based on the most recent knowledge of the groundwater system and its associated uncertainties. Problem structuring and computational challenges seem to be the main factors preventing the widespread implementation of dynamic strategies in groundwater applications. The objective of this study is to address these challenges by introducing a novel probabilistic Multiperiod CSO approach for dynamic groundwater management. This includes reformulation of the groundwater management problem so that it can be adapted to the multiperiod CSO approach, and subsequent employment of polynomial chaos expansion-based stochastic dynamic programming to obtain optimal dynamic strategies. The proposed approach is employed to provide sustainable solutions for a coastal aquifer storage and recovery facility in Oman, considering the effect of natural recharge uncertainty. It is revealed that the proposed dynamic approach results in an improved performance by taking advantage of system variations, allowing for increased groundwater abstraction, injection and hence monetary benefit compared to the commonly used static optimization approach.

     

Brackish groundwater resources in Bahrain: Current exploitation,numerical evaluation and prospect for utilization

In Bahrain, where water resources available for direct use are finite and the best of its quality has a salinity of over 2.5 g L^–1, utilization of brackish groundwater is an essential part in the management of the country's water resources. Bahrain's brackish water occurs in the Rus-Umm Er Radhuma formations in the form of a lens of a finite lateral extent, with a salinity ranges between 8 and 15 g L^–1. Planning for utilization of brackish groundwater for desalination purposes in Bahrain was based on simulation modeling of the aquifer system using a mixing cell model developed originally in 1983. The model was used to predict the aquifer response to pumping from the proposed wellfield in terms of changes of TDS over a period of 20 years. Construction and operation of the wellfield in 1984 was based on the predicted salinity changes. Over the past 9 uears of wellfield operation (1984–1993), and through continuous monitoring of the aquifer response to pumping, the collected data is used to post-audit the original model by history matching. The calibration process adopted has resulted in a statisfactory agreement between the model output and the observed data. The model is then used to predict the wellfield salinity changes and the aquifer potentiometric levels. The expected life span for the brackish groundwater utilization by the wellfield is redefined through constrained utilization that takes into account salinity deterioration coupled with the effect of head decline on hydraulic interaction between the brackish water and the upper fresh water aquifer. The results suggest that the operation of the wellfield should cease by the year 2007. Construction of a new model that enables testing and evaluating different development scenarios is recommended to aid future management decisions regarding the utilization of brackish groundwater.