Convergence of a positive nonlinear control volume finite element scheme for an anisotropic seawater intrusion model with sharp interfaces

International audienceWe consider a degenerate parabolic system modelling the flow of fresh and saltwater in an anisotropic porous medium in the context of seawater intrusion. We propose and analyze a nonlinear Control Volume Finite Element scheme. This scheme ensures the nonnegativity of the discrete solution without any restriction on the mesh and on the anisotropy tensor. Moreover It also provides a control on the entropy. Based on these nonlinear stability results, we show that the scheme converges towards a weak solution to the problem. Numerical results are provided to illustrate the behavior of the model and of the scheme

A gravity current model with capillary trapping for oil migration in multilayer geological basins

International audienceWe propose a reduced model accounting capillary trapping to simulate oil migration in geological basins made of several rock types. Our model is derived from Darcy type models thanks to Dupuit approximation and a vertical integration in each geological layer. We propose a time-implicit finite volume scheme which is shown to be unconditionally stable and to admit discrete solutions. Numerical outcomes are then provided in order to illustrate the behavior of our reduced model

Analyse numérique d'une approximation élément fini pour un modèle d'intrusion saline dans les aquifères côtiers

In this work, we study a finite element scheme we apply to a model describing saltwater intrusion into coastal aquifers confined and free. The model is based on the hydraulic approach of vertically averaging the 3D original problem, this approximation is based on a quasi-hydrostatic flow hypothesis which, instead of the walls and springs, is checked. To model the interface between freshwater and salt water (respectively between the saturated zone and dry zone), we combine the approach net interface (approach with the diffuse interface) ; This approach is derived from the phase field theory introduced by Allen-Cahn, to describe the phenomena of transition between two zones. Given these approximations, the problem consists of a strongly couple to edps parabolic quasi-linear system in the case of unconfined aquifers describing the evolution of the depths of two free surfaces and elliptical-parabolic type in the case confined aquifer, the unknowns being then the depth of salt water / fresh water and the hydraulic load of fresh water. In the first part of the thesis, we give in the case of a confined aquifer, error estimation results of a semi-implicit scheme in a combined time discretization space finite element type Pk Lagrange. This result among other uses a regularity result of the gradient of the exact solution in the space Lr(ΩT), r > 2, which can handle the non-linearity and to establish the error estimate under assumptions reasonable regularity of the exact solution. In the second part of the thesis, we generalize the previous study to the case of the free aquifer. The main difficulty is related to the complexity of the system of parabolic edps but again, thanks to regularity result Lr(ΩT), r > 2 gradients established for the free surfaces, we show that the scheme is of order 1 time and space k for sufficiently regular solutions. We conclude this work by numerical simulations in different contexts (impact of porosity and hydraulic conductivity of the evolution of the interface, and pumping fresh water injection, tidal effects) thus validating the model and diagram. The we compare the results with those obtained using a finite volume scheme constructed from a structured mesh.Dans ce travail, nous étudions un schéma élément fini que nous appliquons à un modèle décrivant l'intrusion saline dans les aquifères côtiers confinés et libres. Le modèle est basé sur l'approche hydraulique qui consiste à moyenner verticalement le problème initial 3D, cette approximation repose sur une hypothèse d'écoulement quasi-hydrostatique qui, loin des épontes et des sources, est vérifiée. Pour modéliser les interfaces entre l'eau douce et l'eau salée (respectivement entre la zone saturée et la zone sèche), nous combinons l'approche 'interface nette' à l'approche avec 'interface diffuse' ; cette approche est déduite de la théorie de champ de phase, introduite par Allen-Cahn, pour décrire les phénomènes de transition entre deux zones. Compte tenu de ces approximations, le problème consiste en un système fortement couplé d'edps quasi-linéaires de type parabolique dans le cas des aquifères libres décrivant l'évolution des profondeurs des 2 surfaces libres et de type elliptique-prabolique dans le cas des aquifères confinés, les inconnues étant alors la profondeur de l'interface eau salée/eau douce et la charge hydraulique de l'eau douce. Dans la première partie de la thèse, nous donnons dans le cas d'un aquifère confiné, des résultats d'estimation d'erreur d'un schéma semi-implicite en temps combiné à une discrétisation en espace de type élément fini Pk Lagrange. Ce résultat utilise entre autre un résultat de régularité du gradient de la solution exacte dans l'espace Lr(ΩT), r > 2, ce qui permet de traiter la non-linéarité et d'établir l'estimation d'erreur sous des hypothèses de régularité raisonnables de la solution exacte. Dans la seconde partie de la thèse, nous généralisons l'étude précédente au cas de l'aquifère libre. La difficulté principale est liée à la complexité du système d'edps paraboliques mais à nouveau, grâce au résultat de régularité Lr(ΩT), r > 2 établi pour les gradients des surfaces libres, nous montrons que le schéma est d'ordre 1 en temps et k en espace pour des solutions suffisamment régulières. Nous concluons ce travail par des simulations numériques dans différents contextes (impact de la porosité et de la conductivité hydraulique sur l'évolution de l'interface, pompage et injection d'eau douce, effet des marées) validant ainsi le modèle et le schéma. Puis nous comparons les résultats à ceux obtenus avec un schéma volume fini construit à partir d'un maillage structuré

Monitoring seawater intrusion into the fractured UK Chalk aquifer using measurements of self-potential (SP)

Using laboratory, numerical and field experiments this study investigated whether borehole measurements of self-potential (SP) can be used to monitor seawater intrusion into the fractured UK Chalk aquifer. The SP, a natural voltage, arises in water saturated fractured porous media due to gradients in pressure (electrokinetic (EK) potential) and concentration (exclusion-diffusion (EED) potential), both features of seawater intrusion. An electrode array was installed in a monitoring borehole c.1.7 km from the coast, in Saltdean, East Sussex, and c.1.3 km from an active abstraction borehole. Head fluctuations in the monitoring borehole were controlled by tidal processes and seasonal changes in inland head. SP monitoring over 1.5 years revealed tidal SP signals. The fluctuations (c.600 μV) were two orders of magnitude larger than those observed at an inland site in the same aquifer, near Reading in Berkshire. Numerical simulation, supported by laboratory measurements, of the coupled hydrodynamic and electrical processes in the coastal aquifer suggested that the EK potential generated by tidal processes was one order of magnitude too small to be responsible for the tidal SP fluctuations. Instead, SP was caused by the EED potential that arose due to the concentration gradient between groundwater and seawater across the saline front (i.e. the 1000 mg/l isoline) some distance from the borehole. The saline front moved through a fracture at the base of the borehole in response to tides. A vertical SP gradient (c.0.22 mV/m), only present in the coastal borehole, was also observed. Modelling suggested that the gradient was due to the close proximity of the saline front (c.4 m) below the borehole and was caused by the EED potential. In August 2013 and 2014, tides and a decline in inland head caused saline water to enter the borehole. Fluid electrical conductivity logging showed that entry was via the fracture. Prior to each occurrence of saline breakthrough, an increase in the SP of c.300 μV was observed, commencing c.7 days before saline water was detected in the borehole. Although this study focused on a monitoring borehole, SP arrays could be installed in abstraction boreholes. The results suggest that SP monitoring may be used to provide early warning of saline water breakthrough, allowing for improved management of groundwater resources in coastal aquifers.Open Acces

Numerical Simulation and Effective Management of Saltwater Intrusion in Coastal Aquifers

Seawater intrusion (SWI) is a widespread environmental problem, particularly in arid and semi-arid coastal areas. Unplanned prolonged over-pumping of groundwater is the most important factor in SWI that could result in severe deterioration of groundwater quality. Therefore, appropriate management strategies should be implemented in coastal aquifers to control SWI with acceptable limits of economic and environmental costs. This PhD project presents the development and application of a simulation-optimization (S/O) model to assess different management methods of controlling saltwater intrusion while satisfying water demands, and with acceptable limits of economic and environmental costs, in confined and unconfined coastal aquifers. The first S/O model (FE-GA) is developed by direct linking of an FE simulation model with a multi-objective Genetic Algorithm (GA) to optimize the efficiency of a wide range of SWI management scenarios. However, in this S/O framework, several multiple calls of the simulation model by the population-based optimization model, evaluating best individual candidate solutions resulted in a considerable computational burden. To solve this problem the numerical simulation model is replaced by an Evolutionary Polynomial Regression (EPR)-based surrogate model in the next S/O model (EPR-GA). Through these S/O approaches (FE-GA and EPR-GA) the optimal coordinates and rates of the both abstraction and recharge barriers are determined in the studied management scenarios. As a result, a new combined methodology, so far called ADRTWW, is proposed to control SWI. The ADRTWW model consists of deep Abstraction of saline water near the coast followed by Desalination of the abstracted water to a potable level for public uses and simultaneously Recharging the aquifer using a more economic source of water such as treated wastewater (TWW). In accordance to the available recharge options (injection through well or infiltration from surface pond), the general performance of ADRTWW is evaluated in different hydro-geological settings of the aquifers indicating that it offers the least cost and least salinity in comparison with other scenarios. The great capabilities of both developed S/O models in identification of the best management solutions and the optimal coordinates and rates of the abstraction well and recharge well/pond are discussed. Both FE-GA and EPR-GA can be successfully employed by a robust decision support system. In the next phase of the study, the general impacts of sea level rise (SLR), associated with its transgression nature along the coastline surface on the saltwater intrusion mechanism are investigated in different hypothetical and real case studies of coastal aquifer systems. The results show that the rate and the amount of SWI are considerably greater in aquifers with flat shoreline slopes compared with those with steep slopes. The SWI process is followed by a significant depletion in quantity of freshwater resources at the end of the century. The situation is exacerbated with combined action of SLR and groundwater withdrawals. This finding is also confirmed by 3D simulation of SWI in a regional coastal aquifer (Wadi Ham aquifer) in the UAE subjected to the coupled actions of SLR and pumping.Ministry of Higher Education and Scientific Research in Kurdistan Regional Government of Iraq (KRG-HCDP Scholarship program)British Council under Water Security scheme (Project Code: SH- 04509

Development of sustainable groundwater management methodologies to control saltwater intrusion into coastal aquifers with application to a tropical Pacific island country

Saltwater intrusion due to the over-exploitation of groundwater in coastal aquifers is a critical challenge facing groundwater-dependent coastal communities throughout the world. Sustainable management of coastal aquifers for maintaining abstracted groundwater quality within permissible salinity limits is regarded as an important groundwater management problem necessitating urgent reliable and optimal management methodologies. This study focuses on the development and evaluation of groundwater salinity prediction tools, coastal aquifer multi-objective management strategies, and adaptive management strategies using new prediction models, coupled simulation-optimization (S/O) models, and monitoring network design, respectively. Predicting the extent of saltwater intrusion into coastal aquifers in response to existing and changing pumping patterns is a prerequisite of any groundwater management framework. This study investigates the feasibility of using support vector machine regression (SVMR), an innovative artificial intelligence-based machine learning algorithm, to predict salinity at monitoring wells in an illustrative aquifer under variable groundwater pumping conditions. For evaluation purposes, the prediction results of SVMR are compared with well-established genetic programming (GP) based surrogate models. The prediction capabilities of the two learning machines are evaluated using several measures to ensure their practicality and generalisation ability. Also, a sensitivity analysis methodology is proposed for assessing the impact of pumping rates on salt concentrations at monitoring locations. The performance evaluations suggest that the predictive capability of SVMR is superior to that of GP models. The sensitivity analysis identifies a subset of the most influential pumping rates, which is used to construct new SVMR surrogate models with improved predictive capabilities. The improved predictive capability and generalisation ability of SVMR models, together with the ability to improve the accuracy of prediction by refining the dataset used for training, make the use of SVMR models more attractive. Coupled S/O models are efficient tools that are used for designing multi-objective coastal aquifer management strategies. This study applies a regional-scale coupled S/O methodology with a Pareto front clustering technique to prescribe optimal groundwater withdrawal patterns from the Bonriki aquifer in the Pacific Island of Kiribati. A numerical simulation model is developed, calibrated and validated using field data from the Bonriki aquifer. For computational feasibility, SVMR surrogate models are trained and tested utilizing input-output datasets generated using the flow and transport numerical simulation model. The developed surrogate models were externally coupled with a multi-objective genetic algorithm optimization (MOGA) model, as a substitute for the numerical model. The study area consisted of freshwater pumping wells for extracting groundwater. Pumping from barrier wells installed along the coastlines is also considered as a management option to hydraulically control saltwater intrusion. The objective of the multi-objective management model was to maximise pumping from production wells and minimize pumping from barrier wells (which provide a hydraulic barrier) to ensure that the water quality at different monitoring locations remains within pre-specified limits. The executed multi-objective coupled S/O model generated 700 Pareto-optimal solutions. Analysing a large set of Pareto-optimal solution is a challenging task for the decision-makers. Hence, the k-means clustering technique was utilized to reduce the large Pareto-optimal solution set and help solve the large-scale saltwater intrusion problem in the Bonriki aquifer. The S/O-based management models have delivered optimal saltwater intrusion management strategies. However, at times, uncertainties in the numerical simulation model due to uncertain aquifer parameters are not incorporated into the management models. The present study explicitly incorporates aquifer parameter uncertainty into a multi-objective management model for the optimal design of groundwater pumping strategies from the unconfined Bonriki aquifer. To achieve computational efficiency and feasibility of the management model, the calibrated numerical simulation model in the S/O model was is replaced with ensembles of SVMR surrogate models. Each SVMR standalone surrogate model in the ensemble is constructed using datasets from different numerical simulation models with different hydraulic conductivity and porosity values. These ensemble SVMR models were coupled to the MOGA model to solve the Bonriki aquifer management problem for ensuring sustainable withdrawal rates that maintain specified salinity limits. The executed optimization model presented a Pareto-front with 600 non-dominated optimal trade-off pumping solutions. The reliability of the management model, established after validation of the optimal solution results, suggests that the implemented constraints of the optimization problem were satisfied; i.e., the salinities at monitoring locations remained within the pre-specified limits. The correct implementation of a prescribed optimal management strategy based on the coupled S/O model is always a concern for decision-makers. The management strategy actually implemented in the field sometimes deviates from the recommended optimal strategy, resulting in field-level deviations. Monitoring such field-level deviations during actual implementation of the recommended optimal management strategy and sequentially updating the strategy using feedback information is an important step towards adaptive management of coastal groundwater resources. In this study, a three-phase adaptive management framework for a coastal aquifer subjected to saltwater intrusion is applied and evaluated for a regional-scale coastal aquifer study area. The methodology adopted includes three sequential components. First, an optimal management strategy (consisting of groundwater extraction from production and barrier wells) is derived and implemented for the optimal management of the aquifer. The implemented management strategy is obtained by solving a homogeneous ensemble-based coupled S/O model. Second, a regional-scale optimal monitoring network is designed for the aquifer system, which considers possible user noncompliance of a recommended management strategy and uncertainty in aquifer parameter estimates. A new monitoring network design is formulated to ensure that candidate monitoring wells are placed at high risk (highly contaminated) locations. In addition, a k-means clustering methodology is utilized to select candidate monitoring wells in areas representative of the entire model domain. Finally, feedback information in the form of salinity measurements at monitoring wells is used to sequentially modify pumping strategies for future time periods in the management horizon. The developed adaptive management framework is evaluated by applying it to the Bonriki aquifer system. Overall, the results of this study suggest that the implemented adaptive management strategy has the potential to address practical implementation issues arising due to user noncompliance, as well as deviations between predicted and actual consequences of implementing a management strategy, and uncertainty in aquifer parameters. The use of ensemble prediction models is known to be more accurate standalone prediction models. The present study develops and utilises homogeneous and heterogeneous ensemble models based on several standalone evolutionary algorithms, including artificial neural networks (ANN), GP, SVMR and Gaussian process regression (GPR). These models are used to predict groundwater salinity in the Bonriki aquifer. Standalone and ensemble prediction models are trained and validated using identical pumping and salinity concentration datasets generated by solving numerical 3D transient density-dependent coastal aquifer flow and transport numerical simulation models. After validation, the ensemble models are used to predict salinity concentration at selected monitoring wells in the modelled aquifer under variable groundwater pumping conditions. The predictive capabilities of the developed ensemble models are quantified using standard statistical procedures. The performance evaluation results suggest that the predictive capabilities of the standalone prediction models (ANN, GP, SVMR and GPR) are comparable to those of the groundwater variable-density flow and salt transport numerical simulation model. However, GPR standalone models had better predictive capabilities than the other standalone models. Also, SVMR and GPR standalone models were more efficient (in terms of computational training time) than other standalone models. In terms of ensemble models, the performance of the homogeneous GPR ensemble model was found to be superior to that of the other homogeneous and heterogeneous ensemble models. Employing data-driven predictive models as replacements for complex groundwater flow and transport models enables the prediction of future scenarios and also helps save computational time, effort and requirements when developing optimal coastal aquifer management strategies based on coupled S/O models. In this study, a new data-driven model, namely Group method for data handling (GMDH) approach is developed and utilized to predict salinity concentration in a coastal aquifer and, simultaneously, determine the most influential input predictor variables (pumping rates) that had the most impact onto the outcomes (salinity at monitoring locations). To confirm the importance of variables, three tests are conducted, in which new GMDH models are constructed using subsets of the original datasets. In TEST 1, new GMDH models are constructed using a set of most influential variables only. In TEST 2, a subset of 20 variables (10 most and 10 least influential variables) are used to develop new GMDH models. In TEST 3, a subset of the least influential variables is used to develop GMDH models. A performance evaluation demonstrates that the GMDH models developed using the entire dataset have reasonable predictive accuracy and efficiency. A comparison of the performance evaluations of the three tests highlights the importance of appropriately selecting input pumping rates when developing predictive models. These results suggest that incorporating the least influential variables decreases model accuracy; thus, only considering the most influential variables in salinity prediction models is beneficial and appropriate. This study also investigated the efficiency and viability of using artificial freshwater recharge (AFR) to increase fresh groundwater pumping rates from production wells. First, the effect of AFR on the inland encroachment of saline water is quantified for existing scenarios. Specifically, groundwater head and salinity differences at monitoring locations before and after artificial recharge are presented. Second, a multi-objective management model incorporating groundwater pumping and AFR is implemented to control groundwater salinization in an illustrative coastal aquifer system. A coupled SVMR-MOGA model is developed for prescribing optimal management strategies that incorporate AFR and groundwater pumping wells. The Pareto-optimal front obtained from the SVMR-MOGA optimization model presents a set of optimal solutions for the sustainable management of the coastal aquifer. The pumping strategies obtained as Pareto-optimal solutions with and without freshwater recharge shows that saltwater intrusion is sensitive to AFR. Also, the hydraulic head lenses created by AFR can be used as one practical option to control saltwater intrusion. The developed 3D saltwater intrusion model, the predictive capabilities of the developed SVMR models, and the feasibility of using the proposed coupled multi-objective SVMR-MOGA optimization model make the proposed methodology potentially suitable for solving large-scale regional saltwater intrusion management problems. Overall, the development and evaluation of various groundwater numerical simulation models, predictive models, multi-objective management strategies and adaptive methodologies will provide decision-makers with tools for the sustainable management of coastal aquifers. It is envisioned that the outcomes of this research will provide useful information to groundwater managers and stakeholders, and offer potential resolutions to policy-makers regarding the sustainable management of groundwater resources. The real-life case study of the Bonriki aquifer presented in this study provides the scientific community with a broader understanding of groundwater resource issues in coastal aquifers and establishes the practical utility of the developed management strategies

Geo-Environmental Approaches for the Analysis and Assessment of Groundwater Resources at Catchment-Scale

This book focuses on the tools and methods used for tackling the complexity of the different hydrological and hydrogeological set-ups, the hydrodynamic patterns, the site specifications, and the wide variability of internal and external factors and/or processes on the catchment-scale level that impose the need for combined integrated approaches of robust methods. This Special Issue aims to provide successful applications or new insights on the stand-alone or joint considerations of groundwater resources assessment and characterization methods and explore new state-of-the-art methodological concepts in light of a rapidly changing environment