Aquifer Management Research Articles

Estimation of Ground Water Recharge in the Command Area of Krishna Central Delta

Groundwater recharge is the most important component in all the water balance studies and in ground water development projects as a part of sustainable groundwater management. Norms set by the Groundwater Resource Estimation Committee, GEC-2015 was used for the estimation of recharge. The study was conducted for the Bandar canal command area constituting the Krishna Central Delta in Andhra Pradesh. Following the norms of GEC-2015, the recharge was estimated for the past decade from 2012-13 to 2021-22 and it was found that recharge rate ranged from 438135.8 ha-m in the year 2015-16 to 1677730 ha-m in the year 2013-14. While computing the gross recharge, recharge attributed by rainfall, canal seepage, irrigation return flow and from the ponds/tanks are considered. Recharge estimated sheds information on replenishment and improved management of coastal aquifers where seawater intrusion is a major problem.

Aquifer Management Establishing a Tradable Water Rights System: The Effect of Natural Discharge and Salinity

Economic instruments such as tradable water rights systems have been proposed as cost-effective methods for managing groundwater. The relevant literature shows that the majority of the relevant studies do not consider aquifer’s natural discharge, which is expected to have a significant impact on the determination of the optimal groundwater management policy. This paper attempts to highlight the impact of considering natural discharge in the formulation of groundwater management policies. Thus, two different cases of aquifer management are considered and the corresponding time-dynamic problems are solved by considering natural discharge in order to derive optimal trajectories for a number of key variables. These cases are (1) non-intervention – full competition and (2) intervention with a tradable water rights system. The results obtained from simulations on a coastal aquifer show that indeed not considering the natural discharge leads to an overestimation of the benefits from groundwater consumption that can reach 5.79% in the case of non-intervention and in the case of intervention with a tradable water rights system.

Modelling groundwater pollutant transfer mineral micropollutants in a multi-layered aquifer in Burkina Faso (West African Sahel)

In Burkina Faso, human activities around water points in rural areas affect groundwater resources, which become unfit for consumption. Nearly 33.5% of boreholes are subject to point source pollution. The assessment of the evolution of such pollution should be monitored to assess groundwater quality. In addition, withdrawals for irrigation alone are estimated at 85%, i.e. 46% of the water demand, heightening the deterioration in quality while creating depression zones further leading to an increase in recharge. It is therefore critical to understand the evolution and fate of the transfer of pollutants in such environments. In this study, we aimed to model the transfer of pollutant and predict the future state of pollution using the MT3D-USGS Groundwater Solute Transport Simulator code through the Groundwater Modelling Software (GMS) over the period 2012–2062 (50 years). A mathematical model is further developed through inferential statistics and used as a surrogate model for comparison. The results showed that deterioration in water quality was more attributable to withdrawals, especially for Cyanide (Cn) and Arsenic (As). A rather slow degradation is reported for Lead (Pb), which extends over 22 km, and Fluoride (F), which extends from 4 to 10 km due to localized recharge. A faster degradation for Cn over a distance of 2–16 km and as from 3 to 11 km is also observed because of the geological setting of the subsoil. These results might assist decision-makers for the quantitative and qualitative management of groundwater resources, and the management of the basement aquifer in the area through the establishment of protection zones.

Reconstructing high-resolution groundwater level data using a hybrid random forest model to quantify distributed groundwater changes in the Indus Basin

High-resolution, continuous groundwater data is important for place-based adaptive aquifer management. This information is unavailable in many areas due to spatial sparsity of and temporal gaps in groundwater monitoring. This study advances the ability to generate high-resolution (1 km2), temporally continuous estimates of groundwater level (GWL) changes by incorporating 1 km2 covariates and existing piezometer observations into predictive modeling. We employed a hybrid machine learning (ML) model, primarily using the geographically weighted random forest (RFgw) model. To assess the performance of the RFgw model, we conducted a comprehensive comparison with the SGS geostatistical method and non-spatial ML models (RF and XGBoost). The framework was implemented across the Indus Basin using biannual (July and Oct) GWL data from piezometers and local covariates from 2003 to 2020. The RFgw model demonstrated superior accuracy in predicting GWLs, improving R2 by 10 %, 17 %, and 22 % compared to SGS, RF, and XGBoost, respectively. Notably, SGS, RF, and XGBoost substantially underestimated the GWL in deeper wells (7–11 m), whereas RFgw showed a much smaller underestimation (up to ∼ 3 m). The 90 % prediction interval revealed that RFgw had less uncertainty (1–3 m) followed by RF (2–5 m), and SGS and XGBoost (up to 8 m) for most testing piezometers. Incorporating high-resolution covariates into RFgw predictive modeling provided reliable estimates of GWL changes for unmonitored sites. Using the reconstructed GWL data, we examined the GWL changes in head (i.e., upstream) and tail (i.e., downstream) farms within canal distributaries, illustrating faster groundwater drawdown in tail farms (e.g., 0.82 m/yr) than head farms (0.02 m/yr in the Hakra canal distributary). Densely populated urban areas (e.g., Lahore, Multan, and Faisalabad) had the highest GWL decline (e.g., up to 0.9 m/yr). The framework can be used in other groundwater-stressed regions to support better aquifer management in the face of limited in-situ observations.

Aquatic microdiversity from urban cenotes in Cancun, Quintana Roo, Mexico

The microdiversity of cenotes in the Yucatan Peninsula, Mexico has been little studied, with the phytoplankton and protists being the most representative species. However, all previous studies have been focused on cenotes associated with touristic activities, leaving a gap in the understanding of cenotes located within urban areas. The present study is dedicated to the identification of phytoplankton and protists in the cenotes of Cancun, Quintana Roo, Mexico. We conducted our research in four urban cenotes, collecting samples using a 150 µm plankton net, filtering them with a 45 µm membrane, and examining them under optical microscopy. Subsequently, we calculated the abundance, richness, and completeness of the samples. Our findings revealed a total of 6 phyla, 4 subphyla, 10 classes, 8 subclasses, 15 orders, 15 families, 18 genus, and 17 species and 4 species indeterminata in the cenotes of Cancun, Quintana Roo, Mexico. Among these, there were 8 species of phytoplankton and 1 species indeterminata, while 9 species of protists and 3 species indeterminata. These results highlight the remarkable species richness and the complex structure and composition of urban cenotes, suggesting that some species may be unique to this particular ecosystem. Currently, there is limited knowledge regarding the behavior of these aquifers (urban cenotes), and a comprehensive inventory or characterization of their microdiversity is lacking. Such information could be instrumental in the management, conservation, and sustainable use of these valuable aquifers.

Comprehensive uncertainty analysis for surface water and groundwater projections under climate change based on a lumped geo-hydrological model

Sustainable management of aquifers requires long-term predictions of their aquifer-scale groundwater balance under climate change with meaningfully quantified uncertainty. In our analysis, we account for uncertainty in model parameters, measured data, model errors, stochastic model inputs (e.g., rainfall, potential evapotranspiration), and climate scenarios. To afford this analysis, we rely on an extension of lumped hydrological models that includes groundwater flow and storage, called lumped geohydrological model (LGhM). It shows good model performance and is three orders of magnitude faster than 2D or 3D numerical groundwater models. We use Markov chain Monte Carlo (MCMC) for Bayesian inference on a calibration period to quantify posterior parameter uncertainty and lumped data-and-model error. Then, we perform Monte Carlo forward runs with stochastic weather inputs under three different climate scenarios to quantify uncertainty in long-term predictions up to the year 2040. We apply our approach on a virtual reality representation of the Wairau Plain aquifer, New Zealand. We hypothesize that the variability in future climate is the most important impact factor. To test this hypothesis, we disentangle the overall uncertainty between data/model, parameters, weather, and climate inputs. We expect our approach to be highly useful for arbitrary types of catchments because the LGhM model structure can easily be adapted.

Coastal Aquifer Management: Hydrological, Environmental, Economic and Social Challenges in the Context of Global Change

Groundwater is limited and its sustainable use is peremptory if we are to preserve dependent ecosystems and human supplies [...]

Water Balance Calculation for a Transboundary Aquifer System between Estonia and Latvia

Groundwater management in transboundary aquifers is complex due to the hidden nature of groundwater and its intricate interactions with surface water. The overarching issue lies in the need for improved tools and strategies to manage transboundary aquifers effectively, given their critical importance to regional water resources and ecosystems. In addressing these challenges, this study focuses on a specific transboundary aquifer system between Estonia and Latvia, situated within the sedimentary rocks of North-East Europe. Here, we propose a conceptual model approach as a valuable tool for comprehending the hydrogeological characteristics of transboundary aquifers and supporting more efficient management strategies. Utilizing open-source software MODFLOW-6, our developed conceptual model integrates the aquifer system’s geological and hydrogeological framework and simulates groundwater flow under transient conditions. Our findings highlight a profound hydrological connection between groundwater and surface water, particularly within the first 200 m of the aquifer. Despite varying cross-border groundwater flows, collaboration remains vital for sustainable transboundary aquifer management, aligning with international agreements such as the Water Convention and the EU Water Framework Directive, benefiting similar systems.

An adaptive multi-fidelity optimization framework based on co-Kriging surrogate models and stochastic sampling with application to coastal aquifer management

Surrogate modelling has been used successfully to alleviate the computational burden that results from high-fidelity numerical models of seawater intrusion in simulation-optimization routines. Nevertheless, little attention has been given to multi-fidelity modelling methods to address cases where only limited runs with computationally expensive seawater intrusion models are considered affordable imposing a limiting factor for single-fidelity surrogate-based optimization as well. In this work, a new adaptive multi-fidelity optimization framework is proposed based on co-Kriging surrogate models considering two model fidelities of seawater intrusion. The methodology is tailored to the needs of solving pumping optimization problems with computationally expensive constraint functions and utilizes only small high-fidelity training datasets. Results from both hypothetical and real-world optimization problems demonstrate the efficiency and practicality of the proposed framework to provide a steep improvement of the objective function while it outperforms a comprehensive single-fidelity surrogate-based optimization method. The method can also be used to locate optimal solutions in the region of the global optimum when larger high-fidelity training datasets are available.

Hydrogeophysical Investigation in Parts of the Eastern Dahomey Basin, Southwestern Nigeria: Implications for Sustainable Groundwater Resources Development and Management

Geoelectrical resistivity measurements were conducted in five locations within the eastern portion of the Dahomey basin for the purpose of subsurface evaluation and detecting saturated zones. The locations are Covenant University (L1), Bells University (L2), Oju-Ore-Ilogbo Road (L3), Obasanjo-Ijagba Road (L4), and Iyana Iyesi (L5). The study was carried out to avert the common challenges of drilling low-yield groundwater boreholes in the area. A total of 30 Vertical Electrical Soundings (VES) and five two-dimensional Electrical Resistivity Tomography (ERT) data sets have been acquired along the study areas. The geoelectrical resistivity results were integrated with the borehole logs to generate the spatial distribution of the subsurface lithologies in the area. The delineated subsurface lithologies include the topsoil (lateritic clay), clayey sand, sandy clay, fine silty sand, coarse sand, and shale/clay units. The fine silty sand and coarse sand units were identified as the two main aquifer units within the area. The depths to the upper aquifer unit in the area include 31.7–96.7 m, 38.5–94.0 m, 30.7–57.5 m, 39.1–63.4 m, and 46.9–57.5 m for locations L1, L2, L3, L4, and L5, respectively. At the same time, the depths to the lower aquifer unit in the area include 43.4–112.7 m, 52.2–108.0 m, 44.2–72.5 m, 53.7–78.5 m, and 63.5–72.9 m for locations L1, L2, L3, L4, and L5, respectively. The estimated hydraulic parameters for both aquifers show they are highly productive with mean porosity, mean hydraulic conductivity, and mean transmissivity of 20–22%, 12.4–17.0 × 10−2 m/s, 1.56–2.18 m2/s for the upper aquifer, and 48–50%, 371–478 × 10−2 m/s, 50.00–62.14 m2/s for the lower aquifer. By focusing on these aquifer systems during exploration, sustainable groundwater resources can be secured, providing relief to homeowners within the study area who might otherwise face the frustration of drilling unproductive and low-yield boreholes. However, it is crucial to consider the presence of sub-vertical faults in the study area, as these faults can significantly impact groundwater development and management. These sub-vertical structural faults may lead to changes in the permeability, hydraulic conductivity, and transmissivity of the delineated aquifers, affecting their productivity across the divide and ultimately influencing the overall water availability in the area. Careful consideration of these geological factors is essential for effective aquifer management and sustainable groundwater utilisation.

Analysis of Aquifer‐System Deformation in the Doñana Natural Space (Spain) Using Unsupervised Cloud‐Computed InSAR Data and Wavelet Analysis

AbstractThis work is focused on the Almonte‐Marismas aquifer located within Doñana Natural Space (SW Spain); this aquifer is threatened by droughts, irrigation‐driven groundwater overexploitation, urban use, and the potential reactivation of gas extraction and storage projects. We present ground deformation measurements from Sentinel‐1 Interferometric Synthetic Aperture Radar (InSAR) data ranging from 1 to 2.5 cm, covering ∼2,500 km2 from 2014 to 2020. Detecting spatially distributed ground deformation over this agricultural area is challenging due to the low‐coherence radar signals; consequently, the ground movement results are on the same order of magnitude as the errors associated with InSAR data. We have approached this issue by considering auxiliary information such as groundwater levels, climatic time series, and pumping rates and analyzing their spatio‐temporal connections to ground displacements. We correlate InSAR and hydrogeological information through wavelet analysis, developing a Python package that allows applying the same methodology in other similar study areas. For the first time in the Doñana area, a significant relationship between distances to pumping wells and the displacement extent is detected. Moreover, other subsidence‐related triggering factors are identified, such as the soil moisture balance, clay shrinking‐swelling processes, and creep of geological formations. These results are highly valuable to support aquifer management decisions in the Doñana Natural Space; in this border region, three groundwater bodies were officially declared overexploited in 2020. Our findings provide a ground motion baseline assessment to help differentiate historical variations from any future anthropogenic effect in this complex marsh land ecosystem.

Water accounting in the Berrechid plain (Morocco): A process approach

AbstractWater scarcity is a growing challenge to the governance of water resources and to multiple water uses. Dealing with water scarcity requires a better‐shared understanding of water supply and demand dynamics on the part of the different stakeholders who contribute to and/or suffer the consequences of water scarcity. This study highlights the importance of establishing a water accounting system for groundwater management in the Berrechid plain (Morocco) and the conditions under which such accounting may help solve current water issues. The plain is under considerable water stress, and stakeholders are struggling to implement aquifer management plans to ensure groundwater sustainability. The study identified and quantified various components of the water balance and estimated annual groundwater overexploitation for the period 2001–2018 to be 32 million m3. Fractional analysis of the water balance showed that the reason for aquifer water stress was a rapid increase in irrigated land and current intensive agricultural and irrigation practices, which threaten both the sustainability of water resources and economic activities in the plain. To improve water governance, a system of water accounting is required that promotes responsible use and ensures that all stakeholders are answerable and accountable for their water consumption along with any actions that may affect water flows.

Performance comparison of physics-based and machine learning assisted multi-fidelity methods for the management of coastal aquifer systems

In this work we investigate the performance of various lower-fidelity models of seawater intrusion in coastal aquifer management problems. The variable density model is considered as the high-fidelity model and a pumping optimization framework is applied on a hypothetical coastal aquifer system in order to calculate the optimal pumping rates which are used as a benchmark for the lower-fidelity approaches. The examined lower-fidelity models could be classified in two categories: (1) physics-based models, which include several widely used variations of the sharp-interface approximation and (2) machine learning assisted models, which aim to improve the efficiency of the SI approach. The Random Forest method was utilized to create a spatially adaptive correction factor for the original sharp-interface model, which improves its accuracy without compromising its efficiency as a lower-fidelity model. Both the original sharp-interface and Machine Learning assisted model are then tested in a single-fidelity optimization method. The optimal pumping rated which were calculated using the Machine Learning based SI model sufficiently approximate the solution from the variable density model. The Machine Learning assisted approximation seems to be a promising surrogate for the high-fidelity, variable density model and could be utilized in multi-fidelity groundwater management frameworks.

Modeling Water Flow and Solute Transport in Unsaturated Soils Using Physics‐Informed Neural Networks Trained With Geoelectrical Data

AbstractAccurate modeling of water flow and solute transport in unsaturated soils is of significant importance for precision agriculture, environmental protection and aquifer management. Traditional modeling approaches are considerably challenging since they require well‐defined boundaries and initial conditions. Physics‐informed neural networks (PINNs) have recently been developed to learn and solve forward and inverse problems also constrained to a set of partial differential equations and are more flexible than traditional modeling approaches. However, hydrological applications of PINNs used so far spatial measurements of hydraulic head, water content and/or solute concentrations, which were well distributed in the subsurface for training the system. Such measurements are hard to obtain in real‐world applications. Here, we propose to train PINNs with non‐invasive geoelectrical tools for simulating two‐dimensional water flow and solute transport during infiltration and redistribution processes with unknown initial conditions. Two‐dimensional flow and transport numerical simulations were used as benchmarks to examine the suitability of the described approach. Results have shown that the trained PINNs system was able to reproduce the spatiotemporal distribution of both water content and pore‐water salinity during both processes with high accuracy, using five time‐lapse geoelectrical measurements and matric head measurements at a single location. The trained PINNs system reconstructed the initial conditions of both state parameters at both processes. It was also able to separate the measured electrical signal into its two components, that is, water content and pore‐water salinity. The subsurface geoelectrical tomograms were significantly improved compared to those obtained from a classical inversion of the raw geoelectrical data.

Optimal management of the groundwater coastal aquifer based on the hydraulic characteristics in Wadi Al Marwani basin: KSA

Optimal management of the groundwater coastal aquifer based on the hydraulic characteristics in Wadi Al Marwani basin: KSA

Spatio-temporal evaluation of trace element contamination using multivariate statistical techniques and health risk assessment in groundwater, Khulais, Saudi Arabia

Groundwater is the only freshwater source for agriculture and domestic use in the Khulais region of Saudi Arabia (SA). Anthropogenic activities, particularly agricultural runoff and lithogenic sources cause groundwater contamination, posing health risks to all generations (infant, child, and adult) via ingestion, dermal, and inhalation exposure routes. The configuration of non-carcinogenic and carcinogenic health concerns posed by contaminated water is, thus, a time-sensitive requirement. This study uses multivariate statistical techniques to assess health risks and to identify health impacts and pollution sources. Sampling of groundwater at nineteen sampling sites was carried out in two seasons (winter and summer) of 2021. The samples were analyzed for major ions and toxic metals. Results show that the average hazard quotient (HQ) and health hazard index (HHI) in infants was higher than 1 for most of toxic metal in both the seasons. The health risks associated with ingestion were significantly higher than those associated with the dermal and inhalation pathways. The aquifer’s carcinogenic risk ranged from high to extremely high in terms of chromium (Cr), nickel (Ni), and lead (Pb) concentrations. The estimated health risk values may have a negative impact on people’s health, which suggests that active aquifer management should be implemented. Multivariate statistical analyses were accomplished to determine the primary contamination sources in the aquifer system. The total dissolved solid (TDS) correlated strongly among chloride (Cl−), sulphate (SO42−), sodium (Na+), potassium (K+), magnesium (Mg2+), calcium (Ca2+), iron (Fe), strontium (Sr), fluoride (F−) and bromide (Br−), which caused by seawater intrusion within winter and summer seasons. The hierarchical cluster analysis (HCA) identifies two clusters and one independent case within the summer and winter seasons. One-way analysis of variance (ANOVA) showed significant variations in the concentrations of Mg2+, Aluminum (Al), Cobalt (Co), Cr, Ni, and Pb in winter, while TDS, electrical conductivity (EC), Cl−, SO42−, Na+, Mg2+, Ca2+, Sr, F− and Br− in summer. This research demonstrates that aquifer cleanup and management protocols should be implemented, encouraged, and maintained. Applying the best hygienic practices and pre-clean-up of polluted groundwater is recommended before application for different purposes.

Sustainable aquifer management for food security

Sustainable aquifer management for food security

Characterization and Productivity of Alluvial Aquifers in Sustainability Oasis Areas: A Case Study of the Tata Watershed (Southeast Morocco)

Groundwater from alluvial aquifers is a critical source of water supply for rural agriculture, particularly in semi-arid and arid regions. Effective management of these aquifers requires an understanding of the factors that influence their water resources. In this study, we present a case study of the Tata watershed in southeastern Morocco, where the economy is heavily dependent on agriculture and relies exclusively on groundwater. We demonstrate the importance of integrating geological, hydrogeological, and geophysical methods to characterize the aquifer and evaluate groundwater productivity. Analysis of 64 data wells tapping into the aquifer revealed significant disparities in flow yields, ranging from 0.05 to 15.50 L per second. The highest yields were found between depths of 12 and 43 m, which correspond to the alluvium and the altered and fractured part of its substrate. The maximum alluvial thickness of 57 m was determined using geo-electrical prospecting. A piezometric map was created to define the recharge zones, which correspond to the lateral contributions of the bordering Georgian limestones, and infiltration of both rain and surface water along the Tata wadi. Since 1987, there has been a continuous drop in groundwater level, which can be attributed to the increase in irrigated areas following financial incentives provided by the Moroccan government to the agricultural sector. A proposal has been made for the construction of a recharge dam to enable the recharge of the alluvial aquifer. This development is expected to serve a dual purpose by mitigating the deleterious impacts of flooding and facilitating the gradual water infiltration of the alluvial aquifer. This case study provides insights into the hydrodynamics of the aquifer and establishes a simplified model of its functioning. These findings have important implications for the management of alluvial aquifers in similar regions.

Ant-Inspired Metaheuristic Algorithms for Combinatorial Optimization Problems in Water Resources Management

Ant-inspired metaheuristic algorithms known as ant colony optimization (ACO) offer an approach that has the ability to solve complex problems in both discrete and continuous domains. ACOs have gained significant attention in the field of water resources management, since many problems in this domain are non-linear, complex, challenging and also demand reliable solutions. The aim of this study is to critically review the applications of ACO algorithms specifically in the field of hydrology and hydrogeology, which include areas such as reservoir operations, water distribution systems, coastal aquifer management, long-term groundwater monitoring, hydraulic parameter estimation, and urban drainage and storm network design. Research articles, peer-reviewed journal papers and conference papers on ACO were critically analyzed to identify the arguments and research findings to delineate the scope for future research and to identify the drawbacks of ACO. Implementation of ACO variants is also discussed, as hybrid and modified ACO techniques prove to be more efficient over traditional ACO algorithms. These algorithms facilitate formulation of near-optimal solutions, and they also help improve cost efficiency. Although many studies are attempting to overcome the difficulties faced in the application of ACO, some parts of the mathematical analysis remain unsolved. It is also observed that despite its popularity, studies have not been successful in incorporating the uncertainty in ACOs and the problems of dimensionality, convergence and stability are yet to be resolved. Nevertheless, ACO is a potential area for further research as the studies on the applications of these techniques are few.

The impact of future hydrology stresses and climate change on submarine groundwater discharge in arid regions: A case study of the Nile Delta aquifer, Egypt

Study regionClimate change is expected to severely impact Egypt's Nile Delta Aquifer (NDA). Despite its large freshwater reservoir, estimated at 400 Billion Cubic metres (BCM), climate-change-induced drivers (drought and sea-level rise) coupled with increasing groundwater over-abstraction will cause a gradual reduction of the available freshwater volume. This study used the numerical model SEAWAT to study the impact of the main hydrogeological and anthropogenic factors on the response of the submarine groundwater discharge (SGD) (i.e., the net fresh seaward groundwater flux) and seawater intrusion (SWI) in the NDA. Study focusFive scenarios were examined, including (i) a probable Sea-level rise (SLR), (ii) expected reduction in Nile hydrograph and its branches, (iii) freshwater overpumping, (iv) the combination of reduction in Nile hydrograph and overpumping, and (v) the combination of these scenarios in the years 2030, 2050 and 2070. New hydrological insights for the regionThe results show that the increasing saltwater head due to SLR coupled with a reduction in Nile flow and overpumping ultimately results in the landward shifting of the saltwater within the aquifer. In addition, the resulting salinity increase in the aquifer caused a significant increase in the deterioration of a large quantity of freshwater volume with a subsequent reduction of the SGD. Also, the salt mass variation (SMV) in scenario 5 increased to 7.09%, 10.69%, and 12.99%, while the groundwater discharges variation (SGDV) to the sea declined by 21.90%, 42.38%, and 61.95% in the years 2030, 2050 and 2070, respectively. Moreover, the coastal aquifers required the management of the SGD to keep the balance between the freshwater and saltwater interface. This study is useful for the future planning and water resources management in coastal regions for integrated management of SGD, SWI, and aquifer freshwater storage. Also, the applications of smart measurements of SGD and groundwater salinity are required for coastal aquifers management.