Coastal Aquifer Research Articles

The Island of Unguja in Zanzibar (Tanzania) has experienced an accelerated urban development growth since the 1990s due to a rapidly increasing population. These rapid land demands put additional stress on the country’s ability to plan urban centers, cities, and the management of natural resources. The study aimed to determine the impact of urbanization on groundwater availability in the catchment area of the Masingini–Mwanyanya forest reserves from 1992 to 2022. The study used a detection approach to determine the Land Use Land Cover (LULC) changes for three decades, starting from 1992 to 2022. Landsat remote sensed images of 1992, 2002, 2012, and 2022 were used. Additionally, a paired t-test was conducted to determine the significant changes in mean population growth, urbanization, and humidity. The aquifer recharge evolution analysis was conducted using the QGIS software (3.34.8 released version). Obtained results revealed that for these three decades, the forest areas decreased by 14.5% (i.e., from 8.3 km2 in 1992 to 7.1 km2 in 2022), while built-up area increased from 0 km2 in 1992 to 1.7 km2 in 2022. Moreover, the evolution of undesirable Land Use Land Cover (LULC) changes, particularly the persistent conversion of forested areas into built-up zones, has been detected. This trend poses a significant threat to the sustainable management of water resources and catchment forest reserves. The study also indicated a decline in the recharge of the coastal aquifer supplying Zanzibar City, which decreased from 15.5 Mm3 to 11.1 Mm3. These findings highlight that the Masingini Forest Reserve is increasingly encroached by rapid urbanization, which is a phenomenon that may jeopardize the availability and sustainability of groundwater resources in the catchment without proper urban planning. Based on these results, the study recommends further research and upscaling of the existing findings, as well as collaboration with relevant authorities to redefine the Masingini–Mwanyanya forest catchment area to ensure the sustainable use of groundwater resources.

Mixing zones in carbonate coastal aquifers are dynamic interfaces where freshwater and seawater converge, triggering complex biogeochemical processes. This study investigates diagenetic barite (BaSO4) precipitation within such a mixing zone in the dolomitic aquifer of the Sierra de Gádor (SE Spain). Three sectors were analyzed: two active mixing zones—one associated with submarine discharge and the other affected by marine intrusion—and an uplifted, fossilized Pleistocene mixing zone. Mineralogical, petrographic, and geochemical analyses reveal extensive dissolution of the dolomitic bedrock, forming polygonal voids and fracture-controlled porosity, frequently covered by Fe and Mn oxides. Barite crystals were identified exclusively in the Fe oxide precipitates at depths where 80% of seawater is reached. The saturation index for barite in groundwater suggests near-equilibrium conditions across the fresh–brackish–saline transition; however, barite precipitation is localized where Fe oxides act as a geochemical barrier, concentrating Ba and enabling nucleation. SEM imaging shows well-formed euhedral barite crystals up to 100 µm in size. This form of crystallization would be similar to the marine diagenetic barite formation models involving organic matter degradation and Ba remobilization, translated to a coastal aquifer setting in this study. Trace metal analyses show significant enrichment of Pb (up to 20 wt%) and other elements (Zn, Ni, and Co), suggesting potential for ore-forming processes if redox conditions shift. This work proposes a conceptual model for diagenetic barite formation in coastal aquifers, emphasizing the role of Fe and Mn oxides as reactive substrates in metal cycling at the land–sea interface.

Effects of different wave calculation methods on groundwater flow and salt transport in coastal aquifers under irregular waves

Arsenic mobilization and recirculation dynamics: Groundwater circulation wells for enhanced decontamination in complex coastal aquifer environments

Controlling seawater intrusion in unconfined coastal aquifers through aquifer storage and recovery (ASR): Insights from sandbox experiments

Source apportionment of groundwater contamination and spatial variability in the Bohai Sea region (China).

Impact of groundwater extraction intensity on the monitoring design for seawater intrusion in heterogeneous coastal aquifers

Coastal aquifers are essential sources of freshwater for domestic, agricultural, and industrial use in many regions worldwide. However, these critical resources are increasingly threatened by seawater intrusion, a hydrogeological process exacerbated by excessive groundwater extraction, population growth, and climate change. A comprehensive understanding of the dynamics and research evolution of this phenomenon is vital to support the sustainable management of coastal water resources. This study presents a bibliometric analysis of global research on seawater intrusion in coastal aquifers from 2014 to 2024. Data were retrieved from the Scopus database and analysed using the Bibliometrix package in R, complemented by visualization techniques developed in Python. The analysis examines publication trends, identifies influential authors, institutions, and journals, explores international collaboration networks, and maps the thematic evolution of research topics. By applying key bibliometric indicators and established laws such as those of Bradford and Lotka, the study provides an integrated perspective on the structure, dynamics, and development of this research field.The findings contribute to a deeper understanding of global scientific efforts addressing seawater intrusion and offer insights to guide future research, technological innovation, and policy initiatives for the sustainable management of coastal groundwater resources.

Groundwater quality and hydrogeochemical analysis for assessing saltwater intrusion in coastal aquifers of Eastern Odisha, India

Coupled salt and nitrogen dynamics in coastal reservoir-adjacent aquifer systems under extreme rainfall event.

Abstract Continental coastal aquifer systems are well-studied worldwide and are often characterized on the basis of extensive and diverse borehole datasets. However, while it is postulated that in some cases, these aquifers may extend offshore, their seaward reach remains widely unknown due to the frequently limited availability of data, particularly for subsurface sediments and their pore water salinity. This paper presents a valuable characterization of the onshore aquifers in the Venetian-Friulian Plain (northeastern Italy) and their offshore extension in the Northern Adriatic Shelf, within ~20 km from the coastline. Three-dimensional digital geological and stratigraphic modeling was used to investigate geometries of the layered artesian aquifer system hosted in the Middle to Late Pleistocene sedimentary succession. Near-coastal and offshore aquifers are found to have mainly formed during coastline migration driven by sea level changes and low-permeability layers, sealing these aquifers, result from fine alluvial sediments during sea level lowstands or fine marine sediments during highstands. This study suggests that Quaternary glacio-eustatic fluctuations are mainly responsible for the genesis of the layered aquifer system in the study area. Given the consistency of depositional processes active in the Northern Adriatic Basin since Middle-Pleistocene, and that coastal fresh groundwater extends hundreds of meters below the topographic surface, this study confirms that the Northern Adriatic Basin has significant potential to host widespread offshore freshened groundwater aquifers. This resource might represent an additional freshwater supply in the future.

More than 50% of the world's largest countries and cities depend on groundwater for their daily needs. In particular, 80% of the largest cities in the Middle East, South Asia, and Central Asia rely on groundwater for drinking, irrigation, and industrial uses. In this review, we discuss the impacts of climate change on groundwater, various sources of arsenic contamination in groundwater, the current status of arsenic contamination in selected major countries in South Asia, the integrated application of remote sensing and machine learning methods in arsenic detection, and novel treatment techniques for the removal of arsenic from groundwater. In this study, we found that unconsolidated aquifers and coastal aquifers are the major sources of arsenic contamination in groundwater. On the basis of the present literature survey, the majorly affected coastal aquifers are 11 coastal provinces in Bangladesh, 9 provinces in Vietnam, 3 provinces in Cambodia, and 2 provinces in Thailand. In view of health impacts, the continuous consumption of arsenic-contaminated groundwater has serious health impacts, such as the detection of cancer in the skin, lungs, kidneys, and bladder; heart disease; hypertension; increased blood pressure; and nervous system problems. The advanced satellite images with genetic algorithm, support vector machine, and artificial neural network are highly efficient methods to detect arsenic in groundwater. Treatment techniques, namely, adsorption, membrane filtration, electrocoagulation, and ion-exchange processes, are more significant and effective methods for removing arsenic from groundwater. The lack of awareness among people and strategies for water management systems are the primary reasons for groundwater contamination in many parts of South Asian countries, and very few policies have been implemented at the international level to reduce arsenic contamination in groundwater. The present detailed review will be helpful to policymakers and nongovernmental organizations to take remedial measures and conduct awareness programs in rural and semiarid zones.

Michel Bakalowicz: Besides his contributions to a better understanding of coastal karst aquifers, a major scientist in karst hydrogeology

Extending DRASTIC vulnerability method for groundwater salinity assessment in the urmia coastal aquifer, NW Iran

Patescibacteria are an enigmatic group of bacteria of ultra-small sizes and reduced genomes, commonly found in subsurface environments but largely unexplored in terms of their ecological roles. Despite being present in both freshwater and marine systems, no study has explored how they distribute along salinity gradients. This study provides new insights into their distribution, diversity, and niche partitioning along a Mediterranean subterranean estuary characterized by a strong salinity gradient. We show that Patescibacteria taxa seem to adapt to varying groundwater salinity conditions, displaying a remarkable capacity to occupy fresh, brackish, and saline niches through changes in composition. The identification of ultra-small coccoid cells and symbiotic-like associations highlights a diversity of lifestyles within these groups and provides one of the scarce visual proofs of Patescibacteria. With most detected taxa being highly novel, these findings point to an overlooked importance of Patescibacteria in coastal aquifers, biogeochemically active sites ubiquitous along most coastlines.

Abstract. Local characterization of groundwater systems is critical for managing and protecting vulnerable resources. Geophysical methods can provide dense imaging of subsurface parameters to delineate lithological boundaries and water tables for hydrogeological investigation, though using a single geophysical method for determining lithologies can yield erroneous interpretations as different lithologies can have similar properties. By using several geophysical methods, it is possible to reduce this risk and better assign likely lithologies to subsurface units. We present two case studies where transient electromagnetics (TEM) and surface nuclear magnetic resonance (SNMR) are used in combination to delineate hydrogeological structures. Novel spatially constrained inversion in SNMR was used to provide horizontal consistency between soundings. Three coincident parameters, resistivity from the TEM measurements and water content and relaxation time from the SNMR measurements, were used in a K-means clustering scheme to resolve subsurface structures. The K-means clustering was evaluated with a silhouette index to pick the number of clusters. After clustering, each cluster was assigned a hydrogeological description based on the distinct features in the three parameters; e.g., a low resistivity, high water content, and high T2∗ are assigned as saltwater-saturated sand. In the first case study, the clusters enabled improved resolution of a regional water table in an unconfined aquifer setting with the multi-geophysical approach. The water table estimates were positively evaluated against multiple boreholes within 500 m of coincident geophysical models. The second case study illustrates how clustering, of SNMR and TEM models, can delineate saltwater intrusion in an island coastal aquifer, which would not be possible with any of these methods individually. Additionally, the clustering resolved the main shallow aquifer on the island. Our work illustrates how the combination of geophysical data can be used to improve the identification of hydrogeological layers and reduce interpretational bias.

ABSTRACT Seawater intrusion (SWI) is the most important hydrological problem in the highly populated coastal regions. SWI in the coastal aquifers is caused by the intense withdrawal of groundwater and reversal of the natural hydraulic gradient. The study focuses on geophysical and geochemical analysis to identify areas contaminated by saline water intrusion. Resistivity survey and groundwater analysis were conducted in 33 locations in the study area to identify the extent of SWI. Geochemical analysis indicated that the groundwater quality was not suitable for drinking and irrigation purposes in 64% and 85% of the study area, respectively. The areas with low resistivity and high values of water quality parameters, such as electrical conductivity, chloride, and low values of Na/Cl, indicate SWI. Resistivity study was verified by geochemical studies, and the results indicated high salinity prevailed up to 13.7 km, moderate salinity up to 16.5 km, and freshwater was present beyond 16.5 km from the coast. The study found that geophysical methods offer a valuable alternative to laborious geochemical approaches for estimating aquifer parameters and detecting saline water intrusion. The study indicated the need for proper management of coastal aquifers to control SWI.

Groundwater salinization poses a critical threat to freshwater security in coastal regions, particularly under intensified extraction and evolving hydroclimatic conditions. This study examines the spatial and temporal evolution of salinity in the lower Chao Phraya River Basin during 2008 and 2020 using a multi-method machine learning framework. SHAP-based feature attribution analysis identified groundwater extraction as the most influential driver of salinity dynamics. A Gaussian copula model was employed to quantify the conditional probability of salinity threshold exceedance under varying extraction pressures, capturing nonlinear dependence structures between total dissolved solids (TDS) and groundwater extraction. A Graph Neural Network (GNN) model was developed to simulate TDS concentrations at 212 monitoring stations, demonstrating high predictive performance across both periods. To translate model outputs into actionable insights, a scenario-based Decision Support System (DSS) was implemented, enabling interactive visualization of salinity risk zones under 20% and 40% increases in groundwater withdrawal. Results reveal a pronounced expansion of high-salinity areas over time, largely driven by anthropogenic factors. By fusing explainable machine learning with probabilistic analysis and decision support, this framework provides a novel, scalable tool for real-time groundwater salinity risk assessment and supports evidence-based management in data-scarce coastal aquifers.

This study aims to evaluate key parameters of groundwater quality and associated health risks in three coastal aquifers of Cox's Bazar, Bangladesh, with a focus on manganese contamination and geochemical processes. A total of 288 groundwater samples from 36 monitoring wells were analyzed to assess physicochemical parameters and calculate the Water Quality Index (WQI). Hydrogeochemical facies revealed distinct water types, with the Dupi Tila aquifer containing predominantly fresh Ca-HCO₃ type water, while the Tipam and Bokabil aquifers exhibited Na-Cl-SO₄ facies, indicating seawater intrusion and water-rock interactions. To predict WQI and identify key influencing parameters, four machine learning (ML) models, Random Forest (RF), Gradient Boosting Regressor (GBR), XGBoost, and Artificial Neural Network (ANN) were employed. Among these, XGBoost achieved the highest prediction accuracy (R2 = 0.947, RMSE = 12.2, MAPE = 9.6%), followed by GBR and RF, while ANN showed lower performance. Feature importance analysis highlighted manganese (Mn), total dissolved solids (TDS), sodium (Na⁺), and chloride (Cl⁻) as dominant predictors. Health risk assessments using Hazard Quotient (HQ) analysis identified manganese as a significant threat, particularly for children, with over 50% of samples exceeding safe limits. The findings emphasize the need for regular monitoring and targeted mitigation in vulnerable aquifers. This study is novel in its integration of ML algorithms with geochemical analysis in a refugee-impacted coastal region, offering a predictive framework for sustainable groundwater management. The outcomes are broadly applicable to similar hydrogeological settings affected by salinization and trace metal contamination.

Hydrogeochemical characterization and human health risk assessment for heavy metal contamination in coastal aquifers: A case study in Satkhira District, Bangladesh.