Weijiang Yu

Global warming is altering sea‐surface salt concentration (SSC) through intensified evaporation, shifted precipitation patterns, and accelerated melting of polar ice. Subsurface freshwater in oceanic islands is typically shaped like a thin lens due to limited land area and recharge, often the primary freshwater source for local communities and highly vulnerable to seawater intrusion (SWI). However, the effects of SSC changes on freshwater lens (FWL) and SWI extent in island aquifers remain unknown, and there is little knowledge on how hydraulic conductivity (HK), local aquifer recharge (RCH) and island width ( L ) affect these effects. To end this, this study employs a simplified two‐dimensional, variable‐density island groundwater simulation model to investigate how SSC affects FWL and SWI extent across seven distinct hydrogeological scenarios, using six quantitative indicators: relative changes in (a) average water table elevation (WTE), (b) maximum WTE, (c) FWL depth, (d) FWL thickness, (e) fresh groundwater volume, (f) aquifer salt mass. Simulation results demonstrate that rising SSC increases aquifer salt mass and elevates WTE while shrinking FWL (reducing its depth, thickness, and freshwater volume), as enhanced freshwater‐saltwater density contrasts drive more vertical flow pushing FWL upward. Island aquifers with higher HK, lower RCH, or smaller L show minimal changes in WTE and aquifer salt mass but are more sensitive to SSC changes in terms of FWL depth, thickness and fresh groundwater volume. Moreover, WTE and FWL characteristics show greater sensitivity to SSC declines than to SSC increases.

Submarine groundwater discharge (SGD) is an important pathway for water and solute exchange between coastal aquifers and the ocean, but its spatial detection remains challenging because field methods have limited coverage and remotely sensed anomalies may also reflect other coastal processes. This study developed a hydrodynamically constrained remote sensing framework for SGD identification by integrating optical and thermal indicators with hydrogeological constraints. Sentinel-2 imagery was used to derive the Normalized Difference Chlorophyll Index (NDCI) and Normalized Difference Turbidity Index (NDTI), while Landsat thermal data were used to quantify seasonal sea surface temperature variability using the 90th–10th percentile amplitude. These indicators were combined in a K-means clustering framework, and the classification results were further constrained using year-specific maximum offshore distances estimated from groundwater level observations with a Dupuit–Glover-based scaling approach and hydraulic time-lag correction. Applied to the north shore of Long Island, New York, the framework identified coherent nearshore SGD patches that were broadly consistent with field observation locations and showed both temporally persistent discharge zones and interannual variability in spatial extent. These results indicate that incorporating physically based constraints can improve the robustness and interpretability of remote sensing-based SGD detection.

Subsurface freshwater in oceanic islands is typically shaped like a thin lens due to limited land area and recharge, often the primary freshwater source for local communities and highly vulnerable to seawater intrusion (SWI). Freshwater injection (FI) is considered as a feasible strategy for mitigating SWI in coastal aquifers. However, its transient effectiveness for freshwater lens (FWL) development and SWI mitigation in island aquifers and how the design parameters like FI depth, intensity, duration and injectant concentration affect its performance remain poorly understood. To address this, this study employs a two-dimensional, variable-density island groundwater model to simulate the transient responses of FWL development and SWI mitigation to various FI patterns. Five indicators are developed for comprehensive evaluation, including (1) freshwater recovery efficiency (FRE), and the relative changes in (2) average water table elevation (WTE), (3) FWL depth, (4) FWL volume, and (5) total aquifer salt mass. Results reveal FI universally raises average WTE, expands FWL dimensions, and promotes aquifer desalinization. Injection intensity is the primary driver of WTE rises and salt mass reduction, with higher intensities consistently yielding greater WTE rises and salt mass reductions. Deeper injection within the mixing zone increases FWL depth, but reduces the net gain in FWL volume. Moreover, early-stage FI is highly efficient for expanding FWL volume, often yielding FRE values above 100%, but FRE converges toward zero over time as the system moves toward a new hydrodynamic equilibrium, returning diminishing marginal benefits for long-term FI.

Subsurface freshwater in oceanic islands is typically shaped like a thin lens due to limited land area and recharge, often the primary freshwater source for local communities and highly vulnerable to seawater intrusion (SWI). Saltwater abstraction (SA) is considered as a feasible strategy for mitigating SWI. However, its transient effectiveness for freshwater lens (FWL) development and SWI mitigation in island aquifers, and how the design parameters like SA depth, intensity, and duration affect its performance, remain poorly understood. Therefore, this study employs a two-dimensional, variable-density island groundwater model to simulate the transient responses of FWL development and SWI mitigation to various SA patterns. Six indicators are developed for comprehensive evaluation, including: (1) freshwater recovery efficiency, and the relative changes in (2) average water table elevation (WTE), (3) WTE at the SA well, (4) FWL depth, (5) fresh groundwater volume, and (6) total aquifer salt mass. Simulation results highlight SA depth as the primary determinant of its effectiveness, characterized by critical thresholds that dictate whether SA imposes net positive or negative effects on FWL depth, volume, and aquifer desalinization, with SA intensity and duration serving as scaling factors that amplify the magnitude of these responses. Moreover, while SA can effectively expand FWL volume and shift it toward a more favorable hydrodynamic equilibrium, the diminishing marginal benefits over time cause the FRE to approach zero, indicating SA is a potent short-term restoration strategy rather than a long-term solution from a cost–benefit perspective.

Sea-level rise (SLR) and regional precipitation pattern change cause island subsurface freshwater, typically shaped like a thin lens, to be at higher risk of contamination from seawater intrusion (SWI). Installing a cutoff wall is considered a feasible strategy for protecting coastal fresh groundwater from SWI. However, the performance of the cutoff wall in managing freshwater lens (FWL) development and mitigating SWI into island aquifers under SLR and aquifer recharge (RCH) fluctuations remains inadequately quantified. This study investigates how water table elevation (WTE), FWL depth, thickness, and SWI extent, measured by aquifer salt mass and freshwater volume, in an island aquifer equipped with cutoff walls, respond to SLR and RCH fluctuations. It focuses on a two-dimensional, variable-density island groundwater simulation model based on hydrogeological conditions of San Salvador Island, Bahamas. The results demonstrate that RCH critically influences cutoff wall effectiveness for FWL development and SWI mitigation, with higher RCH amplifying gains in WTE, FWL metrics, freshwater storage, and aquifer salt removal, but this influence diminishes with wall depth increasing. SLR elevates WTE in a stable manner associated with its magnitude but negligibly affects the cutoff wall performance in FWL enhancement and SWI mitigation. Under simultaneous SLR and RCH fluctuations, SLR can offset the WTE reduction caused by reduced RCH, but the joint effects of SLR and RCH on FWL metrics, freshwater storage and aquifer salt removal align with their individual impacts. Moreover, cutoff walls are more efficient in low-RCH settings, yielding greater relative improvements in FWL development and SWI mitigation per unit wall depth increase.

Seawater intrusion (SWI) in coastal aquifers is influenced by both spatial distributions of hydraulic properties and pumping rates. The heterogeneity of parameters such as hydraulic conductivity (K) may have a significant impact on the vulnerability of these systems to SWI and the sustainability of groundwater supply.In this work vulnerability is assessed in relation to indicators such as: (a) the salt concentration of extracted groundwater (C); and (b) the total dissolved mass (TDM) of salt in the aquifer. This study delves into a modified version of the classical two-dimensional Henry's problem, featuring a single pumping well situated in proximity of the coastline. The well pumping rates are expressed as fractions of the total flow rate entering the aquifer from the inland boundary. The fraction range from a minimum of zero (no pumping) to a maximum of five.To investigate the impact of aquifer heterogeneity a series of stochastic simulations are conducted using the popular variable density flow model SEAWAT. Heterogeneity in the K spatial distribution is modelled as a geostatistical log-normal process characterized by an exponential covariance function, with variance values ranging from 0.25 to 1.0, horizontal correlation scales from 10 m up to 2000 m, and a single vertical correlation scale of 10 m. This approach allows for investigating the effects of the K heterogeneity, the layering features of the aquifer system, and the intensity of groundwater pumping on C and TDM.A detailed examination of model results reveals several interesting outcomes. Most notably, the TDM indicator is rather sensitive to the K heterogeneity, whereas the C indicator is much less affected by it. In terms of TDM, selected cases are singled out and discussed. In general, lower K values exhibit minimal SWI even with large pumpage, whereas high K values lead to pronounced SWI even at low pumping. Increased variance and horizontal correlation correspond to varied SWI behaviour. The TDM spread remains generally low due to relatively low variance. With an increase in horizontal correlation, the spread becomes more pronounced for low pumping rates and less pronounced for large pumping rates.

Sea water intrusion (SWI) simulators are essential tools to assist the sustainable management of coastal aquifers. These simulators require the solution of coupled variable‐density partial differential equations (PDEs), which reproduce the processes of groundwater flow and dissolved salt transport. The solution of these PDEs is typically addressed numerically with the use of density‐dependent flow simulators, which are computationally intensive in most practical applications. To this end, model surrogates are generally developed as substitutes for full‐scale aquifer models to trade off accuracy in exchange for computational efficiency. Surrogates represent an attractive option to support groundwater management situations in which fast simulators are required to evaluate large sets of alternative pumping strategies. Reduced‐order models, a sub‐category of surrogate models, are based on the original model equations and may provide quite accurate results at a small fraction of computational cost. In this study, a variable‐density flow reduced‐order model based on proper orthogonal decomposition (POD) and utilizing a fully coupled flow and solute‐transport model is implemented with a finite‐difference (FD) approach for simulating SWI in coastal aquifers. The accuracy and computational efficiency of the FD‐POD approach for both homogeneous and—more realistic—heterogeneous systems are investigated using test cases based on the classic Henry's problem (Henry 1964). The findings demonstrate that the combined FD‐POD approach is effective in terms of both accuracy and computational gain and can accommodate the output of the most popular variable‐density flow models, such as those from USGS's MODFLOW family.

In groundwater pumping optimization (GPO), offline-trained data-driven surrogates can be used to replace numerical-intensive simulators in order to save computing time. The traditional offline training approach involves building surrogates prior to optimization, fitting training datasets that cover the input space uniformly or randomly, which can prove inefficient due to the potential oversampling of low-gradient areas and under-sampling of high-gradient areas. This study proposes an offline machine-learning (ML) algorithm that ranks candidate training points by scoring them based on their distance to the closest training point and on the local gradient of the surrogate estimate and then choosing the highest-rank point. This method is applied to develop surrogates for solving a two-objective GPO problem formulated on a three-dimensional (3D) island aquifer, using hydrogeological conditions representative of San Salvador Island, Bahamas. The objectives are to minimise the supply cost (f_OC) resulting from groundwater pumping and desalination and maximise fresh groundwater supply (Q_p), subject to constraints on seawater intrusion (SWI) control expressed in terms of aquifer drawdown Δs at pumping locations and aquifer salt mass increase ΔSM. Gaussian Process (GP) is the technique applied to construct surrogates of objectives and constraints, alongside the estimation of uncertainties. Using GP models, it is possible to estimate the probability of “Pareto optimality” for each pumping scheme by Monte Carlo simulation. Pareto optimal pumping schemes (POPS) are then characterized by a probability of occurrence, which can be verified by numerical simulation. The GP training strategy's effectiveness in generating POPS is compared to traditional training approaches, showing that such a strategy can efficiently identify reliable POPS.