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Groundwater contamination induced by anthropogenic activities has long been a global issue. Characterizing and modeling contaminant transport processes is crucial to groundwater protection and management. However, challenges still exist in process complexity, data constraint, and computational cost. In the era of big data, the growth of machine learning has led to new opportunities in studying contaminant transport in groundwater systems. In this work, we introduce a new attention‐based graph neural network (aGNN) for modeling contaminant transport with limited monitoring data and quantifying causal connections between contaminant sources (drivers) and their spreading (outcomes). In five synthetic case studies that involve varying monitoring networks in heterogeneous aquifers, aGNN is shown to outperform LSTM‐based (long‐short term memory) and CNN‐ based (convolutional neural network) methods in multistep predictions (i.e., transductive learning). It also demonstrates a high level of applicability in inferring observations for unmonitored sites (i.e., inductive learning). Furthermore, an explanatory analysis based on aGNN quantifies the influence of each contaminant source, which has been validated by a physics‐based model with consistent outcomes with an R2 value exceeding 92%. The major advantage of aGNN is that it not only has a high level of predictive power in multiple scenario evaluations but also substantially reduces computational cost. Overall, this study shows that aGNN is efficient and robust for highly nonlinear spatiotemporal learning in subsurface contaminant transport, and provides a promising tool for groundwater management involving contaminant source attribution. Plain Language Summary: Groundwater contamination caused by human activities is a longstanding global challenge. Accurately characterizing and modeling the movement of contaminants is crucial for the protection and management of groundwater resources. However, the complexity of the processes, limitations in data availability, and high computational demands pose significant challenges. In the age of big data, machine learning offers new avenues for exploring contaminant transport in groundwater. In this study, we introduce a novel machine learning model called an attention‐based graph neural network (aGNN) designed to model contaminant transport with sparse monitoring data and to analyze the causal relationships between contaminant sources and observed concentrations at specific locations. We conducted five synthetic case studies across diverse aquifer systems with varying monitoring setups, where aGNN demonstrated superior performance over models based on other approaches. It also proved highly capable of making inferences about pollution levels at unmonitored sites. Moreover, an explanatory analysis using aGNN effectively quantified the impact of each contaminant source, with results validated by a physics‐based model. Overall, this study establishes aGNN as an efficient and robust method for complex spatiotemporal learning in subsurface contaminant transport, making it a valuable tool for groundwater management and contaminant source identification. Key Points: A novel graph‐based deep learning method is proposed for modeling contaminant transport constrained by monitoring dataThe proposed model quantifies the contribution of each potential contaminant source to the observed concentration at an arbitrary locationThe deep learning method substantially reduces the computational cost compared with a physics‐based contaminant transport model [ABSTRACT FROM AUTHOR]

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Regional nitrate contamination in groundwater is a management challenge involving multisector benefits. There is always conflict between restricting anthropogenic activities to protect groundwater quality and prioritizing economic development, especially in productive agriculture dominated areas. To mitigate the nitrate contamination in groundwater, it is necessary to develop management alternatives that simultaneously support environmental protection and sustainable economic development. A regional transport modeling framework is applied to evaluate nitrate fate and transport in the Dagu Aquifer, a shallow sandy aquifer that supplies drinking water and irrigation water for a thriving agricultural economy in Shandong Province in east coastal China. The aquifer supports intensive high‐value vegetable farms and nitrate contamination is extensive. Detailed land‐use information and fertilizer use data were compiled and statistical approaches were employed to analyze nitrogen source loadings and the spatiotemporal distribution of nitrate in groundwater to support model construction and calibration. The evaluations reveal that the spatial distribution and temporal trends of nitrate contamination in the Dagu Aquifer are driven by intensive fertilization and vertical water exchange, the dominant flow pattern derived from intensive agricultural pumping and irrigation. The modeling framework is employed to assess the effectiveness of potentially applicable management alternatives. The predictive results provide quantitative comparisons for the trend and extent of groundwater quality mitigation under each scenario. Recommendations are made for measures that can both improve groundwater quality and sustain productive agricultural development. Article impact statement: Assessed nitrogen management measures to balance groundwater protection and agricultural sustainability. [ABSTRACT FROM AUTHOR]

The study describes the hydrogeological setting of the Pearl River Delta, a sub-tropical area of southern China encompassing the metropolises of Guangzhou, Shenzhen, Hong Kong and Macau. In the last 40 years, a booming economy and a population of about 60 million has increased water demand satisfied by a huge system of dams and reservoirs. Aquifers in the studied area are underutilized and only a few recent studies have addressed hydrogeological characterization at a local scale. Understanding groundwater dynamics of the Pearl River Delta is important for developing additional water supplies, understanding and mitigating groundwater pollution, and for implementing 'Sponge City' concepts. Via a collection of data from literature and field surveys, the hydrogeological setting of the area is synthetized and represented through thematic maps, cross sections and a hydro-stratigraphic column. Hydrogeological conceptual models are developed that describe the groundwater dynamics in urban and rural areas within the Pearl River Delta. [ABSTRACT FROM AUTHOR]

Shenzhen is the major financial and high-tech center in southern China. The megacity has grown rapidly in the last 40 years with the population increasing from about 30,000 in 1979 to 20 million in 2016. The study area (2,015 km2) is about 42% urban and 58% undeveloped land. The rapid development of the megacity has resulted in severe degradation of the groundwater and surface-water resources and has created a nearly insatiable demand for water, with an average consumption of 2000 × 106 m3/year. Groundwater is an important component of the baseflow of the many streams in the area and is used for potable water supply and irrigation in some of the rural parts of the municipality. This study develops a conceptual model and quantitative framework for assessing the groundwater resources of Shenzhen. The groundwater system consists of shallow aquifers of alluvium and weathered bedrock overlying low permeability igneous and sedimentary rocks. The complex geologic setting was conceptualized as a block structure with blocks bounded by high-angle faults. The water budget in Shenzhen was quantified. The estimated average groundwater discharge is about 12% of annual precipitation. The study provides a starting point to investigate how a megacity such as Shenzhen should manage and protect its groundwater as a strategic resource and environmental asset. It is also a basic management tool for analyzing and contributing to urban drainage concepts such as the "sponge city". [ABSTRACT FROM AUTHOR]

With rivers in critical regions already exploited to capacity throughout the world and groundwater overdraft as well as large-scale contamination occurring in many areas, we have entered an era in which multiple simultaneous stresses will drive water management. Increasingly, groundwater resources are taking a more prominent role in providing freshwater supplies. We discuss the competing fresh groundwater needs for human consumption, food production, energy, and the environment, as well as physical hazards, and conflicts due to transboundary overexploitation. During the past 50 years, groundwater management modeling has focused on combining simulation with optimization methods to inspect important problems ranging from contaminant remediation to agricultural irrigation management. The compound challenges now faced by water planners require a new generation of aquifer management models that address the broad impacts of global change on aquifer storage and depletion trajectory management, land subsidence, groundwater-dependent ecosystems, seawater intrusion, anthropogenic and geogenic contamination, supply vulnerability, and long-term sustainability. The scope of research efforts is only beginning to address complex interactions using multiagent system models that are not readily formulated as optimization problems and that consider a suite of human behavioral responses. [ABSTRACT FROM AUTHOR]

Groundwater vulnerability is often regarded as the resistance of aquifers to pollutions, which is in fact the groundwater environment vulnerability. Similarly the renewable capacity of groundwater system can be regarded as the indicator for groundwater resources vulnerability. In this paper, the concept of groundwater vulnerability is extended to include both the groundwater environment vulnerability and groundwater resources vulnerability, and the extended overall groundwater vulnerability is assessed by examining the solute transport process from ground surface to the water table (for groundwater environment vulnerability), and evaluating the renewable capacity of groundwater system (for groundwater resources vulnerability). For this case study in Beijing Plain, a 1D-modeling, 2D-mapping model is constructed in HYDRUS to simulate the solute transport process through vadose zone. The transit times and solute concentrations at the water table are selected as the indicators for groundwater environment vulnerability. Meanwhile, a 3D groundwater age model in MODFLOW/MT3DMS is employed to model the age distribution in saturated zone, and the modeled ages are taken as the indicators for groundwater resources vulnerability. These two models are coupled together by exchanging their vertical infiltrations and water table elevations. Overall vulnerability is finally assessed by taking all the indicators into account. The result suggests the overall vulnerability can finely represent the synthetic impact of solute transport characteristics (groundwater environment vulnerability in vadose zone) and groundwater system renewability (groundwater resources vulnerability in saturated zone). The most vulnerable regions of Beijing Plain are mostly in agricultural areas, the medium vulnerable areas mostly appear at pumping sites, and the least vulnerable areas are mostly distributed in recharge regions. [ABSTRACT FROM AUTHOR]

Numerical groundwater modeling is an effective tool to guide water resources management and explore complex groundwater-dependent ecosystems in arid regions. In the Heihe River Basin (HRB), China's second largest inland river basin located in arid northwest China, a series of groundwater flow models have been developed for those purposes over the past 20 years. These models have elucidated the characteristics of groundwater flow systems and provided the scientific basis for a more sustainable management of groundwater resources and ecosystem services. The first part of this paper presents an overview of previous groundwater modeling studies and key lessons learned based on seven different groundwater models in the middle and lower HRB at sub-basin scales. The second part reviews the rationale for development of a regional basin-scale groundwater flow model that unifies previous sub-basin models. In addition, this paper discusses the opportunities and challenges in developing a regional groundwater flow model in an arid river basin such as the HRB. [ABSTRACT FROM AUTHOR]

Fort Morgan Peninsula is an attached portion of a dynamic barrier complex in the northern Gulf of Mexico and is a large tourist area that brings in a significant amount of revenue for Alabama. Many of the hotels and tourist attractions depend on the groundwater as their water supply. The over-withdrawal of groundwater and saltwater intrustion will have a negative impact on the ecology, tourism and economy if groundwater resources are not properly monitored and managed. In this study a calibrated groundwater flow model was used to analyze the sustainability of groundwater resources at Fort Morgan Peninsula. Detailed flow budgets were prepared to check the various components of inflow and outflow under different water use and climatic conditions. The results indicated the locations where groundwater was over-pumped and subjected to saltwater intrusion, or will be subjected to saltwater intrusion under a range of projected water use and climatic conditions. [ABSTRACT FROM AUTHOR]

The article discusses various reports published within the issue including the scientific challenges involved in creating efficient groundwater models, the capacities of the reactive transport code PHT3D and the use of MT3DMS to simulate the transfer of heat.

• Warmer water injection, oscillating tides, and MAR operations collectively affect the efficiency and sustainability of MAR. • Warmer water injection reduces freshwater storage and recovery, as well as extracted water quality. • Starting extraction with a receding tide could extend the duration of extracting water with lower saline concentration. • Intermittent injection-extraction operation could mitigate the efficiency decrease caused by the warmer water injection. • This study provides insights into water management in artificial island with extensive industrial activities. Storing and utilizing freshwater in coastal aquifers with managed aquifer recharge (MAR) presents significant challenges, particularly in small island settings where seawater intrusion is a major source of groundwater salinization. Existing studies usually evaluate density-dependent flow under isothermal condition, which neglects the potential impact of temperature on fluid density. To fill the knowledge gap, we performed both laboratory experiments and numerical modeling to investigate the impact of warmer water injection on freshwater storage and extracted water quality for island aquifer. It is found that warmer water (70 °C) injection compromise the "barrier effect" achieved by normal water injection, resulting in a reduced ability to prevent coastal seawater intrusion by, creating an upward hydraulic gradient beneath the injection well. In addition, warm water injection result in a 5 % decrease in freshwater storage capacity for island aquifer. However, by employing a combination of receding tide cycles and intermittent injection-extraction operations, the duration of lowered saline concentration within the extracted water can be extended by approximately 10 % with an 11 % reduction in the overall extracted saline concentration. This study provides valuable insights into the influence of warmer water injection on coastal aquifer quality. The findings from both the laboratory experiments and numerical simulations enhance the understanding of thermal density-dependent dynamics of coastal aquifers, offering valuable guidance for effective freshwater storage and usage in island settings. [ABSTRACT FROM AUTHOR]

[Display omitted] • An improved groundwater solute transport model is developed using multipoint flux approximation. • The new model can use arbitrary shaped polygons to discretize aquifer systems. • The new model can well represent groundwater solute transport processes. • This new model outperforms conventional groundwater solute transport model in aquifers with complex shaped boundary. Groundwater solute transport models are critical for simulating subsurface contaminant processes, guiding policy making for groundwater management, and pollution remediation. In this study, we develop an improved groundwater solute transport model which uses arbitrary-shaped polygons for spatial discretization. This allows for the efficient simulation of solutes in complex boundary aquifer systems. The governing equation is discretized in space using the finite volume method to ensure flux conservation both locally and globally. The dispersion term is discretized by the multipoint flux approximation (MPFA) method which is a finite volume method that is suitable on arbitrary polygon grids. A total variation diminishing (TVD) scheme is used to control numerical oscillation in the advection term. The functionality and performance of the new model are demonstrated by comparing the simulated results between our model and MT3DMS model in five case studies. The comparisons show that the new model can well represent the solute transport processes. In a real-world watershed with complex-shaped boundaries, the new model outperforms the conventional groundwater solute transport model with smaller computed root-mean-square errors. These modeling results suggest that our model can provide robust modeling solutions for simulating groundwater solute transport processes, especially in aquifer systems with complex shaped boundaries. Furthermore, our model can provide a more flexible discretization solution for coupling surface water models and groundwater solute transport models. [ABSTRACT FROM AUTHOR]

Daya Bay, a semi-closed bay of the South China Sea, is famous for its aquaculture, agriculture and tourism. Although routine environmental investigations in the bay have been conducted since the early 1980s, evaluations of submarine groundwater discharge (SGD), an important process in exchange between groundwater and coastal seawater, and its environmental impacts have never been reported. In this study, naturally occurring radon isotope ( 222 Rn) was measured continuously at two sites (north-west and middle-east sites) and used as a tracer to estimate SGD and associated nutrient inputs into the bay. The SGD rates estimated based on the 222 Rn mass balance model were, on average, 28.2 cm/d at north-west site and 30.9 cm/d at middle-east site. The large SGD rate at middle-east site may be due to the large tidal amplitude and the sandy component with high permeability in sediments. The SGD-driven nutrient fluxes, which were calculated as the product of SGD flux and the difference of nutrient concentrations between coastal groundwater and seawater, were 3.28 × 10 5 mol/d for dissolved nitrates (NO 3 –N), 5.84 × 10 3 mol/d for dissolved inorganic phosphorous (DIP), and 8.97 × 10 5 mol/d for reactive silicate (Si). These nutrient inputs are comparable to or even higher than those supplied by local rivers. In addition, these SGD-driven nutrients have a nitrogen-phosphorous ratio as high as ∼43, which may significantly affect the ecology of coastal waters and lead to frequent occurrence of harmful algal blooms. [ABSTRACT FROM AUTHOR]

The design of groundwater exploitation schedules with constraints on pumping-induced land subsidence is a computationally intensive task. Physical process-based groundwater flow and land subsidence simulations are high-dimensional, nonlinear, dynamic and computationally demanding, as they require solving large systems of partial differential equations (PDEs). This work is the first application of a parallelized surrogate-based global optimization algorithm to mitigate land subsidence issues by controlling the pumping schedule of multiple groundwater wellfields over space and time. The application was demonstrated in a 6500 km2 region in China, involving a large-scale coupled groundwater flow-land subsidence model that is computationally expensive in terms of computational resources, including runtime and CPU memory for one single evaluation. In addition, the optimization problem contains 50 decision variables and up to 13 constraints, which adds to the computational effort, thus an efficient optimization is required. The results show that parallel DYSOC (dynamic search with surrogate-based constrained optimization) can achieve an approximately 100% parallel efficiency when upscaling computing resources. Compared with two other widely used optimization algorithms, DYSOC is 2–6 times faster, achieving computational cost savings of at least 50%. The findings demonstrate that the integration of surrogate constraints and dynamic search process can aid in the exploration and exploitation of the search space and accelerate the search for optimal solutions to complicated problems. •A new optimization algorithm (DYSOC) is proposed for computationally demanding constraint functions. •DYSOC is the first surrogate-based constrained optimization algorithm for tackling the land subsidence problem. •Parallel DYSOC can achieve the theoretically ideal linear speedup when using multicore processing. •DYSOC reduces the computational cost by over 50% compared with other widely used algorithms in a field application. [ABSTRACT FROM AUTHOR]

• An improved groundwater model is developed using multipoint flux approximation. • The new model uses arbitrary shaped polygons to discretize aquifer systems. • The new model can represent groundwater flow processes well and outperforms conventional groundwater models in aquifers with complex-shaped boundaries. Groundwater models are critical for simulating subsurface hydrological processes and guiding informed policy-making for groundwater management. However, the widely applied groundwater models typically use regular-shaped grids to discretize aquifer systems and require that the directions of the grid edges are aligned with the hydraulic conductivity tensor. Such rigorous requirements for spatial discretization have constrained the models' application in aquifer systems with anisotropic hydrogeological characteristics. To address such limitations, we develop an improved groundwater flow model based on the multipoint flux approximation (MPFA) method in this study. The new model allows us to use arbitrary-shaped polygon grids to discretize aquifer systems and relaxes the rigorous requirement of the alliance between polygon edges and hydraulic conductivity tensor. The functionality and performance of the new model are demonstrated by comparing the output between our model, MODFLOW, and analytical solution in four case studies with various hydrogeological conditions. In a real-world watershed with complex-shaped boundaries, our model outperforms the conventional groundwater model in boundaries. The modeling results show that our model can yield accurate simulation of subsurface hydrological processes in aquifer systems with complex-shaped boundaries. Furthermore, our model can provide a more flexible discretization solution to couple surface water and groundwater model in integrated hydrological model development. [ABSTRACT FROM AUTHOR]

Modeling agriculture-impacted hydrological processes remains a challenge, as information on irrigation activities is often insufficient. This study developed modules for emulating high-resolution irrigation activities and representing water management policies in integrated hydrologic modeling. The new modeling approach was implemented in China's second largest endorheic river basin with intensive irrigation and exemplary environmental flow regulation. Pumping management is found to impact the hydrological regime at the basin scale and modulate the tradeoff between ecological services and agriculture. Limiting the groundwater level decline within 1 m would lead to a 3.9% decrease in cropland evapotranspiration in the middle basin and a 1.5% increase in the environmental flow towards the lower basin. Environmental flow regulation and pumping management have both synergistic and offset effects, reflecting a complex water-agriculture-ecosystem nexus in this basin. This modeling study suggests heterogeneous and dynamic groundwater management policies in water-limited areas and unravels threshold effects in the policies. • A new module for hydrologic models to emulate high-resolution irrigation activities. • A typical tradeoff between ecosystems and agriculture tuned by pumping management. • Diversion regulation and pumping control have both synergistic and offset effects. • Heterogeneous and dynamic groundwater management policies are preferred. • Threshold effects are observed for the groundwater management policy. [ABSTRACT FROM AUTHOR]