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Surface meltwater from glaciers and ice sheets contributes significantly to sea-level rise, yet the processes governing its transport and retention within cold firn remain poorly constrained, particularly in multiple dimensions. Here we present a multidimensional, vertically integrated modeling framework for aquifers in cold firn that incorporates phase change and residual trapping of liquid water. This mathematical framework, together with its numerical implementation, extends terrestrial groundwater models to describe aquifers expanding within otherwise cold firn, highlighting the analogous physics governing both systems. We derive semi-analytical solutions for finite-volume aquifers and validate them against numerical simulations and higher-fidelity model results. These solutions elucidate key features of meltwater dynamics and provide benchmarks for firn hydrologic models. We further demonstrate the three-dimensional expansion of an aquifer in cold, heterogeneous firn. Both the semi-analytical and numerical results show that lateral aquifer propagation slows at lower initial firn temperatures due to porosity reduction and associated loss of liquid water from freezing. Overall,

Memory stranding wastes 25-35% of installed DRAM in production cloud clusters. Memory pooling over CXL and RDMA offers a remedy, but neither technology alone suffices: CXL provides low-latency, load/store-transparent access limited to a pod, while RDMA provides cluster-wide reach at higher latency with software overhead. A hierarchical architecture combining both tiers is the practical path forward, yet remains unexplored for MicroVM-based serverless computing, where snapshot restore latency is the dominant cold-start bottleneck. We present Aquifer, the first system to serve MicroVM snapshots from a hierarchical CXL+RDMA memory pool. A characterization of snapshot images reveals that the vast majority of pages are either zero or cold, enabling a hotness-based snapshot format that eliminates zero pages and places only the hot working set in the CXL pool while storing cold pages in the RDMA pool. Sharing these snapshots across hosts on CXL 2.0 multi-headed devices, which lack hardware cache coherence, requires Aquifer's ownership-based coherence protocol to ensure correctness. Finally, Aquifer uses a copy-based page serving mechanism pre-installs hot pages from CXL memory before Micr

The combined effect of tidal forcing and aquifer heterogeneity leads to intricate transport patterns in coastal aquifers that impact both on solute residence times and mixing dynamics. We study these patterns through detailed numerical simulations of density-dependent flow and transport in a three-dimensional heterogeneous coastal aquifer under tidal forcing. Advective particle tracking from both the freshwater and seawater domains reveals the formation of chaotic and periodic orbits in the freshwater-saltwater transition zone that may persistently trap contaminants. We find that increasing heterogeneity results in increased trapping, but also increased mixing entropy, which suggests that the chaotic orbits enhance mixing between contaminants from the freshwater and seawater domains. These findings highlight on the one hand, the long-term contamination risks of coastal aquifers through trapping, and on the other hand, the creation of hotspots for chemical and biological reactions through chaotic mixing in the transition zone.

A small phreatic sand dune aquifer lies along the shore of Haifa Bay. It has been exploited for its freshwater resources since the 1930s. During this time the salinity has increased continuously, partly by seawater intrusion due to overpumping. The chemistry of the young aquifer water is laterally variable and is characterized by excess SO$_4^{2-}$, high $Sr^{2+}$ concentrations above that of modern seawater, high alkalinity, and markedly enriched $δ^{13}C_{DIC}$ values. Acidic winter rains, formed from $SO_x$ and $NO_x$ gaseous emissions from a nearby power station, leach the dry deposition that accumulated across the dune surface during the dry summers. The acidity also partially dissolves the aragonite sea shells in the dune sands, remnants of a previous marine transgression. As a consequence, this adds $Sr^{2+}$, $Ca^{2+}$ excess, and alkalinity, while leading to enriched $δ^{13}C_{DIC}$ values, particularly during the winter, at which time the radiocarbon activity in the DIC is observed to decrease.

The thermal dynamics and hydrology of active layer soils and supra-permafrost aquifers determine the fate of the vast pool of carbon that they hold. In permafrost watersheds of Arctic Alaska, air temperature has warmed by up to 3.5 °C and snowfall has increased by up to ~40 mm from 1981 to 2020. How these changes impact the seasonal to decadal hydrological activity of the carbon-rich aquifers is mostly unknown. Observation-informed thermal hydrology modeling of a hillslope drained by a headwater stream (Imnavait Creek) within continuous permafrost showed profound changes from 1981 to 2020. Warmer summer temperatures deepened annual thaw depths. Steadily warming winter air temperatures, heavier snowfall, and stored energy from summer increased annual water outflow from the hillslope aquifer to the stream, warmed soil temperatures, and expanded and prolonged zero-curtain (stable at 0 °C) zones. In 2017-2018, zero-curtain areas with liquid water persisted through winter. Our findings reveal that both summer and winter warming drive year-round aquifer dynamics, creating conditions that amplify the permafrost-carbon-climate feedback.

In coastal volcanic aquifers, the reliability of freshwater seawater-exchange simulations are governed by accuracy of the conceptual groundwater model (CGM). The traditional CGMs are constructed by qualitatively combining independent hydrogeophysical features, limiting their ability to capture the complexity of volcanic terrains. To integrate these disparate, sparse, and imbalanced features, we propose an AI-assisted workflow. First, the self-organizing map (SOM) is applied to estimate a deterministic set of transdisciplinary features called the reference model. Second, generative algorithms are applied to the reference model and empirical distributions constructed to obtain sets of stochastic point clouds called the site model. Data quality metrics identify the preferred generative algorithm whose set of stochastic features are mapped using SOM to the groundwater model grid and assigned as the stochastic CGM. The proposed algorithm is applied to extremely imbalanced multiclass features and multiple discrete numerical features observed at the Halawa-Moanalua aquifer, Oahu, Hawaii. At this stie, the Copula Generative Adversarial Network is deemed as the preferred generative algorith

A Jacobian free Newton Krylov (JFNK) method with a globalization scheme is introduced to solve large and complex nonlinear systems of equations that arise in groundwater flow models of multi-layer aquifer systems. We explore the advantages of the JFNK method relative to the Newton-Krylov (NK) method and identify the circumstances in which the JFNK method demonstrates computing efficiency. We perform the validation and efficiency of the JFNK method on various test cases involving an unconfined single-layer aquifer and a two-layer aquifer with both confined and unconfined conditions. The results are validated by the NK method. The JFNK method is incorporated in Integrated Water Flow Model (IWFM), an integrated hydrologic model developed and maintained by California Department of Water Resources. We examine the determinacy of the JFNK's adaptability on practical models such as the California Central Valley Groundwater-Surface Water Simulation Model (C2VSim).

Analytical and semi-analytical models for stream depletion with transient stream stage drawdown induced by groundwater pumping are developed to address a deficiency in existing models, namely, the use of a fixed stream stage condition at the stream-aquifer interface. Field data are presented to demonstrate that stream stage drawdown does indeed occur in response to groundwater pumping near aquifer connected streams. A model that predicts stream depletion with transient stream drawdown is developed, based on stream channel mass conservation and finite stream channel storage. The resulting models are shown to reduce to existing fixed-stage models in the limit as stream channel storage becomes infinitely large, and to the confined aquifer flow with a no-flow boundary at the streambed in the limit as stream storage becomes vanishingly small. The model is applied to field measurements of aquifer and stream drawdown, giving estimates of aquifer hydraulic parameters, streambed conductance and a measure of stream channel storage. The results of the modeling and data analysis presented herein have implications for sustainable groundwater management.

This study analyzes water quality dynamics and aquifer recharge through irrigated agriculture, contributing to the literature on Managed Aquifer Recharge (MAR) amidst growing water scarcity. We develop two optimal control models-- a linear and a non-linear extension of (Martin and Stahn, 2013) --that incorporate the impact of fertilizers on aquifer water quality, distinguishing between organic and conventional farming practices. The linear model applies a constant rebate mechanism, whereas the non-linear model employs a concave rebate scheme. Our results show that, depending on climate change scenarios, fertilizer-induced food price discounts, and pollution levels, a socially optimal equilibrium in fertilizer use can be attained. Policy implications are discussed, emphasizing the trade-off between environmental sustainability and social welfare.

Aquifer thermal energy storages (ATES) represent groundwater saturated aquifers that store thermal energy in the form of heated or cooled groundwater. Combining two ATES, one can harness excess thermal energy from summer (heat) and winter (cold) to support the building's heating, ventilation, and air conditioning (HVAC) technology. In general, a dynamic operation of ATES throughout the year is beneficial to avoid using fossil fuel-based HVAC technology and maximize the ``green use'' of ATES. Model predictive control (MPC) with an appropriate system model may become a crucial control approach for ATES systems. Consequently, the MPC model should reflect spatial temperature profiles around ATES' boreholes to predict extracted groundwater temperatures accurately. However, meaningful predictions require the estimation of the current state of the system, as measurements are usually only at the borehole of the ATES. In control, this is often realized by model-based observers. Still, observing the state of an ATES system is non-trivial, since the model is typically hybrid. We show how to exploit the specific structure of the hybrid ATES model and design an easy-to-solve moving horizon esti

Capillary heterogeneity is increasingly recognized as a first-order control on gas plume migration and trapping in aquifers and storage formations. We show that spatial variability in the water-methane contact angle, determined by mineralogy and salinity, alters capillary entry pressures and migration pathways. Using molecular dynamics simulations, we estimate contact angles on quartz and kaolinite under fresh and saline conditions and incorporate these results into continuum-scale multiphase flow simulations via a contact-angle-informed Leverett J function, mapping wettability directly onto continuum-scale flow properties. Accounting for contact angle heterogeneity affects methane behavior: mobile and residually trapped methane in aquifers decrease by up to 10 percent, while leakage to the atmosphere increases by as much as 20 percent. The magnitude of this effect depends on permeability contrast, leakage rate, salinity, and facies proportions. By coupling molecular-scale wettability to continuum-scale flow and transport, this cross-scale framework provides a physically grounded basis for groundwater protection and risk assessment and yields more reliable emissions estimates. The

An aquifer thermal energy storage (ATES) can mitigate CO2 emissions of heating, ventilation, and air conditioning (HVAC) systems for buildings. In application, an ATES keeps large quantities of thermal energy in groundwater-saturated aquifers. Normally, an ATES system comprises two (one for heat and one for cold) storages and supports the heating and cooling efforts of simultaneously present HVAC system components. This way, the operation and emissions of installed and, usually, fossil fuel-based components are reduced. The control of ATES systems is challenging, and various control schemes, including model predictive control (MPC), have been proposed. In this context, we present a lightweight input-output-data-based autoregressive with exogenous input (ARX) model of the hybrid ATES system dynamics. The ARX model allows the design of an output-based MPC scheme, resulting in an easy-to-solve quadratic program and avoiding challenging state estimations of ground temperatures. A numerical study discusses the accuracy of the ARX predictor and controller performance.

Effective management of pressure communication and interference between concurrent CO$_2$ storage operations is essential for the development of gigaton-scale storage hubs. Coarse models in reservoir simulation offer a simplified representation of the subsurface to efficiently predict pressure distribution. By averaging properties over larger grid blocks, coarsened models significantly reduce computational demands, enabling faster and more manageable simulations. The approach focuses on preserving key physical properties, namely cell connectivity (transmissibilities) and storage capacity (pore volumes). The effectiveness of the coarsened model is demonstrated by applying the improved well location derived from the coarsened model to the full-resolution Troll aquifer model, resulting in improved pressure distribution. The coarsened model enabled the execution of approximately 100,000 simulations over five days using a local server with 144 CPUs, an effort that would have required around seven months using the original model. The coarsening methodology is implemented using pycopm, an open-source tool design to tailor geological models based on industry-standard grid formats, facilita

Aquifer thermal energy storages (ATES) are used to temporally store thermal energy in groundwater saturated aquifers. Typically, two storages are combined, one for heat and one for cold, to support heating and cooling of buildings. This way, the use of classical fossil fuel-based heating, ventilation, and air conditioning can be significantly reduced. Exploiting the benefits of ATES beyond "seasonal" heating in winter and cooling in summer as well as meeting legislative restrictions requires sophisticated control. We propose a tailored model predictive control (MPC) scheme for the sustainable operation of ATES systems, which mainly builds on a novel model and objective function. The new approach leads to a mixed-integer quadratic program. Its performance is evaluated on real data from an ATES system in Belgium.

Process-based hydrologic models are invaluable tools for understanding the terrestrial water cycle and addressing modern water resources problems. However, many hydrologic models are computationally expensive and, depending on the resolution and scale, simulations can take on the order of hours to days to complete. While techniques such as uncertainty quantification and optimization have become valuable tools for supporting management decisions, these analyses typically require hundreds of model simulations, which are too computationally expensive to perform with a process-based hydrologic model. To address this gap, we assess a hybrid modeling workflow in which a process-based model is used to generate an initial set of simulations and a machine learning (ML) surrogate model is then trained to perform the remaining simulations required for downstream analysis. As a case study, we apply this workflow to simulations of variably saturated groundwater flow at a prospective managed aquifer recharge site. We compare the accuracy and computational efficiency of several ML architectures, including deep convolutional networks, recurrent neural networks, vision transformers, and networks wi

In recent years, water needs increased, driven by climate change and world population growth. In this context, we study groundwater flow in the vadose zone of Beauce aquifer (O-ZNS site, France). This lacustrine limestone vadose zone is characterized by multi-scale heterogeneities. They are defined by strongly various pore structures. This leads to uncertainties for reservoir properties prediction using geophysical methods which impacts reservoir models for flow simulations.In this study, we combined microstructure description and petrophysical analysis in order to model and predict reservoir properties based on different limestones facies and to infer the influence of weathering/fracturing on both acoustics and electrical properties.A total of 16 samples from these facies were cored and characterized by their porosity, permeability, acoustic velocities, complex electrical properties and microstructure analysis.Based on our multi-method approach, we demonstrated the influence of rock structure on reservoir properties prediction and modelling. Petrophysical and microstructure characterization have highlighted two main facies (microporous and homogenous facies and macroporous and het

Analytic and semi-analytic solution are often used by researchers and practicioners to estimate aquifer parameters from unconfined aquifer pumping tests. The non-linearities associated with unconfined (i.e., water table) aquifer tests makes their analysis more complex than confined tests. Although analytical solutions for unconfined flow began in the mid-1800s with Dupuit, Thiem was possibly the first to use them to estimate aquifer parameters from pumping tests in the early 1900s. In the 1950s, Boulton developed the first transient well test solution specialized to unconfined flow. By the 1970s Neuman had developed solutions considering both primary transient storage mechanisms (confined storage and delayed yield) without non-physical fitting parameters. In the last decade, research into developing unconfined aquifer test solutions has mostly focused on explicitly coupling the aquifer with the linearized vadose zone. Despite the many advanced solution methods available, there still exists a need for realism to accurately simulate real-world aquifer tests.

The rapid decline in groundwater around the world poses a significant challenge to sustainable agriculture. To address this issue, agricultural managed aquifer recharge (Ag-MAR) is proposed to recharge the aquifer by artificially flooding agricultural lands using surface water. Ag-MAR requires a carefully selected flooding schedule to avoid affecting the oxygen absorption of crop roots. However, current Ag-MAR scheduling does not take into account complex environmental factors such as weather and soil oxygen, resulting in crop damage and insufficient recharging amounts. This paper proposes MARLP, the first end-to-end data-driven control system for Ag-MAR. We first formulate Ag-MAR as an optimization problem. To that end, we analyze four-year in-field datasets, which reveal the multi-periodicity feature of the soil oxygen level trends and the opportunity to use external weather forecasts and flooding proposals as exogenous clues for soil oxygen prediction. Then, we design a two-stage forecasting framework. In the first stage, it extracts both the cross-variate dependency and the periodic patterns from historical data to conduct preliminary forecasting. In the second stage, it uses w

Underground hydrogen storage in saline aquifers is a potential solution for seasonal renewable energy storage. Among potential storage sites, facilities used for underground natural gas storage have advantages, including well-characterized cyclical injection-withdrawal behavior and partially reusable infrastructure. However, the differences between hydrogen-brine and natural gas-brine flow, particularly through fractures in the reservoir and the sealing caprock, remain unclear due to the complexity of two-phase flow. Therefore, we investigate fracture relative permeability for hydrogen versus methane (natural gas) and nitrogen (commonly used in laboratories). Steady-state relative permeability experiments were conducted at 10 MPa on fractured carbonate rock from the Loenhout natural gas storage in Belgium, where gas flows through {\textmu}m-to-mm scale fractures. Our results reveal that the hydrogen exhibits similar relative permeability curves to methane, but both are significantly lower than those measured for nitrogen. This implies that nitrogen cannot reliably serve as a proxy for hydrogen at typical reservoir pressures. The low relative permeabilities for hydrogen and methane