Ground water最新文献

Mechanical dispersion is driven by a variance in velocity rather than by the concentration gradient in the classical Fickian model. The groundwater community needs a theoretical development for this that offers a practical way to implement it (Konikow 2025). The method of Advective Transport Phenomena (De Lange 2020) describes mechanical dispersion based on the spread of water particles generated at sub-model scale by advective flow through zones with conductivity different from that of the overall aquifer, leading to a new parameter in the dispersive mass flux which is added to the advective mass flux computed at model scale similar to the existing approach in numerical modeling. The new parameter, called dispersive volume shift, is determined only by the traveled distance and the aquifer heterogeneity described by the horizontal and the vertical characteristic length and the log conductivity variance. The dispersive mass flux combines the dispersive volume shift and the concentration difference which is proportional to the traveled distance per time step. Using a spreadsheet model, the longitudinal concentration distribution in a traveling plume is simulated in a homogeneous aquifer and in a heterogeneous aquifer. The latter case shows asymmetry in the plume growth which is not produced by a classical Fickian model. Developments are still needed for application in general numerical modeling.

In the past decade the groundwater modeling industry has trended toward more computationally intensive methods that necessarily require more parallel computing power due to the number of model runs required for these methods. Groundwater modeling that requires many parallel model runs is often limited by numerical burden or by the modeler's access to computational resources. Over the last 15 years the evolution of the cloud in accelerating groundwater model solutions has progressed; however, there are no apparent literature reviews of MODFLOW and PEST cloud implementation, specifically with regards to open-source and efficient scalable solutions. Here we describe infrastructure as code used to develop the architecture for running PEST++ in parallel on the cloud using Docker containers and open-source software to allow simple and repeatable cloud execution. The architecture utilizes Amazon Web Services and Terraform to facilitate cloud deployment and monitoring. A publicly available MODFLOW-6 model was used to evaluate parallel performance locally and in the cloud. Local model runs were found to have a linear 12 s increase in model run time per agent on a typical office computer compared to the cloud implementation's 0.02 s per model, indicating near perfect scaling even at up to 200 concurrent model runs. A consulting groundwater model was calibrated with the cloud infrastructure, which enabled acceleration of project completion at minimal cost.

The N₂/Ar method is valuable for studying legacy nitrate and denitrification progress in groundwater systems. It uses dissolved N₂ and Ar concentrations to calculate the amount of N₂ originating from denitrification (excess-N₂). Successfully applying the method requires accurate values of N₂ and Ar concentrations. Therefore, avoiding degassing and atmospheric contamination during groundwater sampling is crucial for reliable results. In this study, we focus on the effect of sampling devices on N₂, Ar, and the resulting excess-N₂ concentrations. To evaluate this effect over a wide concentration range, we sampled 14 observation wells. One sample was collected using a submersible pump and another using a bladder pump. Furthermore, we collected multiple samples with both pumps at a fifteenth site to assess reproducibility. Additionally, we used a point-source bailer for sampling at this site. The major ion concentrations show that the sampling device does not significantly influence the sample chemistry. In contrast, the measured N₂, Ar, and calculated excess-N₂ concentrations significantly differ between the sampling devices. Overall, the samples collected with the submersible pump show the highest N₂ and Ar concentrations, resulting in the highest excess-N₂ concentrations. N₂ and Ar concentrations of the bladder pump samples are lower, resulting in lower excess-N₂ concentrations. The bailer samples show lower N₂ but similar Ar concentrations to the submersible pump samples, leading to the lowest excess-N₂ concentrations. We conclude that a submersible pump is practical and suitable for collecting groundwater samples to assess denitrification by the N₂/Ar method.

Regulatory agencies in humid temperate environments rely on timely evaluations of streamflow depletion and drawdown to protect aquatic ecosystems and existing water users. Numerical models offer detailed insights, but their complexity and time demands often preclude their practical use in rapid decision-making. We present pycap-dss, an open-source Python package that implements a suite of analytical solutions for estimating streamflow depletion and drawdown. The tool supports superposition of multiple wells and time-varying pumping, enabling cumulative impact assessments in situations with multiple wells and streams. The software is modular and extensible, allowing users to interchange solutions or add new analytical methods. A YAML-based configuration supports batch processing of multiple wells, and an optional AnalysisProject class facilitates integration with regulatory workflows. Rigorous unit and regression testing ensures computational reliability, and continuous integration supports ongoing development. We demonstrate deterministic examples of drawdown where multiple solutions are readily compared and streamflow depletion with multiple wells in the Central Sands region of Wisconsin. We also show the value of Monte Carlo analyses of streamflow depletion in the same Central Sands example, leveraging computational efficiency to evaluate the uncertainty of individual and cumulative streamflow depletion calculations from over 200 high-capacity wells.

Many public supply wells (PSWs) fail because their water chemistry does not meet regulatory standards, despite pilot hole water quality testing suggesting compliance. This is partly attributed to conventional testing that focuses on the mid-section of permeable zones, excluding low-permeability units or aquitards. The main goal is to prove yield, so groundwater is sampled within the tested interval for efficiency. Clay boundaries are typically excluded from zone testing because of low expected yields, but they may harbor elevated concentrations of constituents of concern. Well discharge concentrations may thus be non-compliant due to the blend of groundwater from permeable, high-yield zones and less permeable, elevated concentration zones. We evaluated flow and chemistry across the screens of 143 wells in California and Nevada, identifying the screen intervals with maximum arsenic, iron, manganese, and nitrate concentrations. We examined the relationship between sediment type, flow contribution, and maximum concentrations, focusing on the influence of aquitard boundaries and interbedded sequences on geochemical outcomes. Maximum concentrations occurred mostly (73-84%) in well screens associated with interbedded or coarse sediments with an aquitard boundary. Intervals with aquitard boundaries had higher arsenic concentrations (p = 0.02). In non-compliant wells, 64-69% of the maximum metal concentrations were sourced from fine-grained and interbedded sediments, warranting their inclusion in water quality zone testing. Approaches that may provide the geochemical resolution to determine the distance between aquitard boundaries and well screens are suggested to minimize the risk of constructing non-compliant PSWs that then require treatment.

Long-term monitoring at landfills and impoundments containing coal combustion products (CCPs) or other industrial wastes is essential for detecting possible leachate releases to groundwater and mapping contamination plumes. This study evaluates a novel, non-invasive geophysical approach-towed time-domain electromagnetic (TEM) surveys-for non-invasive and rapid assessment of groundwater quality near landfills and impoundments that have the potential to release plumes with higher total dissolved solids (TDS) than groundwater. CCPs are one such example where releases can have relatively high sulfate, sodium, and/or calcium concentrations resulting in high TDS and, therefore, high electrical conductivity. This makes electromagnetic (EM) methods suitable for their detection and monitoring. Recent advancements in TEM technology enable efficient subsurface imaging over extensive areas using antennas towed by vehicles on land or boats on water bodies. TEM surveys provide valuable information about overburden thickness, geological structures, lithology, and pore-fluid TDS. We conducted integrated ground-based and waterborne TEM surveys at a CCP complex adjacent to a river in the eastern United States. Despite challenging site conditions, including railroad tracks, high-voltage power lines, and power-generation infrastructure, high-quality TEM data were collected. Over 20 line-km of data were acquired and inverted using laterally constrained two-dimensional (2D) and spatially constrained three-dimensional (3D) inversions. Results successfully delineated geological boundaries and identified conductive anomalies consistent with elevated TDS indicative of potential leachate plumes. Geophysical interpretations agreed well with water-quality data from nearby monitoring wells. This work highlights the effectiveness of integrated ground-based and floating TEM surveys for high-resolution characterization around CCP impoundments.

Groundwater is increasingly needed for water supplies but may have limited utility in some locations because of its salinity. Salinity, often expressed as total dissolved solid (TDS), is frequently estimated using specific conductance (SC) measurements. However, the commonly used proxy (0.65 multiplied by SC to indicate TDS, common in many handheld meters) can result in inaccurate TDS estimates. First, the TDS-SC relationship is not linear over the entire concentration range of groundwater. Furthermore, the TDS (and salinity)-SC relationships vary substantially depending on the major-ion composition. Here we develop a proxy method utilizing SC and major-ion water type to estimate TDS and salinity specifically for groundwaters. Compared to most surface waters, groundwater tends to have a wider range of salinity (fresh to highly saline) and higher concentrations of bedrock-derived solutes such as carbonate ions, silica, and many other ions. The dataset used to develop the proxies includes water chemistry data from 149,059 discrete groundwater samples. The groundwater proxies, which employ nonlinear log-log relations, utilize five water types (HCO₃, Cl, Ca-Mg-SO₄, Na-K-SO₄, and mixed waters), are accurate (median percent difference between TDS and salinity determined using the proxy compared to discrete measurements was <±0.8%) over a wide range of SC (up to 200 mS/cm), rapid, cost-effective, and can be measured on-site.

Solute transport simulators aiming to accurately describe the transport of charged chemical species in porous media need to account for electrostatic coupling effects. Each ion in pore water possesses a specific electric charge and molecular diffusion coefficient, properties that determine their mobility and the overall charge balance of aqueous solutions. Depending on the charge, concentration and aqueous diffusion coefficient, the displacement of an ion in solution influences, and is in turn influenced by, other ions in solution by means of electrostatic interactions. This phenomenon has been studied with experiments and numerical simulations in diffusion-dominated regimes, as well as in advection-dominated flow-through systems, showing that electrostatic coupling effects play a relevant role in the spatiotemporal prediction of ion concentrations. However, there is limited availability of solute transport codes incorporating electrostatic coupling, limiting applications of multispecies ionic transport at different scales. This article elaborates on the topic of electrostatic coupling and presents a methodology for incorporating the effect into multispecies solute transport simulations with MODFLOW. The integration is achieved through the Application Programming Interface of the program (MODFLOW-API). This interface enables the access to concentrations and dispersion coefficients of all species during the simulation, which are necessary to calculate a dispersive correction that effectively incorporates electrostatic coupling into the model. Numerical results demonstrate the effectiveness of the coupling strategy, benchmarking the implementation with previously validated numerical simulators and with experimental data.

Reliable mapping and delineation of contaminant plumes and accurate estimation of contaminant mass discharge (CMD) are critical for groundwater risk assessment and planning of remedial actions at contaminated sites. However, traditional interpolation methods are often challenged by low-density sampling resulting in improper plume delineation. This study introduces a probabilistic censoring method that enhances geostatistical interpolation by incorporating comparably cheap, high-resolution, but semi-quantitative data collected from direct push-probes in the subsurface. The method converts halogen-specific detector signals into binary presence-absence indicators, which are interpolated using indicator kriging to generate a probability field of contaminant distribution. The probability field is then used to censor a spatial concentration field derived from traditional groundwater sampling, retaining interpolated concentration values only in areas where contamination is likely. We apply the method to a site contaminated with chlorinated solvents using two datasets with different sampling densities. Results show that, using our new method, plume fringes became more clearly defined and the total area with low concentrations (<10 μg L^-1) increased by 41-85%. CMD estimates were reduced by 13-18%, while relative uncertainty remained largely unchanged. The method integrates seamlessly with traditional interpolation methods and our censoring workflow can be applied to other forms of direct-push data (e.g., relative permeability). As such, the framework offers a useful method for incorporating semi-quantitative field measurements into concentration interpolation and CMD estimation at contaminated sites.