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At least 19 records

All sources NASA NTRS DOE OSTI

DOE OSTI2019

Combining a land surface model with groundwater model calibration to assess the impacts of groundwater pumping in a mountainous desert basin

The quantification of recharge and trans-valley underflow is needed in arid regions to estimate the impacts of new water withdrawals on the water table. However, for mountainous desert areas, such estimates are highly challenging, due to data scarcity, heterogeneous soils, and long residence times. Conventional assessment employs isolated groundwater models configured with simplified uniform estimates of recharge. Here, we employed a data-constrained surface-subsurface process model to provide an ensemble of spatially distributed recharge and underflow estimates using perturbed parameters. Then, the Model-Independent Parameter Estimation and Uncertainty Quantification (PEST) package was used to calibrate the aquifer hydraulic conductivity field in MODFLOW for this ensemble and reject implausible recharge values. This novel dual-model approach, broadly applicable to mountainous arid regions, was designed to maximally exploit available data sources. It can assimilate groundwater head observations, reject unrealistic parameters, and narrow the range of estimated drawdowns due to pumping. We applied this approach to the Chuckwalla basin in California, USA to determine natural recharge. Simulated recharge concentrates along alluvial fans at the mountain fronts and ephemeral washes where run-off water infiltrates. If an evenly distributed recharge was employed as in conventional studies, it would result in regional biases in estimated drawdown and larger uncertainty bounds. Here, we also note that the speed of groundwater recovery does not guarantee sustainability: heavy pumping induces large hydraulic gradients that initially recover quickly when pumping is halted, but the system may not ultimately recover to pre-pumping levels.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2017

A Taylor Expansion-Based Adaptive Design Strategy for Global Surrogate Modeling With Applications in Groundwater Modeling

Global sensitivity analysis (GSA) and uncertainty quantification (UQ) for groundwater modeling are challenging because of the model complexity and significant computational requirements. To reduce the massive computational cost, a cheap-to-evaluate surrogate model is usually constructed to approximate and replace the expensive groundwater models in the GSA and UQ. Constructing an accurate surrogate requires actual model simulations on a number of parameter samples. Thus, a robust experimental design strategy is desired to locate informative samples so as to reduce the computational cost in surrogate construction and consequently to improve the efficiency in the GSA and UQ. In this study, we develop a Taylor expansion-based adaptive design (TEAD) that aims to build an accurate global surrogate model with a small training sample size. TEAD defines a novel hybrid score function to search informative samples, and a robust stopping criterion to terminate the sample search that guarantees the resulted approximation errors satisfy the desired accuracy. The good performance of TEAD in building global surrogate models is demonstrated in seven analytical functions with different dimensionality and complexity in comparison to two widely used experimental design methods. The application of the TEAD-based surrogate method in two groundwater models shows that the TEAD design can effectively improve the computational efficiency of GSA and UQ for groundwater modeling.

58 GEOSCIENCES↗

DOE OSTI2019

Model Package Report: Plateau to River Groundwater Model (Version 8.2)

This model package report documents the groundwater flow component of the Plateau to River Groundwater Model (P2R Model), a groundwater flow and contaminant fate and transport (F&T) simulation model used to support remedial activities conducted by CH2M HILL Plateau Remediation Company at the Hanford Site in Washington State. The objective of this model package report is to describe the modeling objectives; conceptualization; model implementation; calibration, sensitivity, and uncertainty; configuration control; limitations; and future model enhancements of the groundwater flow component of the P2R Model.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Model Package Report: Plateau to River Groundwater Model Version 8.3

This model package report documents the groundwater flow component of the Plateau to River Groundwater Model (P2R Model), which is a groundwater flow and contaminant fate and transport (F&T) simulation model used to support remedial activities conducted by CH2M HILL Plateau Remediation Company at the Hanford Site in Washington State. The objective of this report is to describe the modeling objectives, conceptualization, model implementation, calibration, sensitivity, uncertainty, configuration control, limitations, and future model enhancements of the groundwater flow component of the P2R Model.

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NASA NTRS1991

A Martian global groundwater model

A global groundwater flow model was constructed for Mars to study hydrologic response under a variety of scenarios, improving and extending earlier simple cross sectional models. The model is capable of treating both steady state and transient flow as well as permeability that is anisotropic in the horizontal dimensions. A single near surface confining layer may be included (representing in these simulations a coherent permafrost layer). Furthermore, in unconfined flow, locations of complete saturation and seepage are determined. The flow model assumes that groundwater gradients are sufficiently low that DuPuit conditions are satisfied and the flow component perpendicular to the ground surface is negligible. The flow equations were solved using a finite difference method employing 10 deg spacing of latitude and longitude.

Howard, Alan D.↗

DOE OSTI2024

Large-Scale Visualization of 3D Unstructured Groundwater Model Using Cave Automated Virtual Environment

The immersive three-dimensional (3D) virtual reality (VR) visualization of groundwater models allows us to deepen our understanding of aquifer systems and provide better solutions to present groundwater-related problems, such as groundwater recharge, water quality, and sustainability. Visualization assists in accurately developing groundwater models and revealing important subsurface features, including faulting, folding, and unconformity. However, assessing model accuracy poses challenges due to the complexity of geology and groundwater systems. This research demonstrates a workflow to visualize and analyze raw 3D unstructured groundwater model data using an immersive Cave Automated Virtual Environment (CAVE). To visualize the unstructured groundwater model data, the raw dataset is converted into interactive CAVE-compatible formats utilizing a set of tools: ParaView, Blender, and Unity. This enables researchers to immerse themselves in the data, identifying influential patterns and relationships. e resulting insights can inform the development of sophisticated machine-learning models for groundwater level prediction. The CAVE’s immersive capabilities allow intuitive exploration from various perspectives, providing a more holistic understanding of the factors affecting groundwater levels. These insights are crucial to improve predictive models. The CAVE results also facilitate collaborative analysis and have potential applications in training and education. is research demonstrates the value of immersive VR tools such as the CAVE for unraveling intricacies within high-dimensional scientific data to drive real-world forecasting and modeling applications.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Development of a Conditioned System-Level Groundwater Model to Evaluate Long-Term Groundwater Impacts within a Performance Assessment - 20115

A preliminary performance assessment (PA) of single-shell tank Waste Management Area (WMA) A-AX located at the U.S. Department of Energy (DOE)'s Hanford Site in southeastern Washington is being conducted to satisfy the requirements of DOE Order 435.1 [1] as it relates to closure of the single-shell radioactive waste tanks in the WMA A-AX tank farms. A PA assesses the fate, transport, and impacts of radionuclides within a low-level radioactive waste disposal facility in its assumed closure configuration and the subsequent potential doses to humans over a 1,000-year compliance period and a 10,000-year performance evaluation period. The WMA A-AX preliminary PA evaluation is structured around the complementary use of process-level and system-level models to calculate the facility performance against established DOE Order 435.1 [1] performance objectives. Process-level models are those that represent a detailed phenomenological representation of processes of concern in the PA. Process models typically only represent one or a few of the components of the PA, such as groundwater flow and transport, and must be integrated with other modeling elements to perform PA calculations. System-level models are those that are abstracted from the process models, retaining the essential features of the process model, while allowing integration of all aspects of the PA in a single modeling framework. System-level models are often characterized by coarser numerical discretization, lower dimensionality, or other similar simplifications compared to the process-level model. Traditionally, a three-dimensional (3-D) process-level model is utilized primarily to evaluate the long-term impact on groundwater and the potential doses to individuals who consume contaminated groundwater. System-level models are also utilized to evaluate the groundwater pathway in PAs. These models typically have reduced dimensionality (1-D) and are conditioned utilizing flow fields (Darcy fluxes) and moisture content distributions that are abstracted from the process level models. The abstraction approach assures that the flow field in both models is consistent for a specific set of input parameters for flow, differing only in the discretization and dimensionality of the two models. The preliminary WMA A-AX PA incorporates a detailed representation of the geological system and hydraulic properties within the 3-D model STOMP{sup C} numerical code so that the effects of relevant features and processes on water flow and radionuclide transport in the subsurface can be evaluated. The complementary system-level model is developed utilizing the GoldSim{sup C} code to implement a simplified, 1-D equivalent model to represent the groundwater pathway. Contaminant transport through the vadose zone and unconfined aquifer for Tc-99 and I-129 were evaluated in each of the models. Adjustments to the saturated portion of the GoldSim{sup C} 1-D model were required to mimic the dispersion effect captured with the 3-D STOMP{sup C} model. Once this conditioning was conducted, highly similar results for the transport of Tc-99 and I-129 were achieved at the point of calculation, located 100 m downgradient from the WMA A-AX fenceline. These radionuclides represent elements that are regarded as primary dose drivers in the PA groundwater pathway analysis. The high degree of conformance between the two models suggests that the use of the equivalent 1-D system model is suitable for evaluating the full suite of radionuclides that will be released from the tank sources within WMA A-AX over the 1,000-year compliance period and over the 10,000-year evaluation period. (authors)

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DOE OSTI2023

Benefits and Cautions in Data Assimilation Strategies: An Example of Modeling Groundwater Recharge

Assimilating recent observations improves model outcomes for real-time assessments of groundwater processes. This is demonstrated in estimating time-varying recharge to a shallow fractured-rock aquifer in response to precipitation. Results from estimating the time-varying water-table altitude (h) and recharge, and their error covariances, are compared for forecasting, filtering, and fixed-lag smoothing (FLS), which are implemented using the Kalman Filter as applied to a data-driven, mechanistic model of recharge. Forecasting uses past observations to predict future states and is the current paradigm in most groundwater modeling investigations; filtering assimilates observations up to the current time to estimate current states; and FLS estimates states following a time lag over which additional observations are collected. Results for forecasting yield a large error covariance relative to the magnitude of the expected recharge. With assimilating recent observations of h, filtering and FLS produce estimates of recharge that better represent time-varying observations of h and reduce uncertainty in comparison to forecasting. Although model outcomes from applying data assimilation through filtering or FLS reduce model uncertainty, they are not necessarily mass conservative, whereas forecasting outcomes are mass conservative. Mass conservative outcomes from forecasting are not necessarily more accurate, because process errors are inherent in any model. Improvements in estimating real-time groundwater conditions that better represent observations need to be weighed for the model application against outcomes with inherent process deficiencies. In conclusion, results from data assimilation strategies discussed in this investigation are anticipated to be relevant to other groundwater processes models where system states are sensitive to system inputs.

aquifer recharge↗

DOE OSTI2020

Hanford Site-wide Natural Recharge Boundary Condition for Groundwater Models

The purpose of this environmental calculation file (ECF) is to document the development of a tool that generates temporally and spatially variable representations of natural recharge for the Hanford Site. A key feature of the recharge evolution tool (RET) is that it applies sanctioned natural recharge rates varying as a function of the condition/cover of the ground surface and soil type at different points in time. No hydrologic calculations are performed by the RET, this script works as a lookup database between spatial and temporal datasets to assign research-based recharge rates to corresponding regions throughout the Hanford Site. This work will support vadose zone and groundwater models for the Hanford Site. Although efforts will focus on generating recharge estimates for the entirety of the Hanford Site, the focus scope of this work will be the Central Plateau Area to support the Composite Analysis Vadose Zone facet. In other words, the reliability of this calculation will be greatest within the Central Plateau Area and decrease with departures from that geographic region.

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DOE OSTI2020

Hanford Site-wide Natural Recharge Boundary Condition for Groundwater Models

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DOE OSTI2020

Hanford Site-wide Natural Recharge Boundary Condition for Groundwater Models

The purpose of this environmental calculation file (ECF) is to document the development of a tool that generates temporally and spatially variable representations of natural recharge for the Hanford Site. A key feature of the recharge evolution tool (RET) is that it applies sanctioned natural re-charge rates varying as a function of the condition/cover of the ground surface and soil type at different points in time. No hydrologic calculations are performed by the RET, this script works as a lookup data base between spatial and temporal datasets to assign research-based recharge rates to corresponding regions throughout the Hanford Site. This work will support vadose zone and groundwater models for the Hanford Site. Although efforts will focus on generating recharge estimates for the entirety of the Hanford Site, the focus scope of this work will be the Central Plateau Area to support the Composite Analysis Vadose Zone facet. In other words, the reliability of this calculation will be greatest within the Central Plateau Area and decrease with departures from that geographic region.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2018

The Importance of Capturing Topographic Features for Modeling Groundwater Flow and Transport in Mountainous Watersheds

Abstract Physics‐based distributed hydrological models that include groundwater are widely used to understand and predict physical and biogeochemical processes within watersheds. Typically, due to computational limitations, watershed modelers minimize the number of elements used in domain discretization, smoothing or even ignoring critical topographic features. We use an idealized model to investigate the implications of mesh refinement along streams and ridges for modeling three‐dimensional groundwater flow and transport in mountainous watersheds. For varying degrees of topographic complexity level (TCL), which increases with the level of mesh refinement, and geological heterogeneity, we estimate and compare steady state baseflow discharge, mean age, and concentration of subsurface weathering products. Results show that ignoring lower‐order streams or ridges diminishes flow through local flow paths and biases higher the contribution of intermediate and regional flow paths, and biases baseflow older. The magnitude of the bias increases for systems where permeability rapidly decreases with depth and is dominated by shallow flow paths. Based on a simple geochemical model, the concentration of weathering products is less sensitive to the TCL, partially due to the thermodynamic constraints on chemical reactions. Our idealized model also reproduces the observed emergent scaling relationship between the groundwater contribution to streamflow and drainage area, and finds that this scaling relationship is not sensitive to mesh TCL. The bias effects have important implications for the use of hydrological models in the interpretation of environmental tracer data and the prediction of biogeochemical evolution of stream water in mountainous watersheds.

Wang, Chao↗

DOE OSTI2020

Probabilistic Groundwater Modeling of the RDX Plume at Los Alamos National Laboratory to Support Risk Assessment - 20359

A plume of the contaminant hexahydro-1,3,5-trinitro-1,3,5-triazine (RDX) with concentrations greater than the New Mexico tap water drinking standard (9.66 ppb) is present in the regional aquifer near the southwestern boundary of Los Alamos National Laboratory (LANL). A risk assessment is performed for exposure to regional aquifer groundwater, with long-term predictions of RDX concentrations provided by a calibrated, probabilistic, numerical fate and transport model. The structure of the model is hierarchical, with the RDX Regional Aquifer (RA) groundwater model acting as the primary tool for analysis of downgradient RDX concentrations. The RA model is deeply informed by the conceptual site model (CSM) and is calibrated using site RDX concentration data and hydraulic head measurements, along with other analyses. The model is calibrated using data through December 2019. Where data are scarce other lines of evidence are used to inform inputs, including the multiphase RDX Vadose Zone (VZ) model and Pipe and Disk analytical screening tool. Model inputs are described with informative prior distributions using a robust approach to development that incorporates all available lines of evidence for every parameter used as an input to the RA model. Calibration is performed using a classical nonlinear optimization routine, which is then used to initialize a Bayesian calibration. The Bayesian calibration constrains the uncertainty in the classical calibration, ultimately providing posterior distributions for all model parameters. The challenges of the calibration include high-dimensional parameter space, including spatially heterogeneous hydraulic conductivities, comparatively sparse data, and low RDX concentrations. Posterior parameter distributions developed in the calibration process are then used for stochastic predictive model runs into the future. The result of the forward runs is spatially and temporally explicit estimates of head and concentration with uncertainty at all points in space and time. The probabilistic modeling approach presented here includes innovative computational and statistical methods that leverage high-performance computing (HPC) resources. It makes use of prior modeling work performed at the chromium plume site in the central LANL area, with extensive updates. The risk assessment will ultimately be used to support decision-making at the site, using multiple appropriately weighted sources of information, as well as uncertainty, sensitivity, and value-of-information analyses. (authors)

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NASA NTRS2015

Modelling Groundwater Depletion at Regional and Global Scales: Present State and Future Prospects.

Except for frozen water in ice and glaciers, groundwater is the world's largest distributed store of freshwater and has strategic importance to global food and water security. In this paper, the most recent advances quantifying groundwater depletion (GWD) are comprehensively reviewed. This paper critically evaluates the recently advanced modeling approaches estimating GWD at regional and global scales, and the evidence of feedbacks to the Earth system including sea-level rise associated with GWD. Finally, critical challenges and opportunities in the use of groundwater are identified for the adaption to growing food demand and uncertain climate.

Groundwater Depletion (GWD)↗

DOE OSTI2018

Updated General Separations Areas (GSA) Groundwater Model Calibration Targets

The work described in this report is part of an effort to update the General Separations Area (GSA) regional groundwater flow calibration targets to incorporate additional well data, emphasizing Z-Area, and consideration of Mixed Waste Management Facility groundwater plume monitoring data. This work utilizes a modified version of the Excel-based Well Hydrograph Analysis Tool (WHAT), previously detailed by Hiergesell and coworkers (2015a and 2015b), to evaluate the water level measurements obtained from the Environmental Restoration Data Management System (ERDMS) database. The original version of WHAT did not correctly compute median well water level, and occasionally the minimum and maximum values.

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DOE OSTI2024

A ‘Nuclear Bomb’ or Just ‘a Joke’? Groundwater Models May Help Communicate Nuanced Risks to the Great Salt Lake

The Great Salt Lake entered the zeitgeist of environmental concern in 2022 when a coalition of scientists and activists warned in a highly publicized report that the lake might be just five years away from complete desiccation, a possibility one state official warned was tantamount to an “environmental nuclear bomb”. Shortly thereafter, an unpredicted and unprecedented pluvial winter resulted in an increase in inflow, temporarily halting the lake’s decline and prompting Utah’s governor to mock the dire prediction as “a joke”, an outcome that speaks to the tension between agenda-setting and trust-building that researchers face when sharing worst-case warnings, particularly those based on short-term variability. Here, we describe a robust relationship between the lake and groundwater in the surrounding region and demonstrate how coupled models can thus be used to improve lake elevation predictions, suggesting that while the situation may not be as dire as some have warned, the lake remains at long-term risk as a result of climate warming. We further suggest that efforts to communicate the risk of future desiccation should be informed by stochastic variability and guided by long-term fluctuations in the total water storage of the endorheic lake’s watershed.

Environmental Sciences & Ecology↗

DOE OSTI2018

Impacts of prior parameter distributions on Bayesian evaluation of groundwater model complexity

Not Available

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2018

Groundwater Modeling and Predictions of C-14 Transport from Pit 38 at TA-54, Area G

This report summarizes the efforts to understand the impacts of transient flow on infiltration rates through the Pits 37 and 38 disposal units at Material Disposal Area G and on C-14 travel times to the regional aquifer. Water was used in the disposal of bulk waste generated by cleanup activities at MDA B, including to wash the metal bins in which the material was transported to Area G, to decontaminate the containers so they can be returned to service, and to decontaminate the trucks used to transport the bins.

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