Geology topics

Randall J. Hunt

Publications and source records attributed to Randall J. Hunt.

At least 19 recordsLinked to original sources

USGS2026

A catalogue of Do's and Don'ts in the modeling of environmental systems

Modeling plays a vital role in understanding and managing complex environmental systems, but its credibility and quality depend heavily on a comprehensive set of defensible model activities and practices, especially when the system of interest is plagued with uncertainties and conflicting stakeholder perspectives. This paper proposes a catalogue of Do's and Don'ts to guide modelers in addressing the many pertinent considerations through the whole modeling cycle. This practical tool provides advice on approaching modeling effectively through adhering to good modeling practice. It emphasizes model choices that align with the model purpose and context, and the justification and documentation of modeling decisions and assumptions. Managing uncertainty is a core consideration. The identification, assessment and reporting of these uncertainties is important across the entire modeling process, which spans problem framing, technical design, implementation and application phases. Such good practices are critical for transparency and reliability of the modeling.

Environmental Modelling and Software↗

USGS2025

A model uncertainty quantification protocol for evaluating the value of observation data

The history-matching approach to parameter estimation with models enables a powerful offshoot analysis of data worth—using the uncertainty of a model forecast as a metric for the worth of data. Adding observation data will either have no impact on forecast uncertainty or will reduce it. Removing existing data will either have no impact on forecast uncertainty or will increase it. The history-matching framework makes it possible to perform this quantitative analysis leveraging the connections among observations, model parameters, and model forecasts. We show this behavior on a specific groundwater flow model of the Mississippi Alluvial Plain and show where the analysis can be informative for considering the potential design of an observation network based on existing or potential observations.

Scientific Investigations Report↗

USGS2024

Temporally dense monitoring of pathogen occurrence at four drinking-water well sites – Insights and Implications

Yearlong, event based, microbiological and chemical sampling was conducted at four public water supply well sites spanning a range of geologic settings and well depths to look for correlation between precipitation events and microbial occurrence. Near-continuous monitoring using autosamplers occurred just before, during, and after 5–7 sampling events triggered by rainfall and/or snowmelt. Microbial genetic material was noted at all four locations during all but one sampling event, but was exceedingly variable in time, where one sample would have no detections and the next sample could be a relatively high concentration. The highest microbial sums (microbial concentrations summed over an event) were observed during months in which precipitation exceeded historical averages. Extended wet conditions through the spring thaw resulted in the highest percentage of microbial positive samples, though at relatively low concentrations. Sampling events that followed drier than normal periods showed longer lag times between the onset of precipitation and microbial occurrence, as well as lower microbial detection rates. Although a general lag time pattern was observed at each site, the largest offset in time was observed at the site with the greatest depth to water. The study's temporally dense representation of drinking water pathogen characterization suggests that single event or infrequent periodic sampling of a drinking water supply cannot provide a representative characterization of the probability that pathogens are present, which likely has ramifications for calculating health risk assessments.

Minnesota↗

USGS2023

Simulating groundwater flow in the Mississippi Alluvial Plain with a focus on the Mississippi Delta

The Mississippi Alluvial Plain has become one of the most important agricultural regions in the United States but relies heavily on groundwater for irrigation. On average, more than 12 billion gallons are withdrawn daily from the Mississippi River Valley alluvial aquifer. Declining groundwater levels, especially in the Delta region of northwest Mississippi and the Cache and Grand Prairie regions of eastern Arkansas, have led to concerns about future sustainability. The U.S. Geological Survey Mississippi Alluvial Plain Project is focused on quantifying the groundwater system in the alluvial plain and the response of groundwater resources to future development. A key objective of the project is to provide updated groundwater flow models supported by extensive data collection and analyses. MODFLOW 6, PEST++, and several open-source python packages were used to develop a simplified, faster running version of the Mississippi Embayment Regional Aquifer Study model that can provide boundary conditions for local inset models, including the Mississippi Delta model described in this report. An automated workflow was used for model construction, history matching, and development of baseline future climate scenarios. The models incorporate information from a Soil-Water-Balance code simulation of the terrestrial water balance, metering-based estimates of water use from thousands of wells, measured and estimated streamflow and stages, and the largest airborne electromagnetic survey flown to date in the United States. Baseline scenarios for the Mississippi Delta under potential future climates were constructed using recharge, surface runoff and irrigation pumping forcings from a future version of the Soil-Water-Balance model, driven by downscaled temperature and precipitation output from 10 general circulation model simulations, including high and moderate carbon emissions pathways. Results indicate a complex water balance that varies in time and space in terms of the terrestrial recharge, stream leakage, and regional groundwater flow components, which are affected by seasonal forcings, human activity, and alluvial geomorphology. The general circulation model outputs indicate a continued rise in average temperatures but no clear precipitation trend. Increased crop water demand is anticipated from the higher temperatures, resulting in increased irrigation withdrawals to sustain current levels of irrigated agriculture. Simulated drawdowns in groundwater levels at the mid-21st century vary greatly. Under moderate or wet climate scenarios, and in parts of the aquifer that are well connected to surface water, little to no additional drawdown is anticipated. Under dry or warm scenarios, drawdowns of as much as 10 meters or more are possible in parts of the aquifer that are relatively disconnected from surface water. Under dry or warm scenarios, the portion of the Delta with greater than 60 feet of saturated thickness could be reduced from near 100 percent currently (2018) to 80–90 percent by mid-century. Future simulations with the model could include alternative management scenarios to identify options for improving groundwater sustainability. The automated model construction workflows are designed to facilitate regular updating, making this a “living” framework that the Mississippi Department of Environmental Quality and other stakeholders can use for adaptive management going forward.

Arkansas, Louisiana, Mississippi↗

USGS2023

Effects of auto-adaptive localization on a model calibration using ensemble methods

Simulations of the natural systems for environmental decision-making typically benefit from a highly parameterized approach (Hunt et al. 2007; Doherty and Hunt 2010), which enhances the flow of information contained in state observations to the parameters and improves application to decision support. However, parameter estimation (PE) with highly parameterized environmental models using traditional approaches (e.g., Doherty and Hunt 2010) is computationally intensive. Attempts at addressing the computational burden include improved computing approaches (e.g., Schreüder 2009; Hunt et al. 2010) and advances in algorithmic approaches (e.g., Tonkin and Doherty 2005; Welter et al. 2012, 2015). Recently, the iterative ensemble smoother (IES) approach (Chen and Oliver 2013; White 2018; White et al. 2020a) has greatly improved the efficiency of the PE calibration process compared to previous algorithms while concurrently providing nonlinear estimates of uncertainty (Hunt et al. 2021).

Groundwater↗

USGS2023

Evaluation of models for estimating hydraulic conductivity in glacial aquifers from NMR logging

Nuclear magnetic resonance (NMR) logging is a promising method for estimating hydraulic conductivity ( K ). During the past ∼60 years, NMR logging has been used for petroleum applications, and different models have been developed for deriving estimates of permeability. These models involve calibration parameters whose values were determined through decades of research on sandstones and carbonates. We assessed the use of five models to derive estimates of K in glacial aquifers from NMR logging data acquired in two wells at each of two field sites in central Wisconsin, USA. Measurements of K , obtained with a direct push permeameter (DPP), K DPP , were used to obtain the calibration parameters in the Schlumberger-Doll Research, Seevers, Timur-Coates, Kozeny-Godefroy, and sum-of-echoes (SOE) models so as to predict K from the NMR data; and were also used to assess the ability of the models to predict K DPP . We obtained four well-scale calibration parameter values for each model using the NMR and DPP measurements in each well; and one study-scale parameter value for each model by using all data. The SOE model achieved an agreement with K DPP that matched or exceeded that of the other models. The Timur-Coates estimates of K were found to be substantially different from K DPP . Although the well-scale parameter values for the Schlumberger-Doll, Seevers, and SOE models were found to vary by less than a factor of 2, more research is needed to confirm their general applicability so that site-specific calibration is not required to obtain accurate estimates of K from NMR logging data.

Wisconsin↗

USGS2023

Can hydrological models benefit from using global soil moisture, evapotranspiration, and runoff products as calibration targets?

Hydrological models are usually calibrated to in-situ streamflow observations with reasonably long and uninterrupted records. This is challenging for poorly gage or ungaged basins where such information is not available. Even for gaged basins, the single-objective calibration to gaged streamflow cannot guarantee reliable forecasts because, as has been documented elsewhere, the inverse problem is mathematically ill-posed. Therefore, the inclusion of other observations, and the reproduction of other hydrological variables beyond streamflow, become critical components of accurate hydrological forecasting. In this study, six single- and multi-objective model calibration schemes based on different combinations of gaged streamflow, global-scale gridded soil moisture, actual evapotranspiration (ET), and runoff products are used for the calibration of a process-based hydrological model for 20 catchments located within the Lake Michigan watershed, of the Laurentian Great Lakes. Results show that the addition of gridded soil moisture to gaged streamflow in model calibration improves the ET simulation performance for most of the catchments, leading to the overall best-performing models. The monthly streamflow simulation performance for the experiments using gridded runoff products to inform the model is outperformed by those using the gaged streamflow, but the discrepancy is mitigated with increasing catchment scale. A new visualization method that effectively synthesizes model performance for the simulations of streamflow, soil moisture, and ET was also proposed. Based on the method, it is revealed that the streamflow simulation performance is relatively weak for baseflow-dominated catchments; overall, the 20 catchment models simulate streamflow and ET better than soil moisture.

Lake Michigan↗

USGS2023

Hydrologic change in the St. Louis River Basin from iron mining on the Mesabi Iron Range, northeastern Minnesota

This study compares the results of two regional steady-state U.S. Geological Survey Modular Three-Dimensional Finite-Difference Ground-Water Flow (MODFLOW) models constructed to quantify the hydrologic changes in the St. Louis River Basin from iron mining on the Mesabi Iron Range in northeastern Minnesota. The U.S. Geological Survey collaborated in this study with bands of the Minnesota Chippewa Tribe, and the Minnesota Pollution Control Agency to inform management decisions about aquatic resources in the St. Louis River Basin. A model constructed and calibrated to represent average 1995–2015 mining conditions produced regional groundwater heads and flows. A pre-mining scenario model was constructed from this mining model but had the land and bedrock surfaces restored to pre-mining topographies and had modeled mining features (mine pits, tailings basins, waste-rock piles, and mining-disturbed areas) eliminated to represent general pre-mining stratigraphy and hydrogeology. Many of the features important to the hydrology of this mining area (like individual mine pits) are difficult to represent in groundwater models and required the use of modeling tools to indirectly account for their effects. The difference between the results of these two models represents mining’s effects on the hydrology in the Mesabi Iron Range area of the St Louis River Basin. The mining and pre-mining regional models also can provide boundary conditions and initial properties for future local or site-specific groundwater-flow models in the area. Total groundwater flow through the mining model is 171 million cubic feet per day. Areal recharge is the largest source of groundwater (78 and 81 percent of total groundwater flow in the mining and pre-mining scenario models, respectively). Seepage from streams and lakes provides another 17 percent of the total groundwater flow through both models. Water leaves aquifers through seepage to streams (discharge as base flow, 43 percent in both models) and areal seepage to the land surface (surface seepage), for example to wetlands (45 and 49 percent, mining and pre-mining scenario models respectively). Comparison of the results from the mining and pre-mining scenario models shows that iron mining has produced measurable hydrologic changes in the St. Louis River Basin, but that most of those changes and the highest magnitude changes occur near the mining features. Flow changes to and from surface-water bodies like streams and wetlands were analyzed in detail because of their importance in sustaining surface waters and aquatic life. Overall, groundwater flow in the mining model was 3.62 million cubic feet per day (2.2 percent) greater than total pre-mining model groundwater flow. This was caused by an increase in recharge from tailings basins and a decrease in discharge from surface seepage. Groundwater discharge to mine pits was the largest change in groundwater flows between the models (a change representing 2.8 percent of total pre-mining model groundwater flow). Net recharge to groundwater from tailings basins (2.4 percent), net decrease in surface seepage from groundwater (2.7 percent), and net increase in seepage to streams (1.0 percent) were all in this same range of total pre-mining model groundwater flow. Groundwater lost through mine-pit withdrawals was nearly offset by groundwater gained through recharge from tailings basins. However, because losses and gains occurred in different areas, the effect of mining can have more substantial effects on local areas than the model-wide averages represent.

Minnesota↗

USGS2023

Using airborne electromagnetics to improve depth to bedrock estimates in Wisconsin

Depth to bedrock is an important factor in hydrologic systems. The thickness of glacial sediments overlying bedrock in Wisconsin controls the routing of groundwater in surficial aquifers and its Depth to bedrock is often an important factor in hydrologic systems because hydraulic properties of bedrock and overlying sediments are typically appreciably different. For example, the thickness of glacial sediments overlying bedrock in Wisconsin controls the routing of groundwater in surficial aquifers and its connection with surface water bodies such as lakes and wetlands. In fractured bedrock environments, shallow bedrock can be vulnerable to degraded water quality when contaminants at the surface infiltrate quickly through permeable formations. Here, airborne electromagnetic surveys were acquired in three different parts of Wisconsin, totalling more than 5,700 flight line-kilometers, to improve understanding of depth to bedrock, the lithologic composition of overlying sediments, and as input structure for groundwater model development.

Wisconsin↗

USGS2022

New capabilities in MT3D-USGS for simulating unsaturated-zone heat transport

Changes in climate and land use will alter groundwater heat transport dynamics in the future. These changes will in turn affect watershed processes (e.g., nutrient cycling) as well as watershed characteristics (e.g., distribution and persistence of cold-water habitat). Thus, groundwater flow and heat transport models at watershed scales that can characterize and quantify thermal impacts of surface temperature change on groundwater system temperatures are needed to forecast changes to groundwater-linked ecosystems in riparian zones, streams, and lakes. Including unsaturated zone processes has previously been shown to be important for properly determining the timing and magnitude of groundwater recharge (Hunt et al. 2008). Similarly, heat transport dynamics in the saturated-zone, as well as connected surface-water systems, can be appreciably influenced by unsaturated-zone processes; in this way the unsaturated zone forms an inextricable link between land surface where change occurs and the groundwater system that transmit that change. This paper presents new capabilities for the existing MT3D-USGS transport simulator by adding functionality for simulating heat transport through the unsaturated zone. New simulation capabilities are verified through comparison of simulation results with those of the variably-saturated heat transport simulator VS2DH under steady and transient conditions for both water and heat flow. The new capabilities are assessed using a number of conceptualizations and include evaluations of convective and conductive heat flow. These additional capabilities increase the utility for applied watershed-scale simulations, which in turn should facilitate more realistic characterizations of temperature change on thermally sensitive ecosystems, such as stream habitat.

Groundwater↗

USGS2022

Simulation of heat flow in a synthetic watershed: Lags and dampening across multiple pathways under a climate-forcing scenario

Although there is widespread agreement that future climates tend toward warming, the response of aquatic ecosystems to that warming is not well understood. This work, a continuation of companion research, explores the role of distinct watershed pathways in lagging and dampening climate-change signals. It subjects a synthetic flow and transport model to a 30-year warming signal based on climate projections, quantifying the heat breakthrough on a monthly time step along connected pathways. The system corresponds to a temperate watershed roughly 27 km on a side and consists of (a) land-surface processes of overland flow, (b) infiltration through an unsaturated zone (UZ) above an unconfined sandy aquifer overlying impermeable bedrock, and (c) groundwater flow along shallow and deep pathlines that converge as discharge to a surface-water network. Numerical simulations show that about 40% of the warming applied to watershed infiltration arrives at the water table and that the UZ stores a large fraction of the upward-trending heat signal. Additionally, once groundwater reaches the surface-water network after traveling through the saturated zone, only about 10% of the original warm-up signal is returned to streams by discharge. However, increases in the simulated streamflow temperatures are of similar magnitude to increases at the water table, due to the addition of heat by storm runoff, which bypasses UZ and groundwater storage and counteracts subsurface dampening. The synthetic modeling method and tentative findings reported here provide a potential workflow for real-world applications of climate-change modeling at the full watershed scale.

Water↗

USGS2022

Comparison of radium analytical methods for municipal drinking water well operation

Radium (Ra) is a geogenic contaminant that occurs at high levels in the Midwestern Cambrian-Ordovician aquifer system (MCOAS), a regionally important sandstone and carbonate drinking water aquifer. Water utilities using the MCOAS often must adopt treatment methods or use alternative water sources to maintain high-quality drinking water. Here, we show that Ra in water obtained from a municipal well in Wisconsin remains consistent despite variation in pumping conditions. However, widely used analytical methods (e.g., scintillation counting) for measuring Ra are less precise for quantifying Ra variability given the site conditions. Although not currently used for EPA compliance, mass spectrometry improves the precision of Ra measurements by an order of magnitude over the currently used counting method (e.g., 95 ± 3 mBq/L vs. 110 ± 30 mBq/L) at the concentrations observed in this study. The use of more precise analytical methods will increase understanding of trends in Ra levels important for operating public water systems.

Water Science and Engineering↗

USGS2022

Use case development for earth monitoring, analysis, and prediction (EarthMAP)—A road map for future integrated predictive science at the U.S. Geological Survey

Executive Summary The U.S. Geological Survey (USGS) 21st-century science strategy 2020–30 promotes a bureau-wide strategy to develop and deliver an integrated, predictive science capability that works at the scales and timelines needed to inform societally relevant resource management and protection and public safety and environmental health decisions (U.S. Geological Survey, 2021). This is the overarching goal of the USGS Earth Monitoring, Analysis, and Prediction (EarthMAP) vision, which consists of three components: (1) integrated data and information, (2) integrated predictive science, and (3) actionable information—all designed and delivered to respond to user needs. To launch this vision and help shape the design and implementation of integrated predictive science, the USGS Regional Offices each developed a set of use cases (hereafter Use Cases)—short descriptions of potential science applications that could clearly address high priority decision-making needs of our stakeholders and that align with an integrated science focus. Use Cases are not actionable science planning documents, nor stand-alone scholarly works, but should be considered as innovative, next-generation science ideas that can be considered as potential components of science plans still under development. The goal of Use Case development was to (1) identify and characterize existing USGS scientific capacities and expertise that can support science goals and products, (2) identify opportunities to leverage current capacities for next-generation science, and (3) foster engagement across the entire Bureau to further refine the USGS strategy for EarthMAP and integrated predictive science. The Use Case development effort documented in this report was coordinated by the Use Case Development Team (UCDT), consisting of representatives from each region. The UCDT undertook five tasks: (1) develop a unified approach to engage bureau scientists consistently across all regions in aspirational thinking about what can be accomplished; (2) work with the regions and their Science Centers to generate an initial set of Use Cases, authored directly by scientists; (3) characterize, summarize, and document the initial set of Use Case submissions from authors to illuminate bureau-level demand for integrated science; (4) compare existing and needed capacities from the Use Case descriptions with preliminary results of the EarthMAP Capacity Assessment (Keisman and others, 2021); and (5) describe lessons learned from the Use Case development process and provide recommendations to inform future efforts to generate integrated science activities. This report outlines the approach the UCDT developed to solicit Use Cases from the regions and summarizes the high-level qualitative findings from this first-round effort. The UCDT received 36 Use Cases from the regions and identified potential points of convergence and commonalities considered useful in making connections among the participating scientists. The Southwest (SW) Region and the Rocky Mountain (RM) Region asked scientists to give special consideration to Use Cases with applicability to the Colorado River Basin, and seven of the Use Cases specifically named that geographic area as a focus. Coastal hazards and coastal resilience were identified in Use Cases from the Alaska (AK), Northeast (NE), and Southeast (SE) Regions. Aspects of wildfire and post-wildfire response were part of Uses Cases from AK, RM, and SW Regions. The greatest convergence of Use Case themes was related to conservation of public lands and waters, which is a powerful linkage lending strength to future collaborative efforts. The most common type of stakeholder decisions that would be informed by the Use Case science applications were related to adaptation, mitigation, and response (for example, how to increase the resilience of coastal communities to climate-related stressors and how to prevent or respond to harmful algal blooms). Other common types of decisions included water and land management decisions (including operational water management decisions such as reservoir operations and land use planning in the sagebrush biome), decisions about how to manage and conserve habitats and species, and risk management decisions (such as managing the post-wildfire flood risks). These decision types are not exclusive because many Use Cases cross categories. Use Case authors identified existing and needed science and technology capabilities required for Use Case implementation, which were then aligned to capabilities assessed in the EarthMAP Capacity Assessment (Keisman and others, 2021). Strong alignment was found for data and information integration approaches, modeling and prediction approaches, and capabilities related to delivery of actionable information. A majority of Use Cases indicated insufficient current capacity for needed data collection methods, data integration, and modeling and prediction approaches, whereas only 25 percent indicated insufficient capacity for actionable information delivery. Overall, many Use Case capacity demand gaps could potentially be met by existing bureau-wide capacity. In addition, nearly half of the Use Cases could potentially be implemented within 3 years if funding, capabilities, and personnel impediments were removed and science priorities were realigned. Several challenges emerged during the Use Case development process. The first challenge was developing an approach that was flexible enough to accommodate regional differences in planning and implementation, while also ensuring enough guidance to promote meaningful summary analyses. The UCDT encountered a strong demand for continuous communication and education to improve overall understanding of the integrated predictive science strategy. Another challenge was managing expectations about EarthMAP activities as a design effort that was not aligned to an immediate funding opportunity. Connecting the Use Cases to stakeholder needs without the opportunity for direct stakeholder engagement was also challenging. The last notable challenge was in obtaining consistent interpretation and characterization of the qualitative data housed in the narrative descriptions of Use Cases, written in different styles. Overall, the 36 Use Cases can serve as components of a road map for advancing integrated monitoring and predictive science throughout the USGS by revealing opportunities to (1) encourage cross-region initiatives that address shared interests in common themes by integrating similar Use Cases and through direct involvement of stakeholders in identifying needs and designing effective responses, (2) leverage the Use Cases to target investments that are aligned with the Bureau and Department of the Interior (DOI) priorities, (3) connect Use Cases and the results of the companion EarthMAP Capacity Assessment (Keisman and others, 2021) to identify potential priorities for capacity building investments, and (4) raise awareness of common integrated and interdisciplinary science interests within and across the regions through Use Case and Capacity Assessment summary outreach activities.

Open-File Report↗

USGS2022

Isotopic analysis of radium geochemistry at discrete intervals in the Midwestern Cambrian-Ordovician aquifer system

Radium (Ra) is a geogenic radioactive contaminant that frequently occurs at elevated levels in the Midwestern Cambrian-Ordovician aquifer system (MCOAS). Geochemical indicators (e.g., redox conditions or total dissolved solids) can broadly characterize conditions associated with elevated Ra levels in groundwater, but do not consistently correlate to elevated Ra within specific stratigraphic horizons. A coupled geochemical and isotopic study of groundwater and aquifer solids for major and trace elements, Ra, and uranium (U) at discrete intervals in the MCOAS was used to elucidate processes that may be responsible for this disconnect, via analysis of groundwater as well as extracted and digested solid aquifer samples. We find that the potential for Ra mobilization varies by stratigraphic unit, as observed by whole-rock 226 Ra/ 238 U (dis)equilibrium. Overall, the examined aqueous geochemical characteristics (e.g., redox conditions, total dissolved solids) do not explain Ra concentrations within the system, suggesting that alternative factors, like solid-phase associations or the extent of alpha recoil damage, may be more important. A relation between aqueous 87 Sr/ 86 Sr and 226 Ra suggests that minerals with radiogenic 87 Sr/ 86 Sr are more likely to release 226 Ra to the aqueous system. Overall, the release of U and Ra due to water-rock interaction varies with discrete stratigraphy, depending on aqueous geochemistry and available mineral associations. Due to complex Ra-rock interactions and the heterogeneous geology of the MCOAS, aqueous geochemistry does not fully predict the mobilization and concentration of Ra in groundwater. As sources and sinks of Ra within the MCOAS vary across stratigraphy, knowledge of aqueous geochemistry, available solid-phase associations, and nuclide leachability all are important to consider for understanding elevated Ra occurrence in aquifer systems.

Wisconsin↗

USGS2022

NWTOPT — A hyperparameter optimization approach for selection of environmental model solver settings

Hyperparameter optimization approaches were applied to improve performance and accuracy of groundwater flow models. Freely available new software, NWTOPT, is described that uses Tree of Parzen Estimators (TPE) and Random Search algorithms to optimize MODFLOW-NWTs solver settings. We ran 3500 trials on a steady-state and transient model. To quantify the performance of candidate solver settings, we defined a loss function based on time elapsed and mass balance error of the MODFLOW-NWT forward run. Before optimization the steady- state model ran in ~12 min and the transient model ran in ~5 h with acceptable mass balance error (<1%). After optimization runtimes were reduced to ~2.7 min (steady state) and ~48 min (transient) with errors below 0.1%. In both cases TPE found hyperparameters that resulted in faster running and lower error models than those found by Random Search. The time to complete the optimization trials was also shorter with the TPE algorithm.

Environmental Modelling and Software↗

USGS2022

A scalable model-independent iterative data assimilation tool for sequential and batch estimation of high dimensional model parameters and states

Ensemble-based data assimilation (DA) methods have displayed strong potential to improve model state and parameter estimation across several disciplines due to their computational efficiency, scalability, and ability to estimate uncertainty in the dynamic states and the parameters. However, a barrier to adoption of ensemble DA methods remains. Namely, there is currently a lack of available tools that enable efficient and scalable DA in a non-intrusive fashion and that support implementation flexibility. This paper presents an open-source software tool (PESTPP-DA) that implements a range of data assimilation methods—Ensemble Kalman filter, Ensemble Kalman Smoother and Ensemble Smoother—using the widely known PEST model-interface protocols, to interact with any model. Two iterative solutions can be used for nonlinear and/or non-Gaussian assimilation problems. To demonstrate the broad range of PESTPP-DA applications, two synthetic case studies are presented: (1) the Lorenz model and (2) a groundwater pumping test in the presence of a non-Gaussian hydraulic conductivity field.

Environmental Modelling & Software↗

USGS2021

Groundwater/surface-water interactions in the Partridge River Basin and evaluation of hypothetical future mine pits, Minnesota

The Partridge River Basin (PRB) covers 156 square miles in northeastern Minnesota with headwaters in the Mesabi Iron Range. The basin is characterized by extensive wetlands, lakes, and streams in poorly drained and often thin glacial material overlying Proterozoic bedrock. To better understand the interaction between these extensive surface water features and the groundwater system, a three-dimensional, steady-state, groundwater-flow model of the PRB was developed by the U.S. Geological Survey in cooperation with the Great Lakes Indian Fish & Wildlife Commission using the finite-difference computer code MODFLOW-NWT. The model simulates steady-state base flow in streams and groundwater interactions using the streamflow routing (SFR2) package. Existing mining features including tailings basins, stockpiles, pumped mine pits, and flooded mine pits were simulated using either high hydraulic conductivity zones or the drain (DRN) package. The unsaturated zone flow (UZF) package was used to better represent the groundwater system in areas with a high water table and for wetlands often associated with such areas. UZF typically is used to represent unsaturated zone processes but also can simulate the rejection of recharge and groundwater discharge to the land surface when the water table is near land surface. The steady-state model used data from the 2011 to 2013 period when 2011 high-resolution land surface (light detecting and ranging [lidar]) data were available that reflected land-surface and water elevations from mining activity in the basin. The parameter-estimation software suite PEST_HP was used to obtain a best fit of the modeled to measured groundwater levels, streamflow, pit inflow rates, and mapped peat deposits. The PEST calibration used the target residuals from two models with the same model parameters and targets from two separate periods: (1) a 1995–2015 calibration model, which provided a larger number of calibration targets, and (2) a 2011–2013 mining conditions model, which included calibration targets that reflected conditions consistent with the modeled mine-workings topography. Calibration of the PRB model resulted in ranges of glacial horizontal hydraulic conductivity parameters that generally agreed with literature values and other models of the region. Horizontal hydraulic conductivity of the bedrock was higher in the upper bedrock layers where numerous and continuous fractures have been observed and lower in the deeper bedrock layers. Average basin-wide calibrated infiltration was 5.3 inches per year. An average of 4.6 inches per year of infiltration crosses the water table and becomes recharge and 0.7 inch per year is rejected by UZF due to saturated conditions at the land surface. Simulated groundwater runoff (the sum of rejected recharge and groundwater seepage to the land surface) can either be routed to streams or removed from the model as evapotranspiration. The calibrated model indicates relatively shallow groundwater-flow paths dominating and approximately 50 percent of the stream base flow coming from groundwater runoff. The 2011–2013 mining conditions model was then used to develop five model scenarios simulating the response of the groundwater and surface-water system to potential hydrologic stress. The purpose of these mine pit scenarios is to present a possible workflow to quantify a model’s uncertainty for a given model forecast and serve as a possible guide for initial data collection that may improve a future model’s ability to make such a forecast. The scenarios included one scenario with the currently existing Peter Mitchell pit at final buildout and flooded to an elevation of 1,500 feet, and four scenarios with a hypothetical, new mine pit plus the flooded Peter Mitchell at final buildout. The five model scenarios were used to forecast streamflow at six locations in the PRB, pit inflow rates for the new mine pits and the flooded Peter Mitchell pit, and the average depth to water in 12 wetlands. A linear uncertainty analysis was performed using information from the PEST calibration and tools in the PyEMU python package to assess model uncertainty propagation to the model forecasts. Streamflows generally were reduced with future mining and the greatest streamflow reductions occurred from the flooded Peter Mitchell Pit, probably due to its large size. Average depth to groundwater in wetlands was most affected the closer the wetland was to a new mine pit. Linear uncertainty methods were also used to evaluate data worth, which is the ability for potential new groundwater elevation observations to reduce the uncertainty in scenario forecasts. Data worth was performed for a grid of new hydraulic head observations. Overall, areas with nonnegligible data worth generally corresponded to wetland areas with no groundwater seepage to land surface from UZF. These model behaviors indicated that the land-surface boundary condition simulated by the UZF package was pinning the groundwater elevations to the land surface in areas with groundwater seepage (33 percent of the 2011–2013 base conditions model) such that the sensitivity to new observations in these areas was minimal. Therefore, representing wetlands as boundary conditions minimized the usefulness of data worth calculations because wetland areas were present over a large part of the model domain. Probabilistic capture zones were estimated for each of the mines in the model scenarios. A capture zone represents the area contributing recharge to a model feature, like a well or a mine pit, and can be calculated by forward tracking particles from the water table. By using Monte Carlo techniques, it is possible to generate estimated capture zones that include the probability of recharge capture given the uncertainty present in the model. Monte Carlo techniques use randomly generated model parameter sets sampled from a plausible parameter range to create many possible realizations. The resulting capture zone arrays were calculated by tallying the total number of realizations in which a particle from a model cell was captured by the feature. Probabilities from the Monte Carlo runs ranged from 1 (captured in 100 percent of the runs) near the pits to 0 (captured in 0 percent of the runs) at the edges of the capture zone. Capture zones were not always spatially continuous; for example, the capture zone for the proposed mine pits south of the flooded Peter Mitchell pit was discontinuous with capture surrounding the proposed mine pit and north of the flooded Peter Mitchell pit. This northern section represents deeper groundwater flow paths that originate in the topographic high, move under the flooded pit, and discharge into the proposed pit. This pattern of capture indicates the possibility of some deeper flow through the upper fractured bedrock when the shallow groundwater flow system is modified. These results underscore that future site-specific applications of the base condition model require the input of site-specific data and recalibration to focus on the site of interest.

Minnesota↗

USGS2021

Risk-based wellhead protection decision support: A repeatable workﬂow approach

Environmental water management often benefits from a risk-based approach where information on the area of interest is characterized, assembled, and incorporated into a decision model considering uncertainty. This includes prior information from literature, field measurements, professional interpretation, and data assimilation resulting in a decision tool with a posterior uncertainty assessment accounting for prior understanding and what is learned through model development and data assimilation. Model construction and data assimilation are time consuming and prone to errors, which motivates a repeatable workflow where revisions resulting from new interpretations or discovery of errors can be addressed and the analyses repeated efficiently and rigorously. In this work, motivated by the real world application of delineating risk-based (probabilistic) sources of water to supply wells in a humid temperate climate, a scripted workflow was generated for groundwater model construction, data assimilation, particle-tracking and post-processing. The workflow leverages existing datasets describing hydrogeology, hydrography, water use, recharge, and lateral boundaries. These specific data are available in the United States but the tools can be applied to similar datasets worldwide. The workflow builds the model, performs ensemble-based history matching, and uses a posterior Monte Carlo approach to provide probabilistic capture zones describing source water to wells in a risk-based framework. The water managers can then select areas of varying levels of protection based on their tolerance for risk of potential wrongness of the underlying models. All the tools in this workflow are open-source and free, which facilitates testing of this repeatable and transparent approach to other environmental problems.

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