Revisiting “An Exercise in Groundwater Model Calibration and Prediction” After 30 Years: Insights and New Directions

Hunt, Randall J.; Fienen, Michael N.; White, Jeremy T.

doi:10.1111/gwat.12907

Cited by 30 publications

(38 citation statements)

References 29 publications

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“…The robustness of the PEST inversion program has been demonstrated in a number of studies, see, e.g., Anderson et al (2015) and Hunt et al (2019), and is not reassessed here. The purpose of this section is to assess the accuracy of MFIT direct simulations through five synthetic test cases.…”

Section: Code Verificationmentioning

confidence: 78%

MFIT 1.0.0: Multiflow inversion of tracer breakthrough curves in fractured and karst aquifers

Bodin¹

2020

Preprint

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Abstract. More than half of the Earth’s population depends largely or entirely on fractured or karst aquifers for their drinking water supply. Both the characterization and modeling of these groundwater reservoirs are therefore of worldwide concern. Artificial tracer testing is a widely used method for the characterization of solute (including contaminant) transport in groundwater. Tracer experiments consist of a two-step procedure: 1) introducing a conservative tracer-labeled solution into an aquifer, usually through a sinkhole or a well, and 2) measuring the concentration breakthrough curve (BTC) response(s) at one or several downstream monitoring locations, usually spring(s) or pumping well(s). However, the modeling and interpretation of tracer test responses can be a challenging task in some cases, notably when the BTCs exhibit multiple local peaks and/or extensive backward tailing. MFIT is a new open-source, Windows-based computer package for the analytical modeling of tracer BTCs. This software integrates four transport models that are all capable of simulating single- or multiple-peak and/or heavy-tailed BTCs. The four transport models are encapsulated in a general multiflow modeling framework, which assumes that the spatial heterogeneity of an aquifer can be approximated by a combination of independent one-dimensional channels. Two of the MFIT transport models are believed to be new, as they combine the multiflow approach and the double-porosity concept, which is applied at the scale of the individual channels. Another salient feature of MFIT is its compatibility and interface with the advanced optimization tools of the PEST suite of programs. Hence, MFIT is the first BTC fitting tool that allows regularized inversion and nonlinear analysis of the postcalibration uncertainty of model parameters.

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Section: Code Verificationmentioning

confidence: 78%

MFIT 1.0.0: Multiflow inversion of tracer breakthrough curves in fractured and karst aquifers

Bodin¹

2020

Preprint

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“…For example, the authority collected clustered water-level measurements, which could have been optimized if a comprehensive study was conducted before drilling wells. In addition, no base-flow data were collected even though a single base-flow measurement significantly improves uncertainty quantification [36]. This study also demonstrated that if a contaminant reached the upper layer (for example during storm events that raise the water table), it will travel much faster to surrounding streams.…”

Section: Discussionmentioning

confidence: 97%

Post-Calibration Uncertainty Analysis for Travel Times at a Naval Weapons Industrial Reserve Plant

Ahmmed

James

Yelderman

2020

Water

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The Naval Weapons Industrial Reserve Plant (NWIRP) in McGregor, Texas began manufacturing explosives in 1980 and several hazardous chemicals were discovered in lakes and streams surrounding the site in 1998. Contaminants traveled to local lakes and streams much faster than initially predicted. This research estimated contaminant travel times and identified locations where monitoring wells should be installed to yield the greatest reductions in uncertainties in travel-time predictions. To this end, groundwater and particle-tracking models for NWIRP site were built to predict hydraulic heads and contaminant travel times. Next, parameter (hydraulic conductivities) uncertainties, parameter identifiabilities, observation (hydraulic heads) worth, and predictive (contaminant travel times) uncertainties were quantified. Parameter uncertainties were reduced by up to 92%; a total of 19 of 158 parameters were at least moderately identifiable; travel-time uncertainties were reduced up to 92%. Additionally, travel-time predictions and post-calibration parameter distributions were generated using the null-space Monte Carlo (NSMC) technique. NSMC predicted that conservative tracers exited the flow system within a year, which matches with field data. Finally, an observations-worth analysis found that additional 11 more measurements would reduce travel-time uncertainties by factors from 1.04 to 4.3 over existing data if monitoring wells were installed at the suggested locations.

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“…That evaluation of software approaches focused on the Gauss-Levenberg-Marquardt (GLM) approach to deterministic parameter estimation as popularized by the PEST software Doherty (2018). Hunt et al (2020) conclude with a recognition that additional utility of uncertainty for forecasts and repeatability could be gained through scripting. White et al (2020aWhite et al ( , 2020b addressed the inclusion of automated forecast uncertainty analyses needs through additional capabilities in PEST++ version 5 and demonstrated their use on an enhanced "Freyberg model," where the problem was made more complex in space and time.…”

Section: Introductionmentioning

confidence: 98%

“…The classic Freyberg (1988) paper on a classroom exercise in parameter estimation documented insights and shortcomings in a trial-and-error approach during a time that predates widely available software dedicated to parameter estimation and uncertainty analysis. Hunt et al (2020) revisited the classroom exercise from the Freyberg (1988) paper to explore how newer techniques and more modern tools could obviate shortcomings of the results obtained by students in Freyberg (1988) paper. That evaluation of software approaches focused on the Gauss-Levenberg-Marquardt (GLM) approach to deterministic parameter estimation as popularized by the PEST software Doherty (2018).…”

Section: Introductionmentioning

confidence: 99%

Risk‐Based Wellhead Protection Decision Support: A Repeatable Workflow Approach

Fienen¹,

Corson-Dosch

White³

et al. 2021

Groundwater

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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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Revisiting “An Exercise in Groundwater Model Calibration and Prediction” After 30 Years: Insights and New Directions

Cited by 30 publications

References 29 publications

MFIT 1.0.0: Multiflow inversion of tracer breakthrough curves in fractured and karst aquifers

MFIT 1.0.0: Multiflow inversion of tracer breakthrough curves in fractured and karst aquifers

Post-Calibration Uncertainty Analysis for Travel Times at a Naval Weapons Industrial Reserve Plant

Risk‐Based Wellhead Protection Decision Support: A Repeatable Workflow Approach

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