Groundwater contamination from waste management sites: The interaction between risk‐based engineering design and regulatory policy: 1. Methodology

Massmann, Joel; Freeze, R. Allan

doi:10.1029/wr023i002p00351

Cited by 160 publications

(76 citation statements)

References 30 publications

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“…However, a form of the spatial correlation must be assumed. In the traditional implementation of the updating procedure [e.g., Massmann and Freeze, 1987] it may be possible in pathological cases to generate an updated covariance matrix that is not positive-definite because of finite machine precision and numerical roundoff.…”

Section: Bayesian Solution To Linear Interpolation Of Log Transmissivmentioning

confidence: 99%

A full‐Bayesian approach to the groundwater inverse problem for steady state flow

Woodbury¹,

Ulrych²

2000

Water Resources Research

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Abstract. A full-Bayesian approach to the estimation of transmissivity from hydraulic head and transmissivity measurements is developed for two-dimensional steady state groundwater flow. The approach combines both Bayesian and maximum entropy viewpoints of probability. In the first phase, log transmissivity measurements are incorporated into Bayes' theorem, and the prior probability density function is updated, yielding posterior estimates of the mean value of the log transmissivity field and covariance. The two central moments are generated assuming that the prior mean, variance, and integral scales are "hyperparameters"; that is, they are treated as random variables in themselves which is contrary to classical statistical approaches. The probability density functions (pdfs) of these hyperparameters are, in turn, determined from maximum entropy considerations. In other words, pdfs are chosen for each of the hyperparameters that are maximally uncommitted with respect to unknown information. This methodology is quite general and provides an alternative to kriging for spatial interpolation. The final step consists of updating the conditioned natural logarithm transmissivity (in(T)) field with hydraulic head measurements, utilizing a linearized aquifer equation. It is assumed that the statistical properties of the noise in the hydraulic head measurements are also uncertain. At each step, uncertainties in all pertinent hyperparameters are removed by marginalization. Finally, what is produced is a in(T) field conditioned on measurements of both hydraulic heads and log transmissivity and covariances of the in(T) field. In addition, we can also produce resolution matrices, confidence (credibility) limits, and the like for the In(T) field. It is shown that the application of the methodology yields good estimates of transmissivities, even when hydraulic head measurements are noisy and little or no information is specified on mean values of in(T), variance of in(T), and integral scales. It is common in hydrogeologic practice to utilize nonlinear regression methods for parameter estimation. There are currently several private and public domain software packages that are used for this purpose. In order to achieve unique solutions and avoid unstable behavior in the results, it is necessary to parameterize or zone the problem in such a way as to define a smaller (usually much smaller) number of parameters than data points. As stated above, aquifers are highly heterogeneous, and hydraulic properties can vary significantly over very short distances thus making conceptual models based on large zones questionable in our opinion. Another difficulty lies 2081

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Section: Bayesian Solution To Linear Interpolation Of Log Transmissivmentioning

confidence: 99%

A full‐Bayesian approach to the groundwater inverse problem for steady state flow

Woodbury¹,

Ulrych²

2000

Water Resources Research

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“…A recent series of papers concerned with volatile organic compounds [Massmann et al, 1991;Freeze et al, 1990;Massmann and Freeze, 1987a, b] focused on risk-cost-benefit analyses in the management of contaminated sites. Pelmulder et al [1996] developed a deterministic, regional-scale framework for modeling human health risk as derived from groundwater sources.…”

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confidence: 99%

On the development of a new methodology for groundwater‐Driven health risk assessment

Maxwell¹,

Pelmulder²,

Tompson³

et al. 1998

Water Resources Research

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Abstract. A methodology and hypothetical case study are presented for incorporation of uncertainty and variability into calculations of human health risk appropriate for regional, or basin-scale, groundwater management problems. Uncertainty in well water concentration is introduced through complex contaminant migration patterns in the subsurface. Variability is considered in parameters related to individual behavior patterns and biological effects and to groundwater extraction and distribution networks. A joint uncertainty and variability (JUV) analysis is used to generate a two-dimensional distribution or risk surface that spans both transport uncertainty as well as individual variability. Cuts in this distributional surface (fractiles of variability and percentiles of uncertainty) are presented and discussed. Comparisons with alternative approaches based upon deterministic transport models are also made. In addition, important distinctions are made between the case where household water is derived from the nearest well and the case where household water is mixed from many wells in a distribution system. IntroductionGroundwater is an important natural resource in the United States, comprising 40% of all public supply water and over This paper develops a new integrated methodology of linkedgroundwater contaminant transport and human exposure that includes uncertainty and variability. This methodology explicitly addresses the variability in multipathway exposure and treats groundwater transport in regional scale, heterogeneous aquifers. Important physical features (such as wells and resultant well distribution systems) are included, as is the uncertainty in geophysical parameters. The methodology is also used to study parameter effects over a wide range of heterogeneity. An idealized groundwater contamination problem is then analyzed using the methodology, and insights regarding different water management strategies are described. BackgroundUnder the Safe Drinking Water Act (SDWA) of 1974, 1986, and 1995, the U.S. Environmental Protection Agency (USEPA) is required to regulate levels of contaminants in water supplies in order to protect public health. As part of this protection, the USEPA establishes a nonenforceable maximum contaminant goal level (MCGL) and an enforceable maximum contaminant level (MCL) for contaminants considered to have adverse health effects [Pontius, 1990a, b]. In addition, states may have their own standards. In planning the restoration or remedial action for contaminated groundwater, target cleanup levels may be established either in terms of 833

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“…A plume will be detected by a monitoring system only if the groundwater flow lines passing through the source also pass through the screened interval of the monitoring well (Massmann and Freeze, 1987a). Plume intersection along the well sampling intervals will lead to contaminant detection.…”

Section: Approach Summarymentioning

confidence: 99%

Long-term Monitoring Plan for the Shoal Underground Nuclear Test

Hassan¹

2005

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EXECUTIVE SUMMARYThe groundwater flow and radionuclide transport model characterizing the Shoal underground nuclear test has been accepted by the State of Nevada Division of Environmental Protection. According to the Federal Facility Agreement and Consent Order (FFACO) between the U.S. Department of Energy and the State of Nevada, the next steps in the closure process for the site are model validation (or postaudit), proof of concept, and long-term monitoring. This report addresses the development of the monitoring strategy for Shoal, which is needed for preparing the subsurface Corrective Action Decision Document/Corrective Action Plan (CADD/CAP). The proposed monitoring plan builds on three different, yet complementary, approaches (or tools) for locating the monitoring wells around the site with the main objective being detection monitoring and the secondary objective being data collection for model validation. The purpose of a detection-based monitoring system is the identification of groundwater contamination before a plume traverses a regulatory boundary located hydraulically downgradient of the contamination source. The design of such a system entails locating monitoring wells in the areas likely to encounter plume migration.The first tool is applied to select a number of potential siting horizons to which monitoring wells could be allocated. Based on plume geometry, this tool is used to determine the efficiency of each siting horizon and the minimum number of wells needed to span each horizon for detection monitoring. Different siting horizons can thus be ranked for detection efficiency by evaluating, for each horizon, the ratio of the maximum well spacing to the width of the potential zone of contaminant migration. A large value of this ratio indicates an effective horizon because the migration zone can be traversed with fewer wells. When a large number of monitoring wells are planned, a mathematical programming model that allocates a specified number of monitoring sites throughout the model domain can then be used. For Shoal, however, the number of monitoring wells is expected to be relatively small thereby allowing one to allocate the potential wells to the siting horizons with the highest efficiency rankings, provided that other constraints are being considered in this allocation process.Five siting horizons or control planes (CPs) have been selected for analysis. The five CPs are oriented perpendicular to the mean flow direction, which is not parallel to the model's y-coordinate. The selection of the location of these CPs is aimed at providing the necessary distances from the compliance boundary for a reaction time of 50 years. The farthest CP (CP #5) passes through the western edge of the maximum contaminant level (MCL)-based contaminant boundary (assumed here to be the compliance boundary). CP #4 is located at a distance equivalent to a 50-year reaction time (about 60 m) from the farthest point on the MCL boundary. CP #3 is at a distance of 60 m from CP #5. The next CP (CP #2) passes through the ea...

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Groundwater contamination from waste management sites: The interaction between risk‐based engineering design and regulatory policy: 1. Methodology

Cited by 160 publications

References 30 publications

A full‐Bayesian approach to the groundwater inverse problem for steady state flow

A full‐Bayesian approach to the groundwater inverse problem for steady state flow

On the development of a new methodology for groundwater‐Driven health risk assessment

Long-term Monitoring Plan for the Shoal Underground Nuclear Test

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