When perchlorate degradation in the riverbank cannot impede the contamination of drinking water wells

Delbart, Célestine; Pryet, Alexandre; Atteia, Olivier; Cousquer, Yohann; Valois, Rémi; Franceschi, Michel; Dupuy, Alain

doi:10.1007/s10040-021-02326-y

Cited by 2 publications

(5 citation statements)

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“…Karst conduits are expected to be narrow and of limited extension but can be at the origin of the high values of estimated hydraulic Frontiers in Earth Science frontiersin.org conductivity (Cousquer, 2017). On the opposite, low values can be explained by fine deposits in the riverbed (Delbart et al, 2021).…”

Section: Resultsmentioning

confidence: 97%

“…Measurements of drain discharge rates can be considered as reliable and the misfit may rather be explained by the static, linear relation that is considered with the MODFLOW drain package. In contrast, measurement of mixing ratios derived from concentrations by end-member analysis are prone to uncertainties (Delbart et al, 2021). The structural error of this simplified model is therefore strong and surely contributes to the misfit, but uncertainties in the observation data and historic operating variables are also important.…”

Section: Resultsmentioning

confidence: 99%

“…The well field is located in South-West France and is critical to the water supply for the city of Bordeaux (Cousquer, 2017;Valois et al, 2018;Delbart et al, 2021) as it accounts for about 20% of the needs. The aquifer lies in Oligocene limestone overlain by sandy and alluvial deposits.…”

Section: Case Study 41 Model Descriptionmentioning

confidence: 99%

“…The observation data set is composed of hydraulic heads, drain discharge rates, and mixing ratios. The latter were derived by end-member analysis from HCO 3− and Ca 2+ concentrations (Delbart et al, 2021).…”

Section: Parameter Estimation and Optimizationmentioning

confidence: 99%

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Particle tracking as a vulnerability assessment tool for drinking water production

et al. 2022

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The simulation of concentration values and use of such data for history-matching is often impeded by the computation time of groundwater transport models based on the resolution of the advection-dispersion equation. This is unfortunate because such data are often rich in information and the prediction of concentration values is of great interest for decision making. Particle tracking can be used as an efficient alternative under a series of simplifying assumptions, which are often reasonable at groundwater sinks (wells and drains). Our approach consists of seeding particles around a sink and tracking particles backward, up to the source boundary condition, such as a contaminated stream. This particle tracking approach allows the use of parameter estimation and optimization methods requiring numerous model calls. We present a Python module facilitating the pre- and post-processing operations of a modeling workflow based on the widely used USGS MODFLOW6 and MODPATH7 programs. The module handles particle seeding around the sink and estimation of the mixing ratio of water withdrawn from the sink. This ratio is computed with a mixing law from the particle endpoints, accounting for particle velocities and mixing in the source model cells. We investigate the best practice to obtain robust derivatives with this approach, which is a benefit for the screening methods based on linear analysis. We illustrate the interest of the approach with a real world case study, considering a drinking water well field vulnerable to a contaminated stream. The configuration is typical of many other drinking water production sites. The modeling workflow is fully script-based to make the approach easily reproducible in similar cases.

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Section: Resultsmentioning

confidence: 97%

Section: Resultsmentioning

confidence: 99%

Section: Case Study 41 Model Descriptionmentioning

confidence: 99%

Section: Parameter Estimation and Optimizationmentioning

confidence: 99%

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Particle tracking as a vulnerability assessment tool for drinking water production

et al. 2022

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Section: Resultsmentioning

confidence: 99%

Particle tracking as a vulnerability assessment tool for drinking water production

Pryet¹,

Matran²,

Cousquer

et al. 2022

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<p>The assimilation and prediction of concentration data is often impeded by the computation time of groundwater transport models based on the resolution of the advective-dispersive equation. This is unfortunate because such data is often rich in information and the prediction of concentration values is of great interest for decision making. &#160;Particle tracking may be used as an efficient alternative under a series of simplifying assumptions, which are often reasonable at groundwater sinks. A rapid transport model allows the use of assimilation and optimization methods requiring many model calls. &#160;We developed a Python package to facilitate the use of the USGS MODFLOW6 and MODPATH7 models to simulate the transfer of tracer or contaminant concentrations to a groundwater sink (typically a pumping well or a drain). The approach requires the identification of one or a series of sources of tracer/contaminant such as a contaminated stream or area in the model domain. The package handles particle seeding around the sink and estimation of the concentration of water withdrawn from the sinks. Both &#8220;strong&#8221; and &#8220;weak&#8221; sources can be considered. Concentrations are computed with a mixing law from the particle endpoints and velocities. We investigated the best practice to obtain robust derivatives with this approach, which is essential for all methods based on the linearized version of the model. We provide a step-by-step workflow from model construction to parameter estimation, linear uncertainty analysis, and chance-constraints optimization with the PEST suite. The interest and practical details of the approach are illustrated on a well field vulnerable to a stream, and a parametric analysis is provided in order to evaluate the impact of key numerical parameters on the presented results.</p>

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When perchlorate degradation in the riverbank cannot impede the contamination of drinking water wells

Cited by 2 publications

References 46 publications

Particle tracking as a vulnerability assessment tool for drinking water production

Particle tracking as a vulnerability assessment tool for drinking water production

Particle tracking as a vulnerability assessment tool for drinking water production

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