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Record W7049263077

Monitoring des flux d'eau souterraine et de contaminants au sein d'aquifères hétérogènes

2019· dissertation· en· W7049263077 on OpenAlexaboutno aff

Bibliographic record

VenueORBi (University of Liège) · 2019
Typedissertation
Languageen
FieldEngineering
TopicPhotocathodes and Microchannel Plates
Canadian institutionsnot available
Fundersnot available
KeywordsGroundwaterAquiferContaminationGroundwater flowDispose patternGroundwater pollutionMODFLOWGroundwater model
DOInot available

Abstract

fetched live from OpenAlex

Groundwater is one of the most important natural resources of our planet and it requires appropriate management and protection in order to guarantee its availability for future generations. From a water quality point of view, old industrial activities and modern accidental releases have locally impacted groundwater resource. Management of these contaminated aquifers has historically relied on comparison between measured contaminant concentrations in groundwater and threshold values. This approach is a necessary early characterization step but is totally insufficient to fully investigate the contaminants behavior in groundwater and to quantify the associated risks. Since the beginning of the years 2000, a consensus has been growing among the scientific, technical and decision makers’ community on the fact that management of contaminated aquifers should be performed in terms of contaminant flux metrics. Accordingly, it has become necessary to dispose of techniques able to accurately measure mass fluxes and mass discharges of contaminants in aquifers. Contaminant mass flux usually relies on measurements of both groundwater flux and contaminant concentration in monitoring wells drilled in the aquifer of concern. Research efforts must lead to the proposition of new solutions, methodologies and techniques, in particular for measuring groundwater fluxes. In this work, the Finite Volume Point Dilution Method (FVPDM), is proposed as an innovative single-well method for monitoring groundwater fluxes in aquifers. Mathematical basis and a first analytical solutions allowing to interpret FVPDM experiments performed in steady state groundwater flow conditions were already developed and validated on a few field applications. In this research, a generalized FVPDM interpretation framework for monitoring groundwater fluxes over time is proposed, based on a new finite difference expression proposed to calculate groundwater fluxes from FVPDM experiments performed in transient groundwater flow fields. In a first step, the FVPDM technique was successively applied in various laboratory and field experiments allowing to define its accuracy, precision and resolution under transient groundwater flow conditions. A first lab-scale flow tank experiment demonstrated the accuracy of the FVPDM for groundwater fluxes measurements in both steady and transient state flow conditions. Difference between the prescribed water flux in the flow tank and the measured water flux using FVPDM was as low as 0.15 %. In a second experiment the FVPDM was applied to measure groundwater fluxes on several fractured zones of an open well installed in a crystalline rock aquifer. This constitutes the first successful application of the FVPDM technique in a fractured aquifer, using straddle packers. The classical point dilution method (PDM) was also applied during this experiment, under the same groundwater flow conditions to compare the sensitivity and uncertainty of both methods. It demonstrated that FVPDM generally provides a better precision than PDM but it may require longer experimental durations. A third FVPDM experiment undertaken in an alluvial aquifer allowed to validate in the field the method for monitoring rapidly changing groundwater fluxes. This first series of experiment allowed to validate the FVPDM as a fully operational method for measurements of groundwater fluxes for a wide spectrum of experimental and flow conditions. In a second step, three field-scale applications of the method were performed. The first relates to direct groundwater fluxes measurements in a sub-permafrost aquifer located in the remote territories of northern Quebec. These measurements came in support to a thermo-hydrodynamic model of a watershed where permafrost thaw occurs. This specific application demonstrated the robustness and versatility of the FVPDM. In a second field application, the FVPDM was used to monitor, under controlled conditions a solute mass discharge experiment undertaken in a heterogeneous alluvial aquifer at a series of control planes in order to compare different methods for calculating the total mass discharge based on discrete groundwater fluxes and concentration measurements. In a third application, the FVPDM was successfully used in a groundwater pollution investigation to characterize highly transient groundwater flows and pollutant mass fluxes within a coastal aquifer influenced by marked tides. The results of this experiment allowed to improve and refine the conceptual site model and provided crucial information for optimizing further investigations and risk mitigation measures at this polluted site. The FVPDM was applied in a wide range of environmental contexts, of application scales, of experimental setups, of aquifer types, of time scales, of groundwater flow conditions, and for both research and consultant-type purposes. The FVPDM was proven to be a robust and versatile method that provides high-quality reliable groundwater flux data for general hydrogeological characterizations and for contaminant mass fluxes monitoring, even under highly transient flow conditions. From a more general perspective, this research demonstrated the great importance and the huge benefits of having direct and reliable in situ measurements of groundwater fluxes for any kind of hydrogeological studies. This research proves once more the value of undertaking mass flux measurements for characterization of contaminated sites, risk assessment and design of risk mitigation measures.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.332
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.017
GPT teacher head0.238
Teacher spread0.221 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2019
Admission routes1
Has abstractyes

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