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On the use of the ground water fluxes for hydraulic tomography: Theoretical and field-based assessments

2020· article· en· W3160092837 on OpenAlexaffabout
Behzad Pouladiborj, Olivier Bour, Niklas Linde, Daniel Paradis, Jean-Marc Ballard, Jérôme de La Bernardie, Nataline Simon, Cynthia Lee, Laurent Longuevergne, René Lefebvre

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicFlow Measurement and Analysis
Canadian institutionsInstitut National de la Recherche ScientifiqueGeological Survey of CanadaNatural Resources Canada
Fundersnot available
KeywordsHydraulic conductivityAquiferGroundwaterGroundwater flowGroundwater modelGeologySoil scienceHydraulic headTomographySlug testThermal conductionGeotechnical engineeringHydrology (agriculture)Environmental scienceMaterials scienceOpticsPhysics

Abstract

fetched live from OpenAlex

<p>Hydraulic tomography is known for imaging hydraulic conductivity of aquifers. In hydraulic tomography, the aquifer is stressed sequentially at several locations with pumping or slug tests while hydraulic heads are observed in different points. These hydraulic head data along with a numerical model are then used to reconstruct the hydraulic conductivity distribution of the aquifer through inversion process. The reconstructed distribution usually represents smooth-low resolution model of hydraulic conductivity which may be suitable for representation of groundwater flow with limited applicability to transport problems. Here, we investigate the added value of using groundwater fluxes measurement for the reconstruction of hydraulic conductivity in tomographic experiment. Vertical profile of groundwater flux may be estimated using active fiber optic distributed temperature sensor (FO-DTS) methods with FO cables installed by direct push so as it is in direct contact with formation. In active FO-DTS, FO cable is heated and heat is transported by conduction and convection. So different water fluxes result in different temperature behavior. This study is carried out in two parts. First, we conducted a synthetic analyze where we used a sequence of synthetic multivariate Gaussian aquifers with different tomographic configurations and datasets. This analysis showed that joint inversion of groundwater fluxes and hydraulic heads leads to better hydraulic conductivity resolution than using hydraulic heads solely. Inversion of groundwater fluxes alone is also superior than using only hydraulic heads. Then, insights gained from the synthetic study were used to guide the implementation of a field study at the Saint-Lambert experimental site located 40 km south of Quebec City, Canada. The tomography experiment was performed between 3 wells closely spaced (between 5 and 9 m) and two active FO-DTS cables. FO cables were installed vertically by a direct push drilling technique at mid-point between the central pumping well and two observation wells. Discrete intervals along the observation wells were also isolated with packers to monitor temperature and hydraulic heads at different depths in these two screened observational wells. First, the aquifer was constrained to pumping continuously for 24 hours at a constant rate of 10 LPM with simultaneously recording temperature (passive mode) and hydraulic heads in 8 discrete well intervals and in the pumping well itself as well as along the 2 FO-DTS with approximate resolution of 25 cm. Then, by analyzing the piezo-metric heads and making sure that steady-state conditions were achieved, the pumping was held at the same rate but heat was injected to fiber optic cables (active mode) for another 64-hour period. After this period, heating and pumping were stopped. Preliminary results show the feasibility of the active FO-DTS in capturing varying groundwater fluxes with depth, as reflected in the different temporal temperature trend. These temperature trends will be used to estimate the vertical groundwater flux profile from these temperature temporal trends at a vertical resolution of approximately 25 cm. Then estimated fluxes will be used for hydraulic tomography. Those experimental results along with the synthetic analyze are shown to be promising in improving characterization of hydraulic conductivity of aquifers.</p>

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.575
Threshold uncertainty score0.208

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 head0.037
GPT teacher head0.228
Teacher spread0.191 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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".

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Citations0
Published2020
Admission routes2
Has abstractyes

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