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Record W2948811738

Characterization of the Heterogeneous Flow and Pollutant Transfer in the Unsaturated Zone in the Fluvio-glacial Deposit. Four Decades of Progress in Monitoring and Modeling of Processes in the Soil-Plant- Atmosphere System: Applications and Challenges.

2013· article· en· W2948811738 on OpenAlexaff
Thierry Winiarski, Laurent Lassabatère, Rafaël Angulo-Jaramillo, David Goutaland

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicSoil and Unsaturated Flow
Canadian institutionsImpact
Fundersnot available
KeywordsGeologyInfiltration (HVAC)Vadose zoneElectrical resistivity tomographyGlacial periodHydrology (agriculture)GeomorphologySoil scienceSoil waterGeotechnical engineeringElectrical resistivity and conductivity
DOInot available

Abstract

fetched live from OpenAlex

Infiltration basins are part of the best management practices. They are aimed at infiltrating stormwater to prevent additional collection and treatment through rainwater systems. In the suburbs of Lyon (France), many of these infiltration basins were built over fluvio-glacial deposit. These basins have been the subject of research programs on vadose zone flow and fate of pollutants. This study focuses on the impact of the heterogeneity of the fluvio-glacial deposit on both flow pattern and solute transfer. A proper geological and sedimentological description is first proposed to characterize the efficient water transfer properties of the fluvio-glacial deposit at the work scale (1 ha). The local geological and sedimentological architecture of the deposit and its lithofacies were investigated locally through trenches using both particle size analysis and sedimentological approach. This information was extended to the whole work by combining several geophysical techniques, i.e. GPR, electric resistivity and seismic refraction tomography (data not shown). Then water infiltration experiments were performed on each lithofacies to derive the hydrodynamic properties through BEST algorithm (Beerkan estimation of Soil Transfer properties), leading to the corresponding hydrofacies. In addition, soil-column and batch experiments were performed to estimate hydrodispersive parameters by tracer experiments and the geochemical properties of lithofacies for a model pollutant, copper (Cu). All these data were implemented into Hydrus to model flow and solute transfer through a 2D soil profile with a precise description of the hydrofacies at the basin scale (flow domain 14x2 m2). The results are highly relevant because they emphasize different types of preferential flow due to either the presence of capillary barriers, drainage layers or pipe flow, which may be responsible for the enhancement of pollutant transfer. In particular, they show that sand lenses may play an important role whereas unconnected gravels may have insignificant effect on flow. This methodology may help in understanding the mechanisms which that are responsible for preferential solute transfer. A sensitivity analysis combining the distribution of lithofacies, the soil initial water content and unsaturated hydraulic properties allows bettering understanding the development of preferential flows across the vadose zone underneath the basin. This data is of great interest in terms of the optimization of basin infiltration monitoring.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.197
Teacher spread0.180 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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
Published2013
Admission routes1
Has abstractyes

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