Hydrological response of weathered clay‐shale slopes: water infiltration monitoring with time‐lapse electrical resistivity tomography
Bibliographic record
Abstract
Abstract This work presents an attempt to monitor water infiltration and subsurface flow within a clay‐shale landslide using time‐lapse electrical resistivity tomography (ERT). A rainfall experiment was carried out on a plot of 100 m2at the Laval landslide in the Draix experimental catchments (ORE Draix, South French Alps) in order to characterize the spatial and temporal development of water circulation in the soil and to identify when steady‐state flow conditions are reached. The experiment was conducted during 67 h with initial unsaturated conditions in the slope. The apparent electrical resistivity values were inverted with a time‐lapse approach using several cross models. The results indicate a significant decrease in resistivity (−18%) compared to the initial state in the rain plot. Downslope progression of negative resistivity anomalies is imaged suggesting that vertical and subsurface lateral flows have developed. About 21 h after the start of the rain experiment, a constant level of resistivity values is observed indicating that the hydrological system reached steady‐state flow conditions. This observation is consistent with ground water level observations and chemical tracer analysis. Computed differences in time of steady‐state conditions highlight possible preferential flows near the landslide toe. A hydrological concept of functioning of the slope is proposed, and apparent saturated hydraulic conductivity (Ksof 1·7 × 10−4m × s−1) is computed from the steady‐state times. This study demonstrates the potentiality of ERT monitoring to monitor water infiltration in clay‐shale slopes and the high water transfer capacity of reworked clay‐shale material. Copyright © 2011 John Wiley & Sons, Ltd.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".