Factors affecting the spatial pattern of bedrock groundwater recharge at the hillslope scale
Bibliographic record
Abstract
Abstract The spatial patterns of groundwater recharge on hillslopes with a thin soil mantle overlying bedrock are poorly known. Complex interactions between vertical percolation of water through the soil, permeability contrasts between soil and bedrock and lateral redistribution of water result in large spatial variability of water moving into the bedrock. Here, we combine new measurements of saturated hydraulic conductivity of soil mantle and bedrock of the well‐studied Panola Mountain experimental hillslope with previously collected (sub)surface topography and soil depth data to quantify the factors affecting the spatial pattern of bedrock groundwater recharge. We use geostatistical characteristics of the measured permeability to generate spatial fields of saturated hydraulic conductivity for the entire hillslope. We perform simulations with a new conceptual model with these random fields and evaluate the resulting spatial distribution of groundwater recharge during individual rainstorms and series of rainfall events. Our simulations show that unsaturated drainage from soil into bedrock is the prevailing recharge mechanism and accounts for 60% of annual groundwater recharge. Therefore, soil depth is a major control on the groundwater recharge pattern through available storage capacity and controlling the size of vertical flux. The other 40% of recharge occurs during storms that feature transient saturation at the soil‐bedrock interface. Under these conditions, locations that can sustain increased subsurface saturation because of their topographical characteristics or those with high bedrock permeability will act as hotspots of groundwater recharge when they receive lateral flow. Copyright © 2015 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 | 0.001 |
| 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) | 0.001 | 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".