Ephemeral Ponds: Are They the Dominant Source of Depression‐Focused Groundwater Recharge?
Bibliographic record
Abstract
Abstract Depression‐focused recharge is a concept proposed to explain groundwater recharge in the prairie regions of North America. Topographic depressions in this hummocky landscape collect blowing snow and snowmelt, and occasional runoff during rainfall events. Wetland ponds that form in these depressions lose water to evaporation and infiltration. Some of this infiltration contributes to groundwater recharge, both to shallow aquifers in the weathered near‐surface, and to underlying confined intertill aquifers. Here we focus on understanding recharge to the confined aquifers, which supply water for farms and rural communities. The isotopic composition of water in these aquifers shows little or no evaporative enrichment and is inconsistent with the average isotopic composition of the ponds. This observation appears to contradict the depression‐focused recharge model. In this field study, we examine the isotopic composition of diverse types of wetland ponds and groundwater at the St. Denis National Wildlife Area, Saskatchewan, Canada. We use hydraulic head data to identify potential recharge and discharge ponds. Water in permanent recharge ponds that do not dry out every year have distinctly different isotopic signatures from the aquifers, suggesting that they cannot be the dominant source of recharge. Water in ephemeral recharge ponds, which are small and dry out quickly, have isotopic signatures identical to those of aquifers. We propose that ephemeral recharge ponds are the dominant source of depression‐focused groundwater recharge in the prairies. We discuss why permanent recharge ponds may not be the main source of groundwater recharge and summarize our findings in a revised conceptual model.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".