UNDERSTANDING HYDROLOGICAL PROCESSES AND WATER FLUXES LINKING WETLAND PONDS AND GROUNDWATER IN THE PRAIRIE POTHOLE REGION
Bibliographic record
Abstract
Understanding surface water-groundwater interaction processes and quantification of hydrological fluxes remains a scientific challenge in hydrology. However, comprehensive understanding of groundwater interactions with the surface and more accurate estimates of hydrologic fluxes are essential for water resources and environmental management and policy. Numerous hydrological studies conducted in the glaciated Prairie Pothole region focused mainly on the importance of wetland ponds and their relationship with shallow groundwater in the till using physical, geophysical and water chemistry measurements, and numerical models. In this thesis, I combined field observations, isotopes of water and geochemical tracers (δ2H, δ18O, lc-excess, 3H and Cl-, SO42-), to develop a physical isotope model to quantify water fluxes, examine interactions between surface water and the relatively deeper intertill aquifers (< 50 m), and assess the pathways of water and solutes from the ponds, uplands and lowlands areas hummocky landscape. My field campaign spanned between 2013 and 2016 at the St Denis National Research Area in Saskatchewan, Canada, where additional soil, hydrometric and water isotope data were collected to complement the existing previously collected stable isotope, hydraulic and hydrometric data. The data show that water isotope compositions of ponds are reflective of seasons and residence time, and this property is useful for quantifying spatial surface water fluxes. Pond water infiltration rates estimated from the new model show that ephemeral ponds have the highest outflow rates, and pond-subsurface interactions can be determined without groundwater heads. The water isotopes and hydrometric measurements indicate that interaction between ponds and the intertill aquifer is limited to ponds upland, and water from ephemeral ponds are the dominant source of depression-focused recharge to the intertill aquifer. The stable isotopes and dissolved ions data showed that rapid downward advective movement of water occurs in the shallow weathered zone throughout the till and at all landscape positions and this water could serve as recharge water to the aquifer. The work represents a distinct contribution to the literature regarding our understanding of the hydrological processes linking wetland ponds and groundwater in the prairie pothole region.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".