Hydrological dynamics of prairie pothole wetlands: Dominant processes and landscape controls under contrasted conditions
Bibliographic record
Abstract
Abstract Numerous studies have examined the impact of prairie pothole wetlands on overall watershed dynamics. However, very few have looked at individual wetland dynamics across a continuum of alteration status using subdaily hydrometric data. Here, the importance of surface and subsurface water storage dynamics in the prairie pothole region was documented by (1) characterizing surface fill–spill dynamics in intact and consolidated wetlands; (2) quantifying water‐table fluctuations and the occurrence of overland flow downslope of fully drained wetlands; (3) assessing the relation (or lack thereof) between intact, consolidated or drained wetland hydrological behaviour, and stream dynamics; and (4) relating wetland hydrological behaviour to landscape characteristics. Focus was on southwestern Manitoba, Canada, where ten intact, three consolidated, seven fully drained wetlands, and a nearby creek were monitored over two years with differing antecedent storage conditions. Hourly hydrological time series were used to compute behavioural metrics reflective of year‐specific and season‐specific wetland dynamics. Behavioural metrics were then correlated to wetland physical characteristics to identify landscape controls on wetland hydrology. Predictably, more frequent spillage or overland flow was observed when antecedent storage was high. Consolidated wetlands had a high degree of water permanence and a greater frequency of fill–spill events than intact wetlands. Shallow and highly responsive water tables were present downslope of fully drained wetlands. Potential wetland–stream connectivity was also inferred via time‐series analysis, while some landscape characteristics (e.g., wetland surface, catchment area, and storage volume) strongly correlated with wetland behavioural metrics. The nonstationarity of dominant processes was, however, evident through the lack of consistent correlations across seasons. This, therefore, highlights the importance of combining multiyear high‐frequency hydrometric data and detailed landscape analyses in wetland hydrology studies.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.003 |
| 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 teacher head, 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".