Drought impacts on Canadian prairie wetland snow hydrology
Bibliographic record
Abstract
Abstract Droughts affect the Canadian prairies on a regular basis. The drought of 1999–2005 was the most recent one and was the most severe on record for part of the region. It was characterized by lack of precipitation, desiccation of agricultural soils, decline in groundwater tables and depletion of surface water supplies. The effects on wetlands were particularly severe, with many wetlands completely drying out. The physically based cold regions hydrological modelling (CRHM) platform was used to analyse the impacts of this recent drought on water flow to and storage within a small Canadian prairie wetland. Model simulations were conducted for a small closed basin for the drought period of 1999–2005 and the relatively wet period of 2005–2006. The basin consists of a cultivated upland, draining into a glacially formed pothole depression with no outlet. The wetland fills the depression in wet years and is underlain by a heavy glacial till that impedes groundwater exchange. Results from the observations and model outputs showed that much lower precipitation and snow accumulation, shorter snow‐covered duration, enhanced winter evaporation, and much lower discharge to the wetland from basin snowmelt runoff developed in the severe drought years of 1999–2002. As a result, there were only 14·9, 3·7, and 14·4 mm of snowmelt runoff for the springs of 2000, 2001, and 2002, respectively. Compared to the 68·2 mm of melt‐water discharge in the spring of 2006, discharge to the wetland was 78, 95, and 79% less for these years. This is consistent with the observed water level in the wetland, which shows dramatic decline over this period. CRHM was used to investigate the potential impact of snow management as a tool to enhance runoff to the wetland during droughts. Model runs parameterized with suppressed vegetation in the cultivated land surrounding the wetland showed increased blowing snow transport to the wetland from an area exceeding the basin area that resulted in greater snow accumulation in and melt‐water supply to the wetland. Copyright © 2008 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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".