Investigation of Long-Term Climate and Streamflow Patterns in Ontario
Bibliographic record
Abstract
To develop mitigation and adaptation strategies for undesired consequences of climate change, it is important to understand the changing hydrological and climatological trends in the past few decades. Although the changing climate is a cause of concern for the entire planet, its effects can vary significantly on a regional scale. Canada has experienced a rapid rise in the annual mean surface air temperature in the past decades. The current study aims to investigate trends in monthly mean precipitation, rainfall, snowfall, maximum and minimum temperature, as well as baseflow, surface runoff, and total streamflow values for the province of Ontario, Canada. To the best of the author’s knowledge, a similar study involving rural and urban watersheds, that quantifies the impact of changing climate on temperature and other hydrological processes over a period ranging from 1968 to 2017, has not yet been conducted for Ontario. Man-Kendall trend test was used to analyze trends in the above mentioned climatic and hydrometric parameters for rural and urban watersheds situated in the northern and southern parts of Ontario. The results of this study indicate that the mean monthly minimum temperatures for rural watersheds situated in southern Ontario have increased significantly for the winter and summer months, which may have caused an increase in snowmelt and consequently the streamflow for the winter months in the region. Unlike the watersheds in southern Ontario, the northern watersheds witnessed relatively fewer instances of significant changes in mean monthly temperatures, and in some cases, declining rates have been noted. Similarly, only a few watersheds in the north saw a substantial drop in baseflow over the summer months. For nearly all the months, the average monthly minimum and maximum temperatures were found to increase for urban watersheds. The streamflow, baseflow, and surface runoff increased, likely due to rapid urbanization, resulting in a lower infiltration rate. These results will contribute towards the decision-making processes and development of alternate water management policies within the province, taking into account the regional variations in climate change’s impact on the hydrology of Ontario’s watersheds.
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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 | 0.003 |
| 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".