Assessing trends in temperature, precipitation and streamflow due to climate change in Credit River watershed
Bibliographic record
Abstract
'Full text:' Studies on climate change at Natural Resources Canada showed that average temperature in Canada increased by 0.9°C since 1948 and further estimated that Ontario will warm by an average of 2°C to 5°C within the next 75 to 100 years. The climate change is linked to the anthropogenic activities which are understood to increasing green house gasses concentrations in the Earth's atmosphere thereby warming the planet. The warming is further related to affecting the components of hydrological cycle such as precipitation intensities, durations, snowfall, streamflow peaks, low flows etc. According to the Intergovernmental Panel on Climate Change (IPCC) Technical Paper on Climate Change and Water “Observational records and climate projections provide abundant evidence that freshwater resources are vulnerable and have the potential to be strongly impacted by climate change, with wide-ranging consequences for human societies and ecosystems.” The Ministry of Natural Resources projected temperature and precipitation changes for Southern Ontario for period 2075-2100 indicate 3-5°C higher summer and 5-6°C higher winter temperatures and ±10% change in annual precipitation from 1971-2000 using higher green house gas emission scenario (A2). However, the changes in climate and their effect on hydrological cycle could differ locally and these effects could be assessed using local historical data. Therefore, the Valley Conservation Authority initiated a study to assess how the climate change has affected the Credit River watershed by investigating trends in the historical temperature, precipitation and streamflow data sets. The temperature trends were analysed for mean, maximum and minimum temperatures on annual and monthly basis from nine meteorological stations located within or close to the Credit River watershed. The precipitation data from the same nine meteorological stations were used to analyse a) Intensity-Duration-Frequency (IDF) patterns of 1, 2, 6, 12 and 24 hr rainfall duration and 2, 5, 10, 50 year recurrence intervals; b) extreme annual precipitation for 1, 2, 6, 12 and 24 hr duration; and c) mean monthly and seasonal precipitation. The streamflow trend analysis was conducted at nine locations across the Credit River watershed on monthly, seasonal and annual basis. The visual interpretation of the time series plotting and statistical testing of the data for identifying trends has been completed for the study and the results from the analysis are being investigated. (author)
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 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".