Modelling water quality of the Pike River watershed under four climate change scenarios
Bibliographic record
Abstract
The impacts of climate change on the hydrology and water quality of the Pike River watershed, an important contributor of nutrient loads to northern Lake Champlain, were predicted for the time horizon 2041-2070. Four water quality scenarios were simulated using a version of the Soil and Water Assessment Tool (SWAT) modified to suit Québec's agroclimatic conditions. Three of the scenarios were generated using climates simulated with the Fourth Canadian Regional Climate Model (CRCM4). The fourth scenario was generated using the climate simulated with the Arpege Regional Climate Model. SWAT was independently calibrated for the period 2001-2003, and then validated for the periods of 2004-2006 and 1980-2000, before inputting the climate scenarios. Potential mean changes predicted by these scenarios were then analysed for the evapotranspiration, surface and subsurface runoff, stream flow, sediment yields, and total phosphorus and nitrogen.After calibration, mean annual evapotranspiration, surface and subsurface flow as well as water percolation were found to correspond satisfactorily with the hydrology of the basin. Likewise, monthly predicted stream flow compared reasonably well with observed stream flow. The performance of SWAT in simulating sediment and nutrient yields was clearly improved after calibration but did not always reach standards of acceptability. As for climate change results, only one scenario predicted a significant increase in mean annual stream flow and nutrient loadings. However, when considering shorter time spans, simulations predicted significant changes including a winter stream flow two to three times greater than current stream flow and earlier spring floods. The identified causes are the early onset of spring snowmelt, a greater number of rainfall events and snowmelt episodes caused by higher winter and spring temperatures. In contrast, peak flows in April, as well as summer stream flow, appear to decrease but not always significantly. Nutrient delivery to the lake significantly increased in winter and occurred earlier in the year as a consequence of hydrological changes. A three- to four-fold increase in subsurface flow was also observed in winter which may increase nutrient losses through this pathway.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".