Hydrologic and water isotope characterization of a regulated Canadian Shield river basin
Bibliographic record
Abstract
Abstract Stable water isotope surveys have increasingly been integrated into river basins studies, but fewer have used them to evaluate impact of hydropower regulation. This study applies hydrologic and water isotope survey approaches to a Canadian Shield river basin with both regulated and natural flows. Historical streamflow records were used to evaluate the influence of three hydroelectric reservoirs and unregulated portions of the basin on downstream flows and changes in water level management implemented after an extreme flood year (1979). In 2013, water isotope surveys of surface and source waters (e.g., rainfall, groundwater, snowmelt) were conducted to examine spatial and temporal variation in contributions to river flow. Seasonal changes in relative groundwater contribution were assessed using a water‐isotope mass balance approach. Within the basin, two regulated reservoirs exhibited inverted hydrographs with augmented winter flows, whereas a third exhibited a hydrograph dominated by spring snowmelt. In 2013, spatial variation in rain‐on‐snow and air temperatures resulted in a critical lag in snowmelt initiation in the southern and northern portions of the basin resulting in a dispersed, double peak spring hydrograph, contrasting with 1979 when a combination of rain‐on‐snow and coincident snowmelt led to the highest flood on record. Although eastern basin reservoirs become seasonally enriched in δ18O and δ2H values, unregulated western basin flows remain less variable due to groundwater driven baseflow with increasing influence downstream. Combined analysis of historical streamflow (e.g., flood of 1979, drought of 2010) and the 2013 water isotope surveys illustrate extreme meteorological conditions that current management activities are unable to prevent. In this study, the influence of evaporative fractionation on large surface water reservoirs provides important evidence of streamflow partitioning, illustrating the value of stable water isotope tracers for study of larger catchments.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".