Water storage dynamics and runoff response of a boreal Shield headwater catchment
Bibliographic record
Abstract
Abstract Thresholds in terrestrial water storage were quantified to explain differences in observed rainfall‐runoff relationships for a 71·5 ha research catchment in northwestern Ontario, Canada. Using terrain analysis techniques, the catchment was partitioned into discrete hydrologic response units (HRUs). Unsaturated and saturated water storage was calculated for depression and midslope HRUs using continuous hydrometric measurements and a depth function for drainable porosity. The relationship between total water storage in these HRUs and catchment discharge was then examined for evidence of threshold behaviour. Piecewise regression analysis (PRA) was used to quantify a breakpoint in the nonlinear storage‐discharge relationship, with separate linear regressions explaining the change in discharge with storage above and below this value. Above the breakpoint, a large increase in discharge is associated with a small increase in storage. Our results show that event‐scale hydrologic response displays a threshold relationship with antecedent storage and maximum event storage in the terminal depression in the catchment. Our results also suggest that predictions of event runoff improve when storage excesses from upslope depressions are explicitly routed through the catchment taking into consideration storage deficits in downslope HRUs that may impede flow. The application of landscape delineation, hydrometric monitoring and PRA to model S‐Q relationships is demonstrated to be an objective means of quantifying the transition between the two distinct hydrologic regimes in this catchment and provides new insight into how S‐Q dynamics govern the hydrologic functioning of bedrock‐dominated catchments. Copyright © 2011 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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".