Antecedent moisture conditions and catchment morphology as controls on spatial patterns of runoff generation in small forest catchments
Bibliographic record
Abstract
Summary Although existing empirical studies of runoff generation in headwater catchments have provided evidence of runoff mechanisms, contributing sources and active flowpaths from forest catchments around the world, our understanding of how hydrologic and biological processes vary and aggregate in space within headwater systems remains poor. In this study, we examine the spatial patterns of storm runoff generation from eight small nested forest catchments ranging in size from 7 to 147 ha, as a function of antecedent moisture conditions and catchment morphology. The catchments, located in the formerly glaciated terrain of Mont Saint-Hilaire, Quebec, Canada, are complex in both their topographic and subsurface characterization. Hydrologic response from the eight catchments shows a strong nonlinear change with antecedent moisture conditions consistent with the hypothesis of different ‘states-of-wetness’. With the transition from wet to dry conditions, local groundwater stores become depleted in some ephemeral catchments, variable source areas shrink and new-water delivered by shallow-subsurface stormflow and the transient development of perched water in valley-bottoms can account for much larger percentages of total runoff (up to 76% of total runoff). For the five storm events, no consistent pattern in percent new-water delivery was observed. However, for the storms observed under dry conditions, larger magnitudes of new water were generated from the three largest catchments attributable to basin morphology, while storms observed under wet conditions exhibited no consistent pattern, with larger variability among the smaller catchments. The results presented here illustrate the complexity of influences of antecedent moisture conditions and catchment morphology on spatial patterns of runoff generation in headwater systems.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 teacher head, 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".