Controls on runoff from a partially harvested aspen‐forested headwater catchment, Boreal Plain, Canada
Bibliographic record
Abstract
Abstract The water balance and runoff regime of a 55 ha aspen‐forested headwater catchment located on the Boreal Plain, Alberta, Canada (55·1°N, 113·8°W) were determined for 5 years following a partial timber harvest. Variability in precipitation provided the opportunity to contrast catchment water balances in relatively dry (<350 mm year−1), wet (>500 mm year−1), and average precipitation years. In most years, the catchment water balance was dominated by soil water storage, evapotranspiration losses, and vertical recharge. In 1997, despite near‐average annual precipitation (486 mm), there was significant runoff (250 mm year−1) with a runoff coefficient of 52%. A wet summer and autumn in the preceding year (1996) and large snow accumulation in the spring (1997) reduced the soil water storage potential, and large runoff occurred in response to a substantial July rainfall event. Maps of the surface saturated areas indicated that runoff was generated from the uplands, ephemeral draws, and valley‐bottom wetlands. Following 1997, evapotranspiration exceeded precipitation and large soil water storage potentials developed, resulting in a reduction in surface runoff to 11 mm in 1998, and <2 mm in 1999–2001. During this time, the uplands were hydrologically disconnected from ephemeral draws and valley‐bottom wetlands. Interannual variability was influenced by the degree of saturation and connectivity of ephemeral draws and valley wetlands. Variability in runoff from tributaries within the catchment was influenced by the soil water storage capacity as defined by the depth to the confining layer. An analysis of the regional water balance over the past 30 years indicated that the potential to exceed upland soil water storage capacity, to connect uplands to low‐lying areas, and to generate significant runoff may only occur about once every 20 years. The spatial and temporal variability of soil water storage capacity in relation to evaporation and precipitation deficits complicates interpretation of forest harvesting studies, and low runoff responses may mask the impacts of harvesting of aspen headwater areas on surface runoff in subhumid climates of the Boreal Plain. Copyright © 2005 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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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".