Soil partitioning and surface store controls on spring runoff from a boreal forest peatland basin in north-central
Bibliographic record
Abstract
The mid- to high-boreal forest in Canada occupies the discontinuous permafrost zone, and is often underlain by glaciolacustrine sediments mantled by a highly porous organic mat. The result is a poorly drained landscape dominated by wetlands. Frost-table dynamics and surface storage conditions help to control runoff contributions from various landscape elements, hydrological linkages between these elements, and basin streamflow during spring snowmelt. Runoff components and pathways in a forested peatland basin were assessed during two spring snowmelts with contrasting input and basin conditions. Runoff from relatively intense melt (up to 16 mm day1) on slopes with limited soil thawing combined with large pre-melt storage in surface depressions to produce high flows composed primarily of meltwater (78 % of the 0Ð29 m3 s1 peak discharge) routed over wetland surfaces and through permeable upper peat layers. Melt intensity was less in the subsequent year (maximum of 10 mm day1) and active layer development was relatively greater (0Ð2 m deeper at the end of spring melt), resulting in less slope runoff. Coupling of reduced slope contributions with lower storage levels in basin wetlands led to relatively subdued streamflows dominated by older water (73 % of the 0Ð09 m3 s1 peak discharge) routed through less-permeable deeper peat layers and mineral soil. Interannual differences in runoff conditions provide important insight for the development of distributed hydrological models for boreal forest basins and into potential influences on biogeochemical cycling in this landscape under a warming climate. Copyright 2001 John Wiley & Sons, Ltd. KEY WORDS boreal forest; spring melt; depression storage; hydrograph separation; permafrost; ground thawing; wetlands
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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 | 0.000 |
| 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".