Wetlands and low‐gradient topography are associated with longer hydrologic transit times in Precambrian Shield headwater catchments
Bibliographic record
Abstract
Abstract The estimation of hydrologic transit times in a catchment provides insights into the integrated effects of water storage, mixing dynamics, and runoff generation processes. There has been limited effort to estimate transit times in southern boreal Precambrian Shield landscapes, which are characteristically heterogeneous with surface cover including till, thin soils, bedrock outcrops, and depressional wetland features that play contrasting hydrologic roles. This study presents approximately 3.5 years of precipitation and streamflow water isotope data and estimates mean transit times (MTTs) and the young water fraction ( p y ) across six small catchments in the Muskoka‐Haliburton region of south‐central Ontario. The main objectives were to define a typical range of MTTs for headwater catchments in this region and to identify landscape variables that best explain differences in MTTs/ p y using airborne light detection and ranging and digital terrain analysis. Of the transit time distributions, the two parallel linear reservoir and gamma distributions best describe the hydrology of these catchments, particularly because of their ability to capture more extreme changes related to events such as snowmelt. The estimated MTTs, regardless of the modelling approach or distribution used, are positively associated with the percent wetland area and negatively with mean slope in the catchments. In this landscape, low‐gradient features such as wetlands increase catchment scale water storage when antecedent conditions are dryer and decrease transit times when there is a moisture surplus, which plausibly explains the increases in MTTs and mean annual runoff from catchments with significant coverage of these landscape features.
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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) | 0.001 | 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 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".