A Field Examination of Snowmelt Infiltration into Sloping Frozen Soils in the Canadian Rockies
Bibliographic record
Abstract
There is little research on infiltration into seasonally frozen soils on mountain hillslopes and few evaluations of infiltration model performance in this environment exist. As a result, the application of existing infiltration estimation methods developed in level environments is uncertain for estimating spring runoff in mountain basins. A field study was conducted in the Canadian Rockies using eight years of snowpack, liquid soil moisture and temperature profile observations from steep north-facing and south-facing hillslopes. Seasonal infiltration depths and initial soil saturation were estimated with the help of soil freezing characteristic curves, soil texture and timeseries of volumetric water content and soil temperature. Infiltration was found to primarily follow the limited case postulated by Popov (1972), with only one year, at one site, undergoing unlimited infiltration where all meltwater infiltrated. Restricted infiltration did not occur, despite ice layers under the snowpack, which can impede water entry to soils. Infiltration was estimated using an equation for the limited case developed from extensive observations of seasonal infiltration, initial soil saturation and peak SWE in Canadian prairie agricultural fields (Gray et al., 1985b). Whilst this equation accurately estimated infiltration depths, it was unsuitable for application at the study site due to a statistical association between its driving variables. Initial soil saturation did not have a statistically significant influence on infiltration depths at these sites and so a simpler single-variable infiltration equation to estimate infiltration depths based on peak SWE was developed using linear regression and was found to have good predictive capability. Alternative approaches using modelled cumulative melt or infiltration opportunity time to estimate infiltration depths also had good predictability. Runoff depths estimated from a water balance assuming negligible evaporation and sub-surface drainage were reliably predicted using peak SWE or cumulative melt depths by single-variable infiltration equations in the absence of soil moisture, texture, aspect, or slope information. The results provide insights into how snowmelt runoff on hillslopes may be estimated from snowpack accumulation information that has been observed in cold region mountains, despite the complexity of hillslope hydrology and frozen soil infiltration processes.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".