Snowmelt Infiltration and Runoff From Seasonally Frozen Hillslopes in a High Mountain Basin
Bibliographic record
Abstract
ABSTRACT There is relatively 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 8 years of snowpack, liquid soil moisture, and temperature profile observations from steep north‐facing and south‐facing slopes. Seasonal infiltration was calculated using soil freezing characteristic curves, timeseries of soil volumetric water content and temperature. Infiltration was found to primarily follow the limited case postulated by Popov (1972), with only 1 year at one site undergoing unlimited infiltration where nearly all meltwater infiltrated. 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. Whilst this equation accurately estimated infiltration depths on these mountain hillslope sites, it was unsuitable for application due to a statistical association between its driving variables. Initial soil saturation had no 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 and found to have good predictive capability. Alternative approaches using modelled cumulative melt or infiltration opportunity time 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 estimating snowmelt runoff on hillslopes from snowpack accumulation 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 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".