Estimating areal snowmelt infiltration into frozen soils
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Bibliographic record
Abstract
Abstract An algorithm for estimating areal snowmelt infiltration into frozen soils is developed. Frozen soils are grouped into classes according to surface entry condition as: (a) Restricted —water entry is impeded by surface conditions, (b) Limited –capillary flow predominates and water entry is influenced primarily by soil physical properties, and (c) Unlimited —gravity flow predominates and most of the meltwater infiltrates. For Limited soils cumulative infiltration over time is estimated by a parametric equation from surface saturation, initial soil moisture content (water + ice), initial soil temperature and infiltration opportunity time. Total infiltration into Unlimited and Limited soils is constrained by the available water storage capacity. This constraint is also used to determine when Limited soils have thawed. The minimum spatial scale of the infiltration model is established for Limited soils by the variabilities in surface saturation, snow water equivalent, soil infiltrability, soil moisture (water + ice) and depth of soil freezing. Since snowmelt infiltration is influenced by other processes and factors that affect snow ablation, it is assumed that the infiltrability spatial scale should be consistent with the scales used to describe these variables. For open, northern, cold regions the following order in spatial scales is hypothesized: frozen ground ≥ snowmelt ≥ snow water equivalent ≥ frozen soil infiltrability ≥ soil moisture (water + ice) and snow water. For mesoscale application of the infiltration model it is recommended that the infiltrability scale be taken equal to the scale used to describe the areal extent and distribution of the water equivalent of the snowcover that covers frozen ground. Scaling the infiltrability of frozen soils in this manner allows one to exploit established landscape‐stratification methodology used to derive snow accumulation means and distribution. Scaling of soil infiltrability at small scales (microscale) is complicated and requires information on the association(s) between the spatial distributions of soil moisture (water + ice) and snow water. A flow chart of the algorithm is presented. Copyright © 2001 John Wiley & Sons, Ltd.
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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 | 0.001 |
| 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) | 0.002 | 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 it