Quantifying Evapotranspiration in Seasonally Frozen Forests
Bibliographic record
Abstract
In seasonally frozen environments, hydrological processes are highly dynamic during and following the melt period in the spring, and this is when most of the runoff and groundwater re- charge happens. This is also when evapotranspiration (ET) fluxes start to increase in response to higher solar radiation, and a resumption of photosynthesis in evergreen species. This thesis applies the Canadian Land Surface Scheme (CLASS) to three Boreal Ecosystem Research and Monitoring Sites (BERMS) in the boreal forest in Saskatchewan; Old Jack Pine, Old Black Spruce and Old Aspen. CLASS was used to simulate the energy and water balance of the vegetation, soil and snowpack at the three sites. Consistent with previous studies, it was shown that ET is overestimated in the model during the melt/thaw period. A series of numerical experiments were undertaken to investigate in detail the controls on simulated fluxes within the CLASS model and explore the model behaviour. The phenomenon of freezing point depression, where water freezes below 0 °C in soils, is not represented in the CLASS model. Consequently, the model predicted a significant amount of transpiration to occur during the melt period while the soil was at 0 °C and ice was still present in the soil pores. Subtracting the transpiration that occurred from soil layers containing ice improved the simulated ET, compared with flux tower estimates. Therefore, it is suggested that implementing freezing point depression in the model and including a water stress function to shut down transpiration when the soil temperature is ≤ 0 °C would improve the simulated evapotran- spiration during the melt period. The study also showed that calibration of the model parameters improved the simulations but is unable to uniquely constrain the infiltration and soil drainage fluxes by either single objective (ET) or multi-objective (soil moisture and ET) calibration. Further research is needed to explore the hypothesis that root water uptake does not occur in soils where the soil temperature ≤ 0 °C would.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Open science | 0.001 | 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".