Estimating Evaporation in a Prairie Landscape under Drought Conditions
Bibliographic record
Abstract
Abstract: Physically-based atmospheric models of evapotranspiration (ET) that consider the Penman combination energy balance and aerodynamic approach have achieved acceptance as useful tools for obtaining estimates of actual ET from land surfaces. These models have been made applicable to the case of non-saturated conditions through either surface resistance formulations (e.g., Penman-Monteith) or by application of the complementary evaporation theory of feedback between the atmosphere and surface moisture states (e.g., Granger-Gray). Their application becomes complicated under conditions of drought, when extremely low soil moisture availability severely restricts ET from the soil and plants. Under such severe conditions, consideration for the surface water balance and interactions with the balance of available energy and aerodynamic principles are important for accurately estimating actual ET. A modelling application is demonstrated using the Cold Regions Hydrological Model (CRHM) platform to examine the estimation of ET under drought conditions. CRHM allows users to assemble hydrological models by linking a suite of modular physically-based algorithms that describe the individual processes. In this case, the models assembled consider infiltration, evaporation, and soil moisture
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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 | 0.001 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".