Estimating Evaporation in a Prairie Landscape under Drought Conditions
Bibliographic record
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 accounting and are applied to a mixed prairie located at Lethbridge, Alberta, Canada under drought conditions during the growing period in 2000 and 2001. Near surface meteorological and ecological observations used as model input and for evaluating model performance were obtained through the Ameriflux network and the Agriculture and Agri-Food Canada (AFC) Lethbridge Research Centre. Results show that consideration for the effective rooting zone depth of the mixed-prairie at the site is important for estimating actual ET using the Penman-Montieth and Granger-Gray models during severe moisture stress. Relative differences in ET estimates provided by the models are discussed in the context of their contrasting theoretical approaches.
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 | 0.001 |
| 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) | 0.000 | 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".