Evaluation of Estimation Methods for Monthly Reference Evapotranspiration in Arid Climates
Bibliographic record
Abstract
Abstract Reference evapotranspiration (ET0) plays a key role in irrigation system design as well as water management of agricultural ecosystems under irrigated and rainfed conditions. While many methods for estimating the ET0 have been developed during the past several decades, method selection essentially depends on the availability of measured climatic variables. The FAO-56PM method recommended by experts from Food and Agriculture Organization of the United Nations is widely used in agricultural and environmental research to estimate the ET0. However, it requires several climatic parameters that are not always available in developing countries, especially in arid regions. Here, we compare and evaluate the performance of 13 widely- and commonly-used equations for estimating ET0 against that predicted using the FAO-56PM model using climatic data from nine meteorological stations located in arid regions across Iran. On average, the best three methods that could be used as an alternative to the FAO-56PM equation were the Irmak (Irmak et al., 2003), Hargreaves-Samani (Hargreaves and Samani, 1985), and Hargreaves (1975) equations.
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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 | 0.011 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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 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".