Spatiotemporal Variations in Reference Evapotranspiration and Its Contributing Climatic Variables at Various Spatial Scales across China for 1984–2019
Bibliographic record
Abstract
Reference evapotranspiration (ET0) is of great significance in studies of hydrological cycle, agricultural water resources, and hydrometeorology. The present study collected daily meteorological data at 536 meteorological stations in China from 1984 to 2019, calculated daily ET0 using the FAO Penman–Monteith equation, analyzed the spatial distribution and temporal variation characteristics of ET0 and meteorological variables at four different spatial scales (continental, regional, provincial, and local), and discussed the sensitivity of ET0 to the meteorological variables and the contribution rates of the meteorological variables to the ET0 variations. The results showed that ET0 increased at 406 out of the 536 stations (75.7%), with the trends being significant at 65 stations at the 5% significance level, and 147 at the 1% significance level. The slope calculated using Sen’s method and linear trend method showed that the annual ET0 at the continental scale increased by approximately 12 mm/decade. Most of the stations showed decreasing trends in relative humidity (Hm), sunshine duration (SD), and wind speed at 2 m height (U2) while increasing trends in the maximum air temperature (Tmax) and minimum air temperature (Tmin). ET0 was most sensitive to Hm (sensitivity coefficient, St = −0.66), followed by Tmax (St = 0.29), SD (St = 0.18), U2 (St = 0.16), and Tmin (St = 0.07). Most of the stations showed increasing trends in St for Hm (56.16%), Tmax (72.95%), Tmin (87.31%), and U2 (90.49%), and decreasing trends for SD (69.78%). The variations in Hm, Tmax, and Tmin increased the ET0 at most of the stations (82.28%, 98.13%, and 69.03%, respectively). The variations in SD and U2 decreased ET0 at most of the stations (66.04% and 56.34%, respectively). Some ET0 characteristics in a few regions can be well described using a single spatial scale. However, most regions exhibited significantly different ET0 characteristics across spatial scales. The results of this project can provide reference for hydrological analysis and agricultural water management under climate change conditions and provide data and information for other hydrology-related applications.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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) | 0.001 | 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".