Simulation of the regional climatic effect of irrigation over the Yellow River Basin
Bibliographic record
Abstract
In this study, the authors developed a new irrigation scheme based on the Noah land surface model, and then coupled it with the Weather Research and Forecasting regional climate model. Two simulations (with and without irrigation) were conducted over the Yellow River basin for the period April to October 2000–2010. The results indicated that the WRF model is able to successfully capture the spatial pattern and seasonal changes in observed temperature and precipitation over the Yellow River basin. When irrigation was induced, the mean surface air temperature at 2 m (T2m) decreased by 0.1–0.4 K, and there was a correspond increase (decrease) in latent (sensible) heat flux over the irrigated areas, wherein the increase (decrease) reached more than 10 W m−2 over the largest irrigated areas. The cooling effect was consistent with the changes in evapotranspiration and heat fluxes due to irrigation. The changes in lifting condensation level and planetary boundary layer height led to a greater probability of cloud formation and bore a close association with surface fluxes and soil moisture, which then impacted the spatial distribution of T2m and precipitation.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".