Sensitivity Analysis of Potential Evapotranspiration in the Lancang River Basin
Bibliographic record
Abstract
Sensitivity analysis is critical in assessing the impact of climatic variables on potential evapotranspiration (ET0) estimation.A sensitivity analysis of ET0 to perturbations associated with climatic variables is important to improve our understanding of the connections between climatic conditions and ET0 variability.Based on a 46-year daily observed dataset at 35 meteorological stations distributed within or in the vicinity of the Lancang River basin,ET0 was calculated for each station by the Penman-Monteith method.A non-dimensional sensitivity coefficient was employed to identify the sensitivity of ET0 to the variation of air temperature (Tmean),sunshine duration (N),relative humidity (RH),and wind speed (U2) at 3 time scales.Results indicate that the sensitivity coefficient varies greatly over space and time.For the basin as a whole,N is the most sensitive variable,increasing in January and decreasing in July over the study period.An analysis based on the long-term average level show that in general ET0 is most sensitive to N,followed by RH and Tmean.U2 was found to be the least sensitive variable in the basin in most days of a year.These coefficients also exhibit fluctuations throughout a year,especially for Tmean,with its largest value being found in July.Regarding the spatial distribution of the sensitivity coefficients in the basin in January and July,the most prominent change was a reverse distribution of high and low values in the 2 months,reflecting significant spatial differences.As for the temporal trends of the sensitivity coefficients in the basin in January and July,the most prominent change occurred in July,when the sensitivity coefficient for N decreased in most parts of the basin in the south at the Changdu station.The trend was contrary to that of the north of this station,where most stations increased.The increasing trend was also found for the regions in the south of Changdu in January.The large spatial-temporal variability of the sensitivity coefficients indicate that ET0 response to climate change differs greatly with region and season,especially for N.Results of this work can be used as a theoretical basis for future research on the response of ET0 to climatic change in the Lancang River basin.
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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".