Evapotranspiration and water yield over China's landmass from 2000 to 2010
Bibliographic record
Abstract
Abstract. Terrestrial carbon and water cycles are interactively linked at various spatial and temporal scales. Evapotranspiration (ET) plays a key role in the terrestrial water cycle, altering carbon sequestration of terrestrial ecosystems. The study of ET and its response to climate and vegetation changes is critical in China because water availability is a limiting factor for the functioning of terrestrial ecosystems in vast arid and semiarid regions. To constrain uncertainties in ET estimation, the process-based Boreal Ecosystem Productivity Simulator (BEPS) model was employed in conjunction with a newly developed leaf area index (LAI) data set, MODIS land cover, meteorological, and soil data to simulate daily ET and water yield at a spatial resolution of 500 m over China for the period from 2000 to 2010. The spatial and temporal variations of ET and water yield were analyzed. The influences of climatic factors (temperature and precipitation) and vegetation (land cover types and LAI) on these variations were assessed. Validations against ET measured at five ChinaFLUX sites showed that the BEPS model was able to simulate daily and annual ET well at site scales. Simulated annual ET exhibited a distinguishable southeast to northwest decreasing gradient, corresponding to climate conditions and vegetation types. It increased with the increase of LAI in 74% of China's landmass and was positively correlated with temperature in most areas of southwest, south, east, and central China. The correlation between annual ET and precipitation was positive in the arid and semiarid areas of northwest and north China, but negative in the Tibetan Plateau and humid southeast China. The national annual ET varied from 345.5 mm in 2001 to 387.8 mm in 2005, with an average of 369.8 mm during the study period. The overall rate of increase, 1.7 mm yr−1 (R2 = 0.18, p = 0.19), was mainly driven by the increase of total ET in forests. During 2006–2009, precipitation and LAI decreased widely and consequently caused a detectable decrease in national total ET. Annual ET increased over 62.2% of China's landmass, especially in the cropland areas of the southern Haihe River basin, most of the Huaihe River basin, and the southeastern Yangtze River basin. It decreased in parts of northeast, north, northwest, south China, especially in eastern Qinghai-Tibetan Plateau, the south of Yunnan Province, and Hainan Province. Reduction in precipitation and increase in ET caused vast regions in China, especially the regions south of Yangtze River, to experience significant decreases in water yield, while some sporadically distributed areas experienced increases in water yield. This study shows that the terrestrial water cycles in China's terrestrial ecosystems appear to have been intensified by recent climatic variability and human induced vegetation changes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.001 | 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 teacher head, 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".