The variation and propagation characteristics of meteorological, hydrological and agricultural droughts in mainland China
Bibliographic record
Abstract
Drought, a natural hazard, greatly damages environment, agriculture, hydrology and thus, economy and our society at large. The national-scale variation and propagation characteristics of different types of droughts are critical for developing strategies and policies, while information is limited in China. This research investigated the evolution and propagation characteristics of three types of droughts using standardized indices; Standardized Precipitation Index (SPI), Standardized Soil Moisture Index (SSI) and Standardized Runoff Index (SRI) representing meteorological, agricultural and hydrological droughts based on precipitation (PPT), soil water storage (SWS) and baseflow-groundwater runoff (BGR), respectively at multi-timescales in different sub-regions of mainland China over 1948-2010. The most appropriate probability density distributions of PPT, SWS and BGR were selected for the calculation of drought indices and wavelet analysis was used to reveal their periodical characteristics. Modified Mann-Kendall trend test was used to compare the trend among drought indices. Pearson correlation coefficients were calculated to identify the lags of SPI with SSI and SRI. In general, SPI showed an agreement with the historical severe or extreme drought events at different sub-regions. The main periods of SSI were closer to SPI than SRI, indicating stronger connections of agricultural drought with meteorological drought. A weaker connection between meteorological and agricultural/hydrological droughts at shorter timescales was observed in northwestern arid and semi-arid regions. The propagation from meteorological to agricultural or hydrological droughts were well denoted by the lagged time (months) from SPI to SSI or SRI at a timescale ranged from 0 (mostly located in south China) to 5 months (mostly located in northeastern China) for certain timescale. The study provides crucial information and guidance to the policy makers in developing drought management strategies at regional to national scale and their critical time of action.
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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) | 0.000 | 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".