Impact of the False Intensification and Recovery on the Hydrological Drought Internal Propagation
Bibliographic record
Abstract
Understanding the influence factors of hydrological drought internal propagation (HDIP) is crucial for early detection of hydrological drought. However, the ‘false recovery’ (FR) during development of hydrological drought and ‘false intensification’ (FI) during the recovery stage were not considered. Here, the definitions of FR and FI were firstly introduced in detail. We define the FR that occurs during the drought intensification period and does not recover the hydrological drought to a normal pre-drought condition, and the FI that occurs during the drought recovery period and does not allow the hydrological drought to develop into maximum drought intensity. Then, we designed a numerical algorithm to assess the roles of the FR and FI during the hydrological drought by comparing two scenarios: 1) considering the FR and FI and 2) not including these two variables. The monthly streamflow and precipitation records with at least 40 years of data for five unregulated and rainfall-driven basins with minimal human activities, located in southern China, were taken for the case study. Three evaluation indicators were considered, i.e., the average of relative error (Ave.RE), coefficient of determination (R2), and the Nash-Sutcliffe efficiency (NSE) coefficient, to evaluate the differences in tracking effect of HDIP under considering FR (FI) and without considering FR (FI). Results showed that the FI and the FR influence the hydrological drought intensification and recovery by changing the drought severity. The higher the FR is, the lower severity and slower intensification the drought has. A greater FI leads to a hydrological drought that has larger severity and slower recovery. Considering the substantial influence of FR and FI can significantly improve tracking effect of HDIP. The Ave.RE decreased by 36.01% (24.98%) on average, R2 and NSE increased by 22.22% (14.06%) and 39.19% (24.02%) on average in the development (recovery) period of hydrological drought. The FR (FI) during the hydrological drought is mainly caused by the occurrence of short duration precipitation events (precipitation shortage) in the study basins. Our findings highlight the role of FI and FR in hydrological drought and provide valuable scientific insights for tracking hydrological drought in real time.
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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 | 0.005 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 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".