Impacts of small and medium-sized reservoirs on streamflow in two basins of Southeast China, using a hydrological model to separate influences of multiple drivers
Bibliographic record
Abstract
Southeast coast of China The reservoirs in southeast coast of China are mostly small due to the limitations of terrain. In order to analyze the impact of these densely distributed small and medium-sized reservoirs (SMRs) with lacking observation and operational data on runoff, this paper uses a hydrological model & scenario simulation method to separate the impacts of climate variability (CV), land use change (LUC) and SMRs group change on streamflow variation in two river basins of Southeast China. (1) The streamflow of two basins has changed greatly, with CV and SMRs change being the main influencing factors, while the impact of LUC was relatively small. The contribution rates of CV to the annual runoff change of three hydrological stations in two river basins were 90.19%, 61.75% and 26.64%; Contribution rates of SMRs changes were 9.34%, 37.24% and 71.04%, correspondingly. (2) The regulation of streamflow by SMRs changes led to a decrease in both annual and monthly runoff, which was due to the fact that the main functions of SMRs in this region are agricultural irrigation and domestic water supply. (3) The three-factor separation method based on hydrological modeling, which separated the cumulative effects of SMRs in the form of SMRs group, would be valuable for the study and management of watersheds with numerous SMRs and lack of observation and operational data.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".