Ecological water requirement accounting of the main stream of the Yellow River from the perspective of habitat conservation
Bibliographic record
Abstract
The Yellow River Basin is of great significance to China’s economic and social development and ecological security. The Yellow River Basin is not only an important ecological barrier but also an important economic zone. In this paper, natural hydrological conditions were taken as a reference, a habitat simulation model of the key sections of the Yellow River was constructed based on the MIKE 21 model, and an ecological water requirement assessment method for river ecological integrity combined with habitat simulation and features of the hydrological reference group was established, which takes into account the survival and reproduction of indicator species. The suitable flow rates for the spawning period of Silurus lanzhouensis in Lanzhou and Xiaheyan and Cyprinus carpio in Toudaoguai, Longmen and Huayuankou were 350-720 m 3 /s, 350-600 m 3 /s, 150-500 m³/s, 260-400 m 3 /s, and 100-500 m³/s, respectively. Therefore, high pulse flow with a low flow peak should be guaranteed in mid- to late April. The peak flow should be at least approximately 1,000 m 3 /s to ensure that fish receive spawning signals, with a high pulse flow process occurring 1-2 times in May to June. The annual ecological water requirement of the Lanzhou, Xiaheyan, Toudaoguai, Longmen and Huayuankou sections was 9.1-11 ×10 9 m³, 6.3-10.4×10 9 m³, 3.8-8.2×10 9 m³, 4.7-11.3×10 9 m³ and 7.9-15.4×10 9 m³, respectively. The model quantitatively simulates the changes in ecological water requirement of indicator fishes in key sections of the Yellow River, and an effective and more realistic tool for ecological water requirement accounting of the Yellow River has been provided.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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 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".