Bibliographic record
Abstract
湿地水文调蓄功能是湿地生态系统服务功能的重要组成部分, 开展定量评估对湿地生态功能评价具有重要的理论意义和应用价值. 文章基于耦合湿地模块的PHYSITEL/HYDROTEL模型平台, 构建了流域湿地生态水文模型, 模拟了有/无湿地情景下多布库尔河流域水文过程, 定量评估了湿地削减洪峰和维持基流的水文功能. 研究结果表明, 多布库尔河流域湿地具有显著的径流调节能力, 体现在对总径流的削弱作用和对径流机制(流量、频率、历时和发生时间等)的改变作用. 湿地对快径流的影响具有明显的日、月和年时间尺度效应, 尤其在洪峰期间和汛期对快径流的削减作用最明显, 对快径流多年平均的削减作用为5.89%; 而对日、月和年基流的影响较弱, 对基流多年平均的维持作用为0.83%; 湿地对总径流、快径流和基流的影响效应(削弱或增强)和强度有明显的月、季节和年尺度变化特征, 但总体上发挥着削减洪峰和维持基流的功效. 研究结果从发挥湿地水文功能的视角为流域湿地恢复保护与水资源综合管控提供科学依据和新的思路.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.018 | 0.003 |
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".