Poyang Lake basin: a successful, large-scale integrated basin management model for developing countries
Why this work is in the frame
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Bibliographic record
Abstract
Protection of water environment while developing socio-economy is a challenging task for lake regions of many developing countries. Poyang Lake is the largest fresh water lake in China, with its total drainage area of 160,000 km2. In spite of rapid development of socio-economy in Poyang Lake region in the past several decades, water in Poyang Lake is of good quality and is known as the "last pot of clear water" of the Yangtze River Basin in China. In this paper, the reasons of "last pot of clear water" of Poyang Lake were analysed to demonstrate how economic development and environmental protection can be coordinated. There are three main reasons for contributing to this coordinated development: 1) the unique geomorphologic features of Poyang Lake and the short water residence time; 2) the matching of the basin physical boundary with the administrative boundary; and 3) the implementation of "Mountain-River-Lake Program" (MRL), with the ecosystem concept of "mountain as source, river as connection flow, and lake as storage". In addition, a series of actions have been taken to coordinate development, utilisation, management and protection in the Poyang Lake basin. Our key experiences are: considering all basin components when focusing on lake environment protection is a guiding principle; raising the living standard of people through implementation of various eco-economic projects or models in the basin is the most important strategy; preventing soil and water erosion is critical for protecting water sources; and establishing an effective governance mechanism for basin management is essential. This successful, large-scale basin management model can be extended to any basin or lake regions of developing countries where both environmental protection and economic development are needed and coordinated.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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 it