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互连,趋势分析和预测水空气温度与水位动态在蓝月亮湖谷:一个统计和机器学习方法
Shoukat Ali Shah1, Songtao Ai2, Wolfgang Rack3
1Chinese Antarctic Center of Surveying and Mapping, Wuhan University, Wuhan, 430079, China; State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, 430079, China.
Journal of environmental management
|March 8, 2025
概括
冰川养的湖泊温度随着空气温度的上升而上升,但由于水文因素,水位保持稳定. 一个新的Quad-Meta模型准确地预测了高海拔盆地中的这些动态.
科学领域:
- 环境科学 环境科学
- 水文学的水文学
- 气候变化研究 气候变化研究
背景情况:
- 冰川养的湖泊是气候变化的关键指标.
- 它们在高海拔盆地中的温度和水位动态研究不足.
- 了解这些动态对于水资源管理至关重要.
研究的目的:
- 在蓝月亮湖谷调查空气温度 (Ta),水温 (Tw) 和水位 (WL) 的相互作用.
- 使用先进的统计学和机器学习解决预测差距.
- 为这些复杂的动态发展出一个优越的预测模型.
主要方法:
- 使用曼-肯达尔,F-测试和t-测试进行趋势分析.
- 格兰杰因果关系和波纹分析,用于关系和时间尺度.
- 极端值分析和机器学习模型 (GBM,XGB,DT,RF) 的比较.
- 开发和验证混合四元元 (QM) 模型.
主要成果:
- 观察到Ta和Tw的显著变暖趋势,Ta的增长速度更快.
- 水平 (WL) 保持稳定,这表明水文调节的主导.
- 质量管理模型显著优于其他模型,实现了低RMSE和高R2.
结论:
- 高海拔的冰川养的湖泊显示出明显的变暖趋势.
- 尽管气候变暖,但水文因素是调节水位的关键.
- 开发的QM模型为在敏感环境中预测湖泊动态提供了更高的准确性.
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