Land subsidence simulation considering groundwater and compressible layers based on an improved machine learning method
发布时间：2025-08-01
点击次数：
- DOI码：
- 10.1016/j.jhydrol.2025.133008
- 所属单位：
- Wuhan Univ, State Key Lab Informat Engn Surveying Mapping & Re, Wuhan 430079, Peoples R China
- 发表刊物：
- JOURNAL OF HYDROLOGY
- 项目来源：
- This work was supported by National Natural Science Foundation of China (41930109, 41771455) , Natio
- 关键字：
- South-to-North Water Diversion Project,Interferometric Synthetic Aperture Radar,Groundwater variation,Land subsidence,Machine learning
- 摘要：
- Land subsidence is a significant issue in the Beijing Plain, China, induced by groundwater overexploitation. The regional land subsidence is experiencing a new development trend with the external water source provided by the South-to-North Water Diversion Project (SWDP). The study proposes a novel model to simulate large-scale land subsidence that combines the weight of evidence (WOE) with the light gradient boosting machine (LightGBM) to explore the causes of land subsidence development after SWDP. The model encodes categorical variables to integrate information and evidence, reducing noise i
- 合写作者：
- Gong, Huili,Chen, Beibei,Zhou, Chaofan
- 第一作者：
- Shi, Liyuan
- 论文类型：
- 期刊论文
- 通讯作者：
- Shao, Zhenfeng
- 文献类型：
- Article
- 卷号：
- 656
- ISSN号：
- 0022-1694
- 是否译文：
- 否
- 发表时间：
- 2025-08-01