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15827188114Status:
EmployedSchool/Department:
测绘遥感信息工程全国重点实验室Date of Birth:
1976-03-21Alma Mater:
武汉大学Status:
EmployedSchool/Department:
测绘遥感信息工程全国重点实验室Date of Employment:
2004-07-01Administrative Position:
副主任Business Address:
武汉大学星湖实验大楼713Contact Information:
15827188114
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Paper Publications
Current position: Home > Scientific Research > Paper Publications
Land subsidence simulation considering groundwater and compressible layers based on an improved machine learning method
- Time:2025-08-01
- Hits:
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DOI number:
10.1016/j.jhydrol.2025.133008 -
Affiliation of Author(s):
Wuhan Univ, State Key Lab Informat Engn Surveying Mapping & Re, Wuhan 430079, Peoples R China -
Journal:
JOURNAL OF HYDROLOGY -
Funded by:
This work was supported by National Natural Science Foundation of China (41930109, 41771455) , Natio -
Key Words:
South-to-North Water Diversion Project,Interferometric Synthetic Aperture Radar,Groundwater variation,Land subsidence,Machine learning -
Abstract:
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 -
Co-author:
Chaofan,Zhou, Beibei,Chen, Huili,Gong -
Indexed by:
Journal paper -
Correspondence Author:
Zhenfeng,Shao -
Document Type:
Article -
Volume:
656 -
ISSN No.:
0022-1694 -
Translation or Not:
no -
Date of Publication:
2025-08-01