Your browser doesn't support javascript.
loading
Using the meteorological early warning model to improve the prediction accuracy of water damage geological disasters around pipelines in mountainous areas.
Hong, Bingyuan; Shao, Bowen; Wang, Benji; Zhao, Juncheng; Qian, Jiren; Guo, Jian; Xu, Yupeng; Li, Cuicui; Zhu, Baikang.
Afiliação
  • Hong B; National & Local Joint Engineering Research Center of Harbor Oil & Gas Storage and Transportation Technology, Zhejiang Key Laboratory of Petrochemical Environmental Pollution Control, School of Petrochemical Engineering & Environment, Zhejiang Ocean University, Zhoushan 316022, PR China.
  • Shao B; School of shipping and Maritime, Zhejiang Ocean University, Zhoushan 316022, Zhejiang, China.
  • Wang B; School of shipping and Maritime, Zhejiang Ocean University, Zhoushan 316022, Zhejiang, China.
  • Zhao J; National Pipeline Network Group Zhejiang Natural Gas Pipeline Network Co., Ltd., Hangzhou 310000, Zhejiang, China.
  • Qian J; National Pipeline Network Group Zhejiang Natural Gas Pipeline Network Co., Ltd., Hangzhou 310000, Zhejiang, China.
  • Guo J; National & Local Joint Engineering Research Center of Harbor Oil & Gas Storage and Transportation Technology, Zhejiang Key Laboratory of Petrochemical Environmental Pollution Control, School of Petrochemical Engineering & Environment, Zhejiang Ocean University, Zhoushan 316022, PR China.
  • Xu Y; National & Local Joint Engineering Research Center of Harbor Oil & Gas Storage and Transportation Technology, Zhejiang Key Laboratory of Petrochemical Environmental Pollution Control, School of Petrochemical Engineering & Environment, Zhejiang Ocean University, Zhoushan 316022, PR China.
  • Li C; National & Local Joint Engineering Research Center of Harbor Oil & Gas Storage and Transportation Technology, Zhejiang Key Laboratory of Petrochemical Environmental Pollution Control, School of Petrochemical Engineering & Environment, Zhejiang Ocean University, Zhoushan 316022, PR China.
  • Zhu B; National & Local Joint Engineering Research Center of Harbor Oil & Gas Storage and Transportation Technology, Zhejiang Key Laboratory of Petrochemical Environmental Pollution Control, School of Petrochemical Engineering & Environment, Zhejiang Ocean University, Zhoushan 316022, PR China.
Sci Total Environ ; 889: 164334, 2023 Sep 01.
Article em En | MEDLINE | ID: mdl-37209747
ABSTRACT
This paper focuses on the threat of water damage geological disasters brought by the complex terrain along the long-distance natural gas pipeline. The role of rainfall factors in the occurrence of such disasters has been fully considered, a meteorological early warning model for water damage geological disasters in mountainous areas based on slope units has been constructed to improve the prediction accuracy of such disasters and timely early warning and forecasting. An actual natural gas pipeline in a typical mountainous area of Zhejiang Province is taken as an example. The hydrology-curvature combined analysis method is chosen to divide the slope units, and the SHALSTAB model is used to fit the slope soil environment to calculate the stability level. Finally, the stability level is coupled with rainfall data to calculate the early warning index for water damage geological disasters in the study area. The results show that compared with the separate SHALSTAB model, the early warning results coupled with rainfall are more effective in predicting water damage geological disasters. The early warning results are compared with the actual disaster points, among the nine actual disaster points, most of the slope units around seven disaster points are in the state of needing early warning, the early warning accuracy rate reaches 77.8 %. The proposed early warning model can carry out targeted deployment in advance according to the divided slope units, and the prediction accuracy of geological disasters induced by heavy rainfall weather is significantly higher and more suitable for the actual location of the disaster point, which can provide a basis for accurate disaster prevention in the research area and areas with similar geological environments.
Assuntos
Palavras-chave

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Desastres / Gás Natural Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Desastres / Gás Natural Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2023 Tipo de documento: Article