ISSN 1671-1092 CN 33-1260/TK

大坝与安全 ›› 2023 ›› Issue (5): 8-14.

• 监测技术 • 上一篇    下一篇

基于SBAS-InSAR的白鹤滩库区王家山滑坡蓄水前形变特征分析

崔振华1 ,杨建元1 ,顿佳伟2 ,姚宇昂1 ,陈庭轩1
  

  1. 1.浙江华东岩土勘察设计研究院有限公司,浙江 杭州,310012;2.成都理工大学地质灾害防治与地质环境保护国家重点实验室,四川 成都,610059
  • 收稿日期:2023-03-15 修回日期:2023-04-12 出版日期:2023-10-20 发布日期:2023-10-20
  • 作者简介:崔振华(1984—),男,山西盂县人,高级工程师,主要从事地质灾害防治工作。

Analysis of deformation characteristics of Wangjiashan landslide in Baihetan reservoir area before impoundment based on SBAS- InSAR

CUI Zhenhua, YANG Jianyuan, DUN Jiawei, YAO Yu'ang and CHEN Tingxuan   

  1. Zhejiang Huadong Geotechnical Investigation & Disign Institute Co., Ltd.
  • Received:2023-03-15 Revised:2023-04-12 Online:2023-10-20 Published:2023-10-20

摘要:

利用Sentinel-1A卫星SAR数据集和SBAS-InSAR技术研究了白鹤滩库区王家山滑坡蓄水前的时间序列形变特征,结果显示王家山滑坡近4年来处于初始形变状态,中部首先发生形变,进而向前缘和后缘拓展。通过与历史降雨数据的共同分析,发现王家山滑坡对降雨的敏感性很高,形变量不仅与累计降雨量有明显相关性,还受到集中强降雨的影响。因此,应在蓄水期建立一个监测预警系统,以在地质灾害发生前预警,减少人员和财产损失。王家山滑坡的时序形变结果展示了InSAR技术在滑坡探测方面的应用潜力,为滑坡时空演变、诱因分析、防灾减灾提供了新的思路与参考。

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Abstract:

The time series deformation characteristics of Wangjiashan landslide in Baihetan reservoir area before impoundment are studied by using Sentinel- 1ASAR dataset and SBAS- InSAR technology. The results show that Wangjiashan landslide has been in an initial deformation state in the past four years, with deformation occurring first in the middle part and then expanding to the front edge and back edge.Through joint analysis with historical rainfall data, it is found that Wangjiashan landslide is highly sensitive to rainfall, and the deformation is not only significantly correlated with cumulative rainfall, but also influenced by concentrated heavy rainfall. Therefore, a monitoring and early warning system should be established during impoundment period to provide early warning of geological disasters and reduce casualties and property losses. The time series deformation results of Wangjiashan landslide demonstrate the potential application of InSAR technology in landslide detection, which provides new ideas and references for landslide spatiotemporal evolution, causal analysis, as well as disaster prevention and reduction.

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