A time-series InSAR-based analysis of surface deformation of hydro-fluctuation belts and the effects of hydrological elements

doi:10.6046/zrzyyg.2021413

Abstract
Figures/Tables
References
Related Articles
Metrics

Download: PDF(5960 KB) HTML
Export: BibTeX | EndNote | Reference Manager | ProCite | RefWorks

Abstract

Hydro-fluctuation belts are frequently struck by geological disasters. Therefore, ascertaining the effects of hydrological factors such as reservoir water level and rainfall on the surface deformation of these belts is of great significance for the early warning, prevention, and control of geological disasters. Based on 63 scenes of Sentinel-1 ascending images of the Fengjie section of the Three Gorges Reservoir Area from July 2018 to July 2020, this study conducted the inversion of surface deformation using the small baseline subset interferometric synthetic aperture Radar (SBAS-InSAR) technique. The inversion results were compared with the data of ground monitoring points, and the hydrological elements were analyzed using the time series diagrams of deformation, reservoir water level, and monthly rainfall. The conclusions are as follows: ① The change in the reservoir water level and rainfall are important factors causing surface deformation. The effects of the change in the reservoir water level on the slope are primarily reflected in the buoyancy effect and the water level difference inside and outside the slope. In comparison, rainfall can decrease the shear strength and increase the dead weight of the slope, thus further increasing the deformations; ② Quicker change in the reservoir water level corresponds to larger surface deformation, and vice versa; ③ Rainfall is directly proportional to surface deformation and totally dominates the surface deformation in the case of extremely heavy precipitation; ④ The surface of the study area is stable overall. However, two deformation anomaly zones have been found near the hydro-fluctuation belt. They have annual deformation rates of over 30 mm/a, with a maximum of up to 89 mm/a within the anomaly zones. The above conclusions have high theoretical and practical values and can provide scientific support for the accurate prevention and control of geological disasters in hydro-fluctuation belts.

Keywords hydro-fluctuation belt hydrological element deformation mechanism SBAS-InSAR Fengjie section of Three Gorges Reservoir

ZTFLH:

P237

Issue Date: 07 July 2023

	Service

	E-mail this article
	E-mail Alert
	RSS
	Articles by authors

	Jianping PAN
	Zhanbao FU
	Fujiang DENG
	Zhuoyan CAI
	Ruiqi ZHAO
	Wei CUI

Cite this article:

Jianping PAN,Zhanbao FU,Fujiang DENG, et al. A time-series InSAR-based analysis of surface deformation of hydro-fluctuation belts and the effects of hydrological elements[J]. Remote Sensing for Natural Resources, 2023, 35(2): 212-219.

URL:

https://www.gtzyyg.com/EN/10.6046/zrzyyg.2021413 OR https://www.gtzyyg.com/EN/Y2023/V35/I2/212

Fig.1 Location map of the study area

Tab.1 Satellite image parameters

Fig.2 Connection diagram of interference

Fig.3 Annual average deformation rate map

Fig.4 Verification comparison chart

Tab.2 Validation of results(mm)

Fig.5 Deformation process of region 1

Fig.6 Deformation process of region 2

[1]	李姗泽, 邓玥, 施凤宁, 等. 水库消落带研究进展[J]. 湿地科学, 2019, 17(6):689-696.
[1]	Li S Z, Deng Y, Shi F N, et al. Research progress on water-level-fluctuation zones of reservoirs:A review[J]. Wetland Science, 2019, 17(6):689-696.
[2]	黄波林, 殷跃平, 张枝华, 等. 三峡工程库区岩溶岸坡消落带岩体劣化特征研究[J]. 岩石力学与工程学报, 2019, 38(9):1786-1796.
[2]	Huang B L, Yin Y P, Zhang Z H, et al. Study on deterioration characteristics of shallow rock mass in water the level fluctuation zone of karst bank slopes in Three Gorges Reservoir area[J]. Chinese Journal of Rock Mechanics and Engineering, 2019, 38(9):1786-1796.
[3]	杨何, 汤明高, 许强, 等. 三峡库区消落带岸坡岩体劣化特性测试及质量评价[J]. 水利学报, 2020, 51(11):1360-1371.
[3]	Yang H, Tang M G, Xu Q, et al. Deterioration characteristic test and quality evaluation of bank slope rock mass in hydro-fluctuation belt of Three Gorges Reservoir area[J]. Journal of Hydraulic Engineering, 2020, 51(11):1360-1371.
[4]	沈振锋, 张开金, 夏雪, 等. 基于文献计量法的三峡库区消落带研究现状及热点分析[J]. 水生态学杂志, 2021, 42(1):26-34.
[4]	Shen Z F, Zhang K J, Xia X, et al. Bibliometric analysis of the current situation and hot research topics on the water level fluctuation zone of Three Gorges Reservoir[J]. Journal of Hydroecology, 2021, 42(1):26-34.
[5]	高磊. 三峡库区巫山段消落带地形变化及地质灾害分析[D]. 北京: 中国地质大学(北京), 2018.
[5]	Gao L. Terrain change and geological hazard analysis of the hydro-fluctuation belt in the Wushan of Three Gorges Reservoir area[D]. Beijing: China University of Geosciences (Beijing), 2018.
[6]	王丰. 奉节消落带岸坡稳定性评价[D]. 北京: 中国地质大学(北京), 2019.
[6]	Wang F. Stability evaluation of bank slopes in Fengjie[D]. Beijing: China University of Geosciences (Beijing), 2019.
[7]	周剑, 邓茂林, 李卓骏, 等. 三峡库区浮托减重型滑坡对库水升降的响应规律[J]. 水文地质工程地质, 2019, 46(5):136-143.
[7]	Zhou J, Deng M L, Li Z J, et al. Response patterns of buoyancy weight loss landslides under reservoir water level fluctuation in the Three Gorges Rservoir area[J]. Hydrogeology & Engineering Geology, 2019, 46(5):136-143.
[8]	付小林, 汤明高, 叶润青, 等. 不同库水消落方式下动水压力型滑坡变形与稳定性响应研究[J]. 水利水电技术(中英文), 2021, 52(1):201-211.
[8]	Fu X L, Tang M G, Ye R Q, et al. Study on deformation and stability of hydrodynamic landslide under different reservoir water fluctuation modes[J]. Water Resources and Hydropower Engineering, 2021, 52(1):201-211.
[9]	Andrew K G, Richard M G, Howard A Z. Mapping small elevation changes over large areas:Differential Radar interferometry[J]. Journal of Geophysical Research Solid Earth, 1989, 94(B7):9183-9191.
[10]	Berardino P, Fornaro G, Lanari R, et al. A new algorithm for surface deformation monitoring based on small baseline differential SAR Interferograms[J]. IEEE Transactions on Geoscience and Remote Sensing, 2002, 40(11):2375-2383. doi: 10.1109/TGRS.2002.803792 url: http://ieeexplore.ieee.org/document/1166596/
[11]	姜兆英. 短基线集InSAR形变模型的不适定问题解算方法研究[J]. 测绘学报, 2020, 49(3):399. doi: 10.11947/j.AGCS.2020.20190075
[11]	Jiang Z Y. Study on the solving methods of the ill-posed problems of the SBAS InSAR deformation model[J]. Acta Geodaetica et Cartographica Sinica, 2020, 49(3):399. doi: 10.11947/j.AGCS.2020.20190075
[12]	海香. 重庆市奉节县地质灾害风险评价及防灾减灾措施[D]. 重庆: 西南大学, 2008.
[12]	Hai X. A study on risk assessment about geological disasters and hazard prevention and mitigation measures of Fengjie in Chongqing[D]. Chongqing: Southwest University, 2008.
[13]	马新建. 三峡库区滑坡堆积体的渗透特性及渗流规律研究[D]. 成都: 成都理工大学, 2018.
[13]	Ma X J. The study of the permeability characteristics and seepage law of landslide accumulation body in the Three Gorges Reservoir area[D]. Chengdu: Chengdu University of Technology, 2018.
[14]	许嘉慧, 孙德亮, 王月, 等. 基于GIS与改进层次分析法的奉节县滑坡易发性区划[J]. 重庆师范大学学报(自然科学版), 2020, 37(2):36-44,2,142.
[14]	Xu J H, Sun D L, Wang Y, et al. Landslide susceptibility mapping of Fengjie County based on GIS and improved analytic hierarchy process[J]. Journal of Chongqing Normal University(Natural Science), 2020, 37(2):36-44,2,142.
[15]	吴俊峰, 罗永红, 周亮亮. 浮托减重效应对三峡库区竹林湾滑坡稳定性影响研究[J]. 三峡大学学报(自然科学版), 2019, 41(6):48-53.
[15]	Wu J F, Luo Y H, Zhou L L. Study of buoyancy effect on stability of Zhulinwan landslide in Three Gorges Reservoir area[J]. Journal of China Three Gorges University(Natural Sciences), 2019, 41(6):48-53.
[16]	李永康, 许强, 董远峰, 等. 库水位升降作用对动水压力型滑坡的影响——以三峡库区白家包滑坡为例[J]. 科学技术与工程, 2017, 17(18):18-24.
[16]	Li Y K, Xu Q, Dong Y F, et al. Influence of reservoir water level fluctuation on typical hydrodynamic pressure landslide:Taking Baijiabao landslide in Three Gorges Reservoir for an example[J]. Science Technology and Engineering, 2017, 17(18):18-24.
[17]	黄观文, 王家兴, 杜源, 等. 顾及降雨及库水位因素的滑坡时滞分析与预测——以三峡库区新铺滑坡为例[J]. 地球科学与环境学报, 2021, 43(3):621-631.
[17]	Huang G W, Wang J X, Du Y, et al. Time-delay analysis and prediction of landslide considering precipitation and reservoir water level:A case study of Xinpu landslide in Three Gorges Reservoir area[J]. Journal of Earth Sciences and Environment, 2021, 43(3):621-631.
[18]	闫怡秋, 郭长宝, 张永双, 等. 基于SBAS-InSAR技术的西藏雄巴古滑坡变形特征[J]. 地质学报, 2021, 95(11):3556-3570.
[18]	Yan Y Q, Guo C B, Zhang Y S, et al. Study on the deformation characteristics of Xiongba ancient landslide based on SBAS-InSAR method,Tibet[J]. Acta Geologica Sinica, 2021, 95(11):3556-3570.
[19]	朱同同, 史绪国, 周超, 等. 利用2016—2020年Sentinel-1数据的三峡库区树坪滑坡稳定性监测与分析[J]. 武汉大学学报(信息科学版), 2021, 46(10):1560-1568.
[19]	Zhu T T, Shi X G, Zhou C, et al. Stability monitoring and analysis of Shupinglandslide in Three Gorges Area with Sentinel-1 images from 2016 to 2020[J]. Geomatics and Information Science of Wuhan University, 2021, 46(10):1560-1568.
[20]	王尚晓, 李士垚, 牛瑞卿. 木鱼包滑坡形变特征的InSAR监测分析[J]. 长江科学院院报, 2022, 39(4):77-84.
[20]	Wang S X, Li S Y, Niu R Q. Monitoring slope displacements of Muyubao landslide using InSAR analysis technique[J]. Journal of Yangtze River Scientific Research Institute, 2022, 39(4):77-84.

[1]	HU Xiaoqiang, YANG Shuwen, YAN Heng, XUE Qing, ZHANG Naixin. Time-series InSAR-based monitoring and analysis of surface deformation in the Axi mining area, Xinjiang[J]. Remote Sensing for Natural Resources, 2023, 35(1): 171-179.
[2]	LUO Xuewei, XIANG Xiqiong, LYU Yadong. PS correction of InSAR time series deformation monitoring for a certain collapse in Longli County[J]. Remote Sensing for Natural Resources, 2022, 34(3): 82-87.
[3]	XU Zixing, JI Min, ZHANG Guo, CHEN Zhenwei. Method for dynamic prediction of mining subsidence based on the SBAS-InSAR technology and the logistic model[J]. Remote Sensing for Natural Resources, 2022, 34(2): 20-29.
[4]	YANG Wang, HE Yi, ZHANG Lifeng, WANG Wenhui, CHEN Youdong, CHEN Yi. InSAR monitoring of 3D surface deformation in Jinchuan mining area, Gansu Province[J]. Remote Sensing for Natural Resources, 2022, 34(1): 177-188.
[5]	SHA Yonglian, WANG Xiaowen, LIU Guoxiang, ZHANG Rui, ZHANG Bo. SBAS-InSAR-based monitoring and inversion of surface subsidence of the Shadunzi Coal Mine in Hami City, Xinjiang[J]. Remote Sensing for Natural Resources, 2021, 33(3): 194-201.
[6]	HE Haiying, CHEN Caifen, CHEN Fulong, TANG Panpan. Deformation monitoring along the landscape corridor of Zhangjiakou Ming Great Wall using Sentinel-1 SBAS-InSAR approach[J]. Remote Sensing for Land & Resources, 2021, 33(1): 205-213.
[7]	SUN Xiaopeng, LU Xiaoya, WEN Xuehu, ZHEN Yan, WANG Lei. Monitoring of ground subsidence in Chengdu Plain using SBAS-InSAR[J]. REMOTE SENSING FOR LAND & RESOURCES, 2016, 28(3): 123-129.

Viewed

Full text

Abstract

Cited

Shared

Discussed