Deformation Monitoring and Tidal Response Analysis of Strong Surge Tide Estuary Sluice Based on GNSS

LI Yafei; YAO Yibin; QI Minmin; WU Chenghong; GUO Zihuai; WANG Weitang; ZHANG Liang

doi:10.13203/j.whugis20240059

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LI Yafei, YAO Yibin, QI Minmin, WU Chenghong, GUO Zihuai, WANG Weitang, ZHANG Liang. Deformation Monitoring and Tidal Response Analysis of Strong Surge Tide Estuary Sluice Based on GNSS[J]. Geomatics and Information Science of Wuhan University. DOI: 10.13203/j.whugis20240059

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Deformation Monitoring and Tidal Response Analysis of Strong Surge Tide Estuary Sluice Based on GNSS

1 Zhejiang Institute of Hydraulics & Estuary (Zhejiang Institute of Marine Planning and Design), Hangzhou 310017, China;
2 Zhejiang College of Construction, Hangzhou 311231, China;
3 School of Geodesy and Geomatics, Wuhan University, Wuhan 430079, China;
4 Hubei Luojia Laboratory, Wuhan 430079, China

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Received Date: September 17, 2024

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Objectives: The deformation of the river estuary sluice gate may be slightly affected by the tidal fluctuations, and studying the sluice gate's response to tidal deformation is of great significance for the safety and maintenance of the sluice gate. GNSS is a significant tool for deformation monitoring, commonly used for high-precision deformation monitoring of dams or extraction of vibrational characteristics of bridges. However, existing GNSS monitoring mode is inadequate for identifying the characteristics of tidal response signals. Methods: In this study, the Cao'e River Sluice was selected as the research subject. GNSS base and monitoring stations were set up to observe the sluice's deformation. And a method utilizing GNSS-based monitoring techniques was proposed to extract sub-millimeter-level deformation signals with a period of several hours, aimed at identifying the tidal response of the river estuary sluice gate. Results: The results show that due to tidal fluctuations, the Cao’e River Sluice has the greatest response to the larger M2 and S2 partial tides, but the response signal is weak, with the same frequency amplitude not exceeding 1.5 mm in the U direction, and not exceeding 1 mm in the X and Y directions. Overall, the sluice's response to each partial tide is linearly positively correlated in terms of amplitude size, but an excessive response to individual partial tides (such as S4, K1) has occurred, which may be caused by other signals of the same frequency. Conclusions: Using a 5-minute sliding step and a 2-hour solution window can effectively retain the characteristics of the tidal response. This method facilitates the accurate monitoring and assessment of the sluice gate's response to tidal influences, thereby enhancing the safety and maintenance strategies for estuarine sluice structures.
- GNSS,
- deformation monitoring,
- estuary sluice gate,
- tidal harmonic analysis,
- tidal response

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[1]	JING-XIANG G, HONG H. Advanced GNSS technology of mining deformation monitoring[J/OL]. Procedia Earth and Planetary Science, 2009, 1(1): 1081-1088. https://doi.org/10.1016/j.proeps.2009.09.166.
[2]	ZHAO L, YANG Y, XIANG Z, et al. A Novel Low-Cost GNSS Solution for the Real-Time Deformation Monitoring of Cable Saddle Pushing: A Case Study of Guojiatuo Suspension Bridge[J/OL]. Remote Sensing, 2022, 14(20): 5174. https://doi.org/10.3390/rs14205174.
[3]	QUESADA-OLMO N, JIMENEZ-MARTINEZ M J, FARJAS-ABADIA M. Real-time high-rise building monitoring system using global navigation satellite system technology[J/OL]. Measurement, 2018, 123: 115-124. https://doi.org/10.1016/j.measurement.2018.03.054.
[4]	WANG Chenhui, GUO Wei, MENG Qingjia, et al. Landslide Deformation Monitoring Method and Performance Analysis Based on GNSS Virtual Reference Station[J]. Geomatics and Information Science of Wuhan University, 2022, 47(6): 990-996. (王晨辉, 郭伟, 孟庆佳, 等. 基于虚拟参考站的GNSS滑坡变形监测方法及性能分析[J]. 武汉大学学报(信息科学版), 2022, 47(6): 990-996)
[5]	HUANG Guanwen, CHEN Zi, XU Yongfu., et al. (2023). GNSS real-time monitoring technology of expansive soil slope[J]. Acta Geodaetica et Cartographica Sinica, 52(11), 1873-1882.(黄观文, 陈孜, 徐永福. 膨胀土边坡GNSS实时监测技术[J]. 测绘学报, 2023, 52(11): 1873-1882.)
[6]	Guo Wen, WANG Guoquan, BAO Yan, et al. Tilt and Settlement Monitoring of High-Rise Buildings Using GNSS Precise Point Positioning and Seasonal Ground Deformation[J]. Geomatics and Information Science of Wuhan University, 2020, 45(7): 1043-1051. (郭稳, 王国权, 鲍艳, 等. 顾及季节性变形的GNSS高层建筑倾斜和沉降观测方法[J]. 武汉大学学报(信息科学版), 2020, 45(7): 1043-1051.)
[7]	CAO Shilong, LIU Genyou, WANG Shengliang, et al. Bias Characteristics and Accuracy Analysis of GPS Ultra-Long Baseline Solution[J]. Geomatics and Information Science of Wuhan University, 2023, 48(2): 260-267. (曹士龙, 刘根友, 王生亮, 等. GPS超长基线解算的误差特性与精度分析[J]. 武汉大学学报(信息科学版), 2023, 48(2): 260-267.)
[8]	Li Zhenghang, Wu Yunsun, Li Zhenhong, et al. (2000). Processing and Analysis of the External Deformation Data of Geheyan Dam[M]. Journal of Wuhan University of Surveying and Mapping, 482-484.(李征航, 吴云孙, 李振洪, 等. 隔河岩大坝外观变形数据的处理和分析[M]//武汉测绘科技大学学报. 2000: 482-484.)
[9]	JIANG Weiping, LIANG Yuhan, YU Zaikang, et al. Progress and Thoughts on Application of Satellite Positioning Technology in Deformation Monitoring of Water Conservancy Projects[J]. Geomatics and Information Science of Wuhan University, 2022, 47(10): 1625-1634.(姜卫平, 梁娱涵, 余再康, 等. 卫星定位技术在水利工程变形监测中的应用进展与思考[M]//武汉大学学报(信息科学版): 卷47. 2022: 1625-1634.)
[10]	XIAO R, SHI H, HE X, et al. Deformation Monitoring of Reservoir Dams Using GNSS: An Application to South-to-North Water Diversion Project, China[J/OL]. IEEE Access, 2019, 7: 54981-54992. https://doi.org/10.1109/ACCESS.2019.2912143.
[11]	BARZAGHI R, CAZZANIGA N, DE GAETANI C, et al. Estimating and Comparing Dam Deformation Using Classical and GNSS Techniques[J/OL]. Sensors, 2018, 18(3): 756. https://doi.org/10.3390/s18030756.
[12]	PAN L, XIONG B, LI X, et al. High-rate GNSS multi-frequency uncombined PPP-AR for dynamic deformation monitoring[J/OL]. Advances in Space Research, 2023, 72(10): 4350-4363. https://doi.org/10.1016/j.asr.2023.08.056.
[13]	WANG X, ZHAO Q, XI R, et al. Review of Bridge Structural Health Monitoring Based on GNSS: From Displacement Monitoring to Dynamic Characteristic Identification[J/OL]. IEEE Access, 2021, 9: 80043-80065. https://doi.org/10.1109/ACCESS.2021.3083749.
[14]	RAO R, LI C, HUANG Y, et al. Method for Structural Frequency Extraction from GNSS Displacement Monitoring Signals[J/OL]. Journal of Testing and Evaluation, 2019, 47(3): 20180087. https://doi.org/10.1520/JTE20180087.
[15]	CHEN Q, JIANG W, MENG X, et al. Vertical Deformation Monitoring of the Suspension Bridge Tower Using GNSS: A Case Study of the Forth Road Bridge in the UK[J/OL]. Remote Sensing, 2018, 10(3): 364. https://doi.org/10.3390/rs10030364.
[16]	SHEN Qianying, JI Xiaomei, ZHANG Wei, et al. Impact of estuarine storm surge barriers on spatiotemporal variation of tidal asymmetry in a delta[J]. Journal of Tropical Oceanography, 40(5), 1-9.(沈倩颖, 季小梅, 张蔚, 等. 河口挡潮闸对三角洲潮汐不对称时空变化的影响[J]. 热带海洋学报, 2021, 40(5): 1-9.)
[17]	WU Zhi-Lu, LIU Yan-Xiong, HE Xiu-Feng, et al. 2017. Inversion of ocean tidal loadings of marine constituents based on the GPS measurements in the offshore islands. Chinese Journal of Geophysics (in Chinese), 60(1): 61-69.(吴志露, 刘焱雄, 何秀凤, 等. 基于近岸海岛GPS数据反演海洋分潮负荷影响[J]. 地球物理学报, 2017, 60(1): 61-69.)
[18]	WOLANSKI E, ELLIOTT M. Estuarine water circulation[M/OL]//Estuarine Ecohydrology. Elsevier, 2016: 35-76[2024-02-07]. https://linkinghub.elsevier.com/retrieve/pii/B9780444633989000027.
[19]	Fu Senbiao. Research and Practice on Key Technologies of Cao'e River Dam Construction[M]. Water Resources and Hydropower Engineering, 45, 6- 10.(傅森彪. 曹娥江大闸工程建设关键技术研究与实践[M]//水利水电技术: 卷45. 2014: 6-10.)
[20]	TAKASU T, KUBO N, YASUDA A. Development, evaluation and application of RTKLIB: a program library for RTK-GPS[C]//GPS/GNSS symposium. 2007: 213-218.
[21]	PAWLOWICZ R, BEARDSLEY B, LENTZ S. Classical tidal harmonic analysis including error estimates in MATLAB using T_TIDE[J/OL]. Computers & Geosciences, 2002, 28(8): 929-937. https://doi.org/10.1016/S0098-3004(02)00013-4.
[22]	BRIGHAM E O, MORROW R E. The fast Fourier transform[J/OL]. IEEE Spectrum, 1967, 4(12): 63-70.
[23]	YIN Haitao, GAN Weijun, XIAO Genru. Modified Sidereal Filter and Its Effect on High-rate GPS Positioning[J]. Geomatics and Information Science of Wuhan University, 2011, 36(5): 609-611..(殷海涛, 甘卫军, 肖根如. 恒星日滤波的修正以及对高频GPS定位的影响研究[J]. 武汉大学学报信息科学版, 2011, 36(5): 609-611.)
[24]	CHOI K, BILICH A, LARSON K M, et al. Modified sidereal filtering: Implications for high‐ rate GPS positioning[J/OL]. Geophysical Research Letters, 2004, 31(22): 2004GL021621. https://doi.org/10.1029/2004GL021621.

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Deformation Monitoring and Tidal Response Analysis of Strong Surge Tide Estuary Sluice Based on GNSS

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