Deformation monitoring of ring rockfill dam in pumped storage power station based on spaceborne InSAR

doi:10.13474/j.cnki.11-2246.2025.1212

Abstract

Abstract: This study aims to investigate the deformation characteristics of the annular rockfill dam in pumped-storage power plants using time-series spaceborne InSAR deformation monitoring technology.The permanent scatterer InSAR (PSInSAR)processing technique was employed,combined with high-precision digital elevation model (DEM)data,to monitor the surface deformation of the annular rockfill dam in the upper reservoir of the Zhanghewan pumped-storage power plant.The monitoring accuracy of InSAR was validated using ground-based synchronous monitoring data from high-precision measurement robots,and the deformation characteristics of the annular rockfill dam were analyzed.The results show that the dam body and slopes of the upper reservoir in the Zhanghewan power plant exhibited an overall uplift trend during the observation period,which is preliminarily attributed to the temperature increase from winter to summer.The correlation coefficient between the deformation rates of monitoring points obtained by InSAR technology and the ground-based synchronous observations reached 0.838,with a root-mean-square error (RMSE)of 7.24mm/a.The cumulative displacement of monitoring points in the annular rockfill dam is significantly correlated with temperature.The influence of temperature on the displacement of monitoring points exhibits a slow nonlinear characteristic,and the responses of different monitoring points are divergent.The displacement of monitoring points shows a strong correlation with water level changes,indicating that water levels have a significant impact on the upstream-downstream displacement of specific points.This study provides important references for the research and application of InSAR deformation monitoring for large-area structures such as annular rockfill dams.

Key words: InSAR, ring rockfill dam, deformation monitoring, pumped storage power station, deformation characteristics

CLC Number:

P237

WAN Peng, ZHAI Ruoming, DING Bangning, LI Jianzhou, ZOU Shuangchao. Deformation monitoring of ring rockfill dam in pumped storage power station based on spaceborne InSAR[J]. Bulletin of Surveying and Mapping, 2025, 0(12): 71-76.

References

[1] 李德仁, 廖明生, 王艳.永久散射体雷达干涉测量技术[J].武汉大学学报(信息科学版), 2004, 29(8):664-668.
[2] FERRETTI A, FUMAGALLI A, NOVALI F, et al.A new algorithm for processing interferometric data-stacks:squeeSAR[J].IEEE Transactions on Geoscience and Remote Sensing, 2011, 49(9):3460-3470.
[3] 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.
[4] 尹宏杰, 朱建军, 李志伟, 等.基于SBAS的矿区形变监测研究[J].测绘学报, 2011, 40(1):52-58.
[5] CHEN Fulong, LIN Hui, LI Zhen, et al.Interaction between permafrost and infrastructure along the Qinghai-Tibet Railway detected via jointly analysis of C-and L-band small baseline SAR interferometry[J].Remote Sensing of Environment, 2012, 123:532-540.
[6] KIMURA H, YAMAGUCHI Y.Detection of landslide areas using satellite radar terferometry[J].Photogrammetric Engineering and Remote Sensing, 2000, 66(3):337-344.
[7] YE Xia, KAUFMANN H, GUO Xiaofang.Differential SAR interferometry using corner reflectors[J].IEEE International Geoscience and Remote Sensing Symposium, 2002, 2:1243-1246.
[8] YE Xia, KAUFMANN H, GUO X F.Landslide monitoring in the Three Gorges area using D-INSAR and corner reflectors[J].Photogrammetric Engineering & Remote Sensing, 2004, 70(10):1167-1172.
[9] ZHU Wu, ZHANG Qin, DING Xiaoli, et al.Landslide monitoring by combining of CR-InSAR and GPS techniques[J].Advances in Space Research, 2014, 53(3):430-439.
[10] CAL F, ARDIZZONE F, CASTALDO R, et al.Enhanced landslide investigations through advanced DInSAR techniques:the Ivancich case study, Assisi, Italy[J].Remote Sensing of Environment, 2014, 142:69-82.
[11] 刘筱怡, 杨志华, 郭长宝, 等.基于SBAS-InSAR的鲜水河断裂带蠕滑型滑坡特征研究[J].现代地质, 2017, 31(5):965-977.
[12] ZHAO Chaoying, KANG Ya, ZHANG Qin, et al.Landslide identification and monitoring along the Jinsha River Catchment (wudongde reservoir area), China, using the InSAR method[J].Remote Sensing, 2018, 10(7):993.
[13] 朱建军, 李志伟, 胡俊.InSAR变形监测方法与研究进展[J].测绘学报, 2017, 46(10):1717-1733.

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