Iterative Singular Spectral Analysis of the Correlation between Land Subsidence and Groundwater Level Evolution in Beijing Plain Based on InSAR
The Beijing Plain is currently experiencing significant land subsidence,which requires a thorough analysis of its spatial and temporal evolution mechanism to predict future trends.This is essential in ensuring the safety of the city while effectively preventing and controlling land subsidence.This paper utilizes the PS-InSAR method to collect land subsidence data,which is validated for accuracy through leveling data.Moreover,based on the singular spectrum analysis and frequency-spectrum chec-king,the iterative singular spectral analysis(ISSA)method is proposed to decompose the long time series data of land subsid-ence into primary trends and periodic characteristics,offering insights into the time series evolution of land subsidence and groundwater level in the study area.It is found as follows.① The land subsidence is characterized by three main trend charac-teristics of continuous subsidence.subsidence mitigation.and re-subsidence from 2011 to 2016.and that subsidence continues to develop from 2017 to 2020.but the overall trend is more stable.② The periodic characteristics of land subsidence,which is char-acterized by the obvious seasonal difference of land subsidence in the study area,and the land subsidence in summer is more seri-ous than that in winter from 2011 to 2020.③ The primary cause of land subsidence in the Beijing Plain is changes in groundwa-ter level,and that the groundwater level changes of the second and third confined aquifers show a strong positive correlation with land subsidence in the severe and more severe subsidence areas.
land subsidencePS-InSARgroundwater level changefrequency-spectrum checkingiterative singular spectral anal-ysistime-series feature decomposition
万方数据
维普
