In this study, we employed multitemporal InSAR (Interferometric Synthetic Aperture Radar) (MT-InSAR) to detect spatial and temporal ground deformations over the whole Tianjin region in the North China Plain area. Twenty-five ascending Sentinel-1A terrain observation by progressive scans (TOPS) synthetic aperture radar (SAR) scenes covering this area, acquired from 9 January 2016 to 8 June 2017, were processed using InSAR time series analysis. The deformation results derived from Sentinel-1A MT-InSAR were validated with continuously operating reference stations (CORS) at four sites and four stations of the Crustal Movement Observation Network of China (CMONOC). The overall results show good agreement, demonstrating the suitability of applying Doris with Sentinel-1A data to high-resolution monitoring of surface deformation. Significant deformation variations have been observed in different parts of Tianjin. These gradually increased from the central part of the metropolitan area to the nearby suburbs. The deformation rate of the main urban area is well-balanced and it is also relatively linear, with uplifting rates ranging from 0 to 20 mm/yr. However, due to the diversity of the geological conditions and anthropogenic activities, remarkable signs of subsidence were found in several parts of Tianjin. In particular, the south-western part of Wuqing District and western part of Beichen District showed subsidence rates of up to −136 mm/yr. We also found that, in addition to groundwater over-exploitation and lithological characteristics, additional factors also influence ground subsidence, including dynamic loads (e.g., railways), static loads (e.g., urban construction), and groundwater recharging.

Surface vertical deformation includes the Earth’s elastic response to mass loading on or near the surface. Continuous Global Positioning System (CGPS) stations record such deformations to estimate seasonal and secular mass changes. We used 41 CGPS stations to construct a time series of coordinate changes, which are decomposed by empirical orthogonal functions (EOFs), in northeastern Tibet. The first common mode shows clear seasonal changes, indicating seasonal surface mass re-distribution around northeastern Tibet. The GPS-derived result is then assessed in terms of the mass changes observed in northeastern Tibet. The GPS-derived common mode vertical change and the stacked Gravity Recovery and Climate Experiment (GRACE) mass change are consistent, suggesting that the seasonal surface mass variation is caused by changes in the hydrological, atmospheric and non-tidal ocean loads. The annual peak-to-peak surface mass changes derived from GPS and GRACE results show seasonal oscillations in mass loads, and the corresponding amplitudes are between 3 and 35 mm/year. There is an apparent gradually increasing gravity between 0.1 and 0.9 μGal/year in northeast Tibet. Crustal vertical deformation is determined after eliminating the surface load effects from GRACE, without considering Glacial Isostatic Adjustment (GIA) contribution. It reveals crustal uplift around northeastern Tibet from the corrected GPS vertical velocity. The unusual uplift of the Longmen Shan fault indicates tectonically sophisticated processes in northeastern Tibet.

Modeling nonlinear vertical components of a GPS time series is critical to separating sources contributing to mass displacements. Improved vertical precision in GPS positioning at stations for velocity fields is key to resolving the mechanism of certain geophysical phenomena. In this paper, we use ensemble empirical mode decomposition (EEMD) to analyze the daily GPS time series at 89 continuous GPS stations, spanning from 2002 to 2013. EEMD decomposes a GPS time series into different intrinsic mode functions (IMFs), which are used to identify different kinds of signals and secular terms. Our study suggests that the GPS records contain not only the well-known signals (such as semi-annual and annual signals) but also the seldom-noted quasi-biennial oscillations (QBS). The quasi-biennial signals are explained by modeled loadings of atmosphere, non-tidal and hydrology that deform the surface around the GPS stations. In addition, the loadings derived from GRACE gravity changes are also consistent with the quasi-biennial deformations derived from the GPS observations. By removing the modeled components, the weighted root-mean-square (WRMS) variation of the GPS time series is reduced by 7.1% to 42.3%, and especially, after removing the seasonal and QBO signals, the average improvement percentages for seasonal and QBO signals are 25.6% and 7.5%, respectively, suggesting that it is significant to consider the QBS signals in the GPS records to improve the observed vertical deformations.