The North China Plain (NCP) has been experiencing the most severe groundwater depletion in China, leading to a broad region of vertical motions of the Earth’s surface. This paper explores the seasonal and linear trend variations of surface vertical displacements caused by the groundwater changes in NCP from 2009 to 2013 using Global Positioning System (GPS) and Gravity Recovery and Climate Experiment (GRACE) techniques. Results show that the peak-to-peak amplitude of GPS-derived annual variation is about 3.7~6.0 mm and is highly correlated (R > 0.6 for most selected GPS stations) with results from GRACE, which would confirm that the vertical displacements of continuous GPS (CGPS) stations are mainly caused by groundwater storage (GWS) changes in NCP, since GWS is the dominant component of total water storage (TWS) anomalies in this area. The linear trends of selected bedrock-located IGS CGPS stations reveal the distinct GWS changes in period of 2009–2010 (decrease) and 2011–2013 (rebound), which are consistent with results from GRACE-derived GWS anomalies and in situ GWS observations. This result implies that the rate of groundwater depletion in NCP has slowed in recent years. The impacts of geological condition (bedrock or sediment) of CGPS stations to their results are also investigated in this study. Contrasted with the slight linear rates (−0.69~1.5 mm/a) of bedrock-located CGPS stations, the linear rates of sediment-located CGPS stations are between −44 mm/a and −17 mm/a. It is due to the opposite vertical displacements induced by the Earth surface’s porous and elastic response to groundwater depletion. Besides, the distinct renewal characteristics of shallow and deep groundwater in NCP are discussed. The GPS-based vertical displacement time series, to some extent, can reflect the quicker recovery of shallow unconfined groundwater than the deep confined groundwater in NCP; through one month earlier to attain the maximum height for CGPS stations nearby shallow groundwater depression cones than those nearby deep groundwater depression cones.

The Chinese BeiDou Navigation Satellite System has shown potential for precise positioning with a comparable accuracy to that of the Global Positioning System (GPS) at the centimeter level for the horizontal component and the sub-centimeter level for the vertical component. However, a longer convergence time limits the performance of BeiDou precise point positioning (PPP) compared to the GPS PPP solutions. In this study, we applied the tropospheric delay information, derived from the European Centre of Medium-Range Weather Forecasts (ECMWF) analysis and prediction data, into the simulated real-time BeiDou-only and BeiDou/GPS PPP to augment the solutions. Observations from stations in Southeast Asia, which are capable of tracking the BeiDou constellation from the International GNSS Service (IGS) Multi-GNSS Experiment and Pilot Project (MGEX) network, are processed with different strategies: the standard PPP and the introduced ECMWF-augmented PPP with analysis and prediction data, respectively. The positioning results demonstrate that the ECMWF-augmented BeiDou-only and BeiDou/GPS PPP methods using prediction data perform as well as those using analysis data. In the case of BeiDou-only PPP scenarios, remarkable advancements of 80.6% for the convergence time are achieved by two ECMWF-augmented PPP solutions with respect to the standard PPP method. For the positioning accuracy, the two proposed augmented PPP methods attain 6.6 cm in three-dimensional (3D) accuracy when the standard PPP solution get converged (10 cm), representing a remarkable improvement of 34%. As for the north/east/up component, improvements of 14.7 and 8% for positioning accuracy are obtained for the north and east components, respectively, while a remarkable improvement of 37.3% is achieved for the vertical component. In terms of the BeiDou/GPS PPP solutions, the ECMWF-augmented PPP scenarios attain over 10% improvements in 3D accuracy in all processing session lengths. These improvements totally come from the vertical component, whereas almost no enhancements are obtained in two horizontal components.

The development of low-cost, small, modular receivers and their application in diverse scenarios with complex data quality has increased the requirements of single-frequency carrier-phase data preprocessing in real time. Different methods have been developed, but successful detection is not always ensured. The issue is crucial for high-precision positioning with Global Positioning System (GPS). Aiming at a high detection rate and low false-alarm rate, we propose a new cycle-slip detection method based on fuzzy-cluster. It consists of two steps. The first is identification of the epoch when cycle slips appear using Chi-square test based on time-differenced observations. The second is identification of the satellite which suffers from cycle slips using the fuzzy-cluster algorithm. To verify the performance of the proposed method, we compared it to a current robust method using real single-frequency data with simulated cycle slips. Results indicate that the proposed method outperforms the robust estimation method, with a higher correct-detection rate and lower undetection rate. As the number of satellites simulated with cycle slips increases, the correct-detection rate rapidly decreases from 100% to below 50% with the robust estimation method. While the correct-detection rate using the proposed method is always more than 60%, even if the number of satellites simulated with cycle slips reaches five. In addition, the proposed method always has a lower undetection rate than the robust estimation method. Simulation showed that when the number of satellites with cycle slips exceeds three, the undetection rate increases to more than 30%, reaching ~70% for the robust estimation method and less than 30% for the proposed method.