Deformation monitoring plays an important role in performance monitoring to ensure the reservoir dams and embankments are functioning as designed. This work should be the first deformation monitoring application of GNSS in China's huge South-to-North Water Diversion Project. A GNSS deformation monitoring system, equipped with 4G data transmission and automated data processing software, is established at Shuangwangcheng Reservoir, an important regulation control project on the Eastern Route. Precision evaluations of different observation sessions from both GPS and BDS are conducted, and results show that the performance of BDS is comparable to that of GPS, especially for longer observation session solutions. The 1 mm horizontal and 2 mm vertical precisions of daily solutions meet the deformation monitoring requirement of the project. The deformation time series reveal an uneven settlement of Shuangwangcheng Reservoir dam. The causes of deformation are analyzed and the water level change in the reservoir is deemed as the main factor. INDEX TERMS GNSS, BDS, deformation monitoring, dam, south-to-north water diversion project.

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The Urban Agglomeration in Yangtze River Delta is one of the most important economic and industrial regions in China. The City of Changzhou is one of the most important industrial citys in Yangtze River Delta Urban Agglomeration. Activities here include groundwater exploration. Groundwater overexploitation has contributed to the major land deformation in this city. The severity and magnitude of land deformation over time were investigated in Changzhou City. A Small Baseline Subset Interferometric Synthetic Aperture Radar (SBAS-InSAR) technology, provides a useful tool in measuring urban land deformation. In this study, a time series of COSMO-SkyMed and Sentinel-1A SAR images covering Changzhou City were acquired. SBAS-InSAR imaging technique was used to survey the extent and severity of land deformation associated with the exploitation of groundwater in Changzhou City. Leveling data was used to validate the SBAR-InSAR productions, the error of SBAR-InSAR annual subsidence results was within 2 mm. The results showed that three main land subsidence zones were detected at Xinbei, Tianning and Wujin District. Four subsidence points were selected to analyze the temporal and spatial evolution characteristics of land subsidence. The subsidence rate of P1 to P4 was −2.48 mm/year, −12.78 mm/year, −18.09 mm/year, and −12.69 mm/year respectively. Land subsidence over Changzhou showed a trend of slowing down from 2011 to 2017, especially in Wujin District. SBAR-InSAR derived land deformation that correlates with the water level change in six groundwater stations. Indicated that with groundwater rebound, the land rebound obviously, and the maximum rebound vale reached 9.13 mm.

This paper discusses the sea level determination using raw Intermediate Frequency (IF) data transmitted from the Global Navigation Satellite System (GNSS) and received by spaceborne GNSS-Reflectometry satellites, TechDemoSat-1. The reflected signals scattered from a sea ice surface and a rough sea surface are investigated. The altimetry method based on the bistatic group delay (code phase) from GNSS signals for sea level estimation are introduced. The two raw IF datasets recorded on January 18 and 27, 2015 for a duration of 40 seconds are analyzed to drain more information than Level 1 data. The results show a good consistence with mean sea surface (MSS) model. The orbit error of the GNSS-R satellite is corrected by a proposed method that combines the MSS and the least squares solution, which help evaluate the actual altimetry precision. The defect of fixed temporal resolution and fixed 4 onboard processing channels of Level 1 data can be improved by postprocessing using Software Define Receiver (SDR) to mine more information, so as to explore the potential. At the end, fake high signal-to-noise ratio (SNR) DDMs from the raw data are analyzed, which provides a reference for the altimetry of GNSS-R technique using raw data.

This paperanalyzes the interferometric measurements of ground-based Global Navigation Satellite Systems (GNSS) stations and proposes a novel method for sea surface states detection. The novel technique benefits from a costeffective data collection from a large number of global GNSS stations. In this study, we extend a traditional GNSS interferometry reflectometry (GNSS-IR) model so that it can be applied to a multilayer surface by considering the surface roughness, total reflectivity, and penetration loss in multilayer situations. Based on this model, the wavelet analysis is used to perform parameterization on the interferometric observations represented by the Signal to Noise Ratio (SNR). An integration factor and power curve are also proposed to characterize the surface state transition. One-year data from an Arctic geodetic GNSS station in the north of Canada are collected for analysis to validate the proposed approach with comparisons to the existing methods based on the amplitude and damping factors. The results show that the new method demonstrates good usability and sensitivity to detect surface state transitions, eg. icing, snowfall, and snow melting. However, the amplitude and damping factorbased methods derived from the single-layer model are only able to detect the pure ice surface and cannot respond to thick snow conditions. Finally, the high-resolution spaceborne images confirm the reliability of this method, exhibiting a great potential for long-term coastal sea surface detection based on the global geodetic GNSS stations and later being expected to be applied to sense cryosphere surface states.