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The Sarez Dam, currently recognized as the world's highest natural dam, holds immense economic significance, necessitating the reliable monitoring and early detection of potential deformations. This study utilizes the Beidou high-precision deformation monitoring system for the dam. Employing baseline network solutions, precise point positioning, and real-time kinematic positioning, the monitoring data from October 2021 to March 2023 were meticulously processed and comparatively analyzed. The results reveal varied degrees of displacement deformation at all sites, with horizontal deformation towards the lake center and vertical deformation showing subsidence. The three-dimensional vector average displacement is 29.1 mm, with an average monthly rate of 4.3 mm/month, and the maximum deformation is 41.4 mm. The cause of the horizontal deformation towards the lake center may be a slow collapse of the coastal soil and rock towards the lake center. Additionally, the monitoring detected a 7.2-magnitude earthquake on 23 February 2023, 52 km from the dam, causing an average displacement of 22.5 mm towards the south, which is 20 times the monthly deformation rate. In summary, deformation is present within the dam monitoring area, with a relatively stable deformation rate, warranting continued tracking and monitoring. Furthermore, earthquakes significantly impact dam deformation, necessitating heightened attention to the potential for seismic-induced dam damage in the future. [ABSTRACT FROM AUTHOR]

Accuracy and reliability are determining factors when selecting where to place a global navigation satellite system (GNSS) receiver for landslide monitoring and early warning in real time. Previous studies have revealed that surface occlusion models (SOMs) are beneficial to reduce the multipath error of satellite observation when the satellite line of sight is near the ground and improve the accuracy and reliability of GNSS monitoring. This paper investigates fitting functions to determine appropriate SOMs for GNSS stations located in different spatial environments. Based on their similarity to terrain patterns, Gaussian, Fourier, and sum of sine functions were chosen to build SOMs for the rover sites with different occlusions; the performance of fitting accuracy and application on the positioning were analyzed. The results indicate that the three functions present a similar performance considering the goodness of fit, but the Fourier and sum of sine functions can significantly improve the efficacy of SOMs and enhance performance in positioning for landslide monitoring. Therefore, these two functions can effectively support accurate and reliable GNSS landslide monitoring in real time. [ABSTRACT FROM AUTHOR]

Traditional PPP-RTK algorithm research has focused on users in a reference station network. However, if a proper PPP-RTK user algorithm can be designed for out-of-network users to achieve accurate and rapid positioning, the effective service area of existing reference station networks can be markedly expanded. To address the problem of extrapolating atmospheric corrections for out-of-network users, this study presents a single-reference-station (SRS) PPP-RTK model to address atmospheric delay corrections, by ensuring that only corrections from the closest reference station are used. Several numerical experiments were designed and conducted to compare the performance of the presented model and a widely used interpolation model. The extrapolation error distribution, mean and the maximum of absolute values of errors, and standard deviation of errors were selected as indicators. The results show that the SRS PPP-RTK model is significantly more accurate than the interpolation model. Thus, for out-of-network users, we suggest that the presented SRS PPP-RTK model should be used, and the residual atmospheric delays are needed to be estimated. [ABSTRACT FROM AUTHOR]