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Deformations of the reflectors of radio telescopes used in geodetic and astrometric VLBI observations belong to the class of systematic error sources which affect the estimated position of the telescope and which necessitates correction at the observation level. The determination of the gravitationally induced deformations requires some effort and needs specific modeling of the impact on the VLBI delay observables. This has been exercised on the Onsala 20 m radio telescope. In this publication, we present an elevation-dependent model for the contributions of the gravitational deformations to the delay observables for application in VLBI data analysis. New is that thermal expansion in some of the contributing components need to be applied also to the gravitational deformation effects. A further novelty is that we can substantiate the validity of and the need for these corrections. Concerning the validity we show that the empirical model used by astronomical colleagues for deliberately shifting the sub-reflector for gain optimization, exactly (within 0.5 mm RMS) matches the measured gravitationally induced displacement of the sub-reflector plus the change in focal length. The other evidence is the impact on the vertical component of the telescope’s coordinates of − 6.1 mm, which reduces the discrepancy determined in the computations of the ITRF2014 to 1.7 mm.

For describing height changes, ground movement models (bivariate polynomials) are used. These models approximate the ground movement measured at discrete bench marks by high-precision levelings. Because fault edges can be existent in the regions of investigation, they have to be detected and separated from the smooth ground movement. The present study proposes an algorithm that is able to detect and analyze subregions where fault edges are most likely. This algorithm is investigated based on a simulated example and tested using real sample regions: subregions containing a fault edge most likely can be identified. Furthermore, this fault edge is analyzed by revealing outliers in the approximation. If the spatial distribution and magnitude of these outliers is inconspicuous, the existence of a significant fault edge is very unlikely. Based on first considerations, the likeliness of a fault edge can even be analyzed by calculating curvature radii if using denser sampled measurements of remote sensors. These curvature radii can afterwards be used to quantify the damage-potential of the fault edge.