## 1 Introduction
The deformation time series measured using GNSS techniques can reveal an uneven settlement of a dam (e.g., [31]), allowing also the analysis of the causes of deformations, including the water level change and the water-dam system temperature deemed as the main factors. DInSAR techniques can be applied to detect subsurface anomalies including cavities due to seepage [32]. The rate of continuous nonlinear deformations of a dam over time caused by variable water levels and other forcing factors can be evaluated using a persistent scattering InSAR (PS-InSAR) technique [33]. Recently, the InSAR technique has been used for the analysis of the destabilisation process of the Mosul dam (Iraq) [34; 35], using the Constellation of Small Satellites for Mediterranean Basin Observation (COSMO-SkyMed) and Sentinel-1A images. In this first study, the cumulative deformation of a dam using different SAR-sensors was mapped and two different deformation rates linked with on-site dam works were captured. In the following study, the authors took advantage of a deformation InSAR analysis together with numerical simulation modelling to shed new light on the ongoing subsidence process. The discrimination between deformations and seasonal movements over a dam (the Plover Cove dam, Hong Kong, China) has been also discussed by [36] using PS-InSAR. This technique was originally introduced in 2001 [37]. PS-InSAR makes use of natural targets with high reflectivity over time to measure ground motions through a stack of SAR images (a review of PS-InSAR techniques is given by [38]). Some authors have shown the suitability of this method for dam monitoring [1; 29; 33; 39]. Some limits of the PS-InSAR technique for dam monitoring are summarised in [9]. About the deformation monitoring analysis, the Small Baseline Subset (SBAS) technique based on the use of a large number of SAR acquisitions distributed with small baseline subsets can also be applied [40]. A multi-sensor full-resolution SBAS technique [41] can be used by jointly processing data acquired by compatible SAR sensors to monitor earth dams for long periods, thus showing displacements because of the consolidation process [42]. Finally, the integration of PSI and SBAS techniques allows monitoring of both linear and nonlinear ground displacements in mining structures after a collapse event occurred in the tailings of the Fundao dam in Brasil [43]. Sources of inaccuracies are both the baseline of a given interferogram, compared to the critical value [44; 45], and the precision of the ephemeris (Copernicus Sentinels POD Data Hub) [46]. The baseline, indeed, controls the coherence of the interferogram, while the ephemeris accuracy, for instance, has an influence on the conversion of interferogram phases to absolute height require a relative baseline accuracy of 5 cm or even better [47]. The Castello dam was recently studied through in situ measurements, numerical models, and satellite techniques. A preliminary analysis [48] highlighted a significant correlation between water levels derived by optical remote sensing and displacements measured via the Global Navigation Satellite System (GNSS) over a short period (three months). Thereafter, the GNSS displacements were compared with existing models implemented for concrete dams (including hydraulic models by [PERSON] [28] and geotechnical Finite Element Method (FEM) [49]). The comparison between the modelled planimetric components of the displacements and GNSS data (over a time period of 2 years, between 2011 and 2013) appears to be satisfactory, with millimetric residuals [50]; in the same study, a comparison between the displacements measured by GNSS time series and traditional geodetic instruments (total station and spirit levelling), revealed a good agreement for both the vertical and the planimetric components. The advantage of using as reference a GNSS permanent station positioned relatively far from the dam (\(\approx\) 30 km away, at Agrigento) allowed the exclusion of any influence due to the site deformations.