## 4 Conclusions  
Previous work (e.g., [2; 36; 41]) highlighted the capability of satellite techniques for dam monitoring. This research aims to emphasise that comprehensive monitoring is achievable using satellite techniques. In particular, reliable displacements of their temporal behaviour were retrieved, in addition to the filling-emptying cycles of the water level and reservoir-dam system temperature. The water surface extent was estimated by employing the same satellite dataset (SAR images) used for the interferometric processing. Results were estimated with very high accuracy (\(r^{2}\) = 0.97). Water temperature time series was automatically retrieved by means of the Google Earth Engine platform processing all the clear sky Landsat 8 TIRS images available. Comparing time series of air temperature measured in situ and water temperatures estimated from thermal infrared remote sensing a strong agreement was shown both in terms of the range of variability (\(\approx\) 280-305 K) and phase shift (2 days). A quasi PS-InSAR algorithm, using a full-graph MBC method and a nonlinear displacement trend model was applied to both ascending and descending SAR images. The composition of the slant displacements allowed the retrieval of the temporal evolution of total displacement orthogonal to the dam crest. The comparison with displacements measured via GNSS showed a relatively good agreement; indeed, both exhibit the same temporal behaviour, with plateaus at maximum partially overlapping (10 days). The interpolation with a sinusoidal function for both GNSS and PS-InSAR measures allows a better description of the positive and negative displacements occurring during the filling, storage, and emptying phases. GNSS and quasi-PS-InSAR time series exhibited comparable time behaviours. Although there was a time shift, both time series were characterised by a plateau. The plateaus were partially overlapping (\(\approx\) 10 days). Different MBC methods and interferometric models are planned to be tested to improve the matching between remote and in situ displacements. However, these first outcomes suggest that a comprehensive remote sensing approach could represent a good complementary or alternative solution to monitor medium-small reservoirs, which often lack any adequate monitoring systems. In order to confirm these preliminary results, it is necessary to plan a new in situ campaign spanning a longer time period in order to increase the number of observations  
Figure 10: The temporal behaviour (DOY in _x_-axis) of the horizontal total displacements orthogonal to the dam (\(D_{\text{TOT}}\), mm) is estimated via Global Navigation Satellite System (GNSS) (grey dots). A sinusoidal interpolation curve and confidence band of \(\pm\)2 \(\times\)\(\sigma_{\text{XY}}\) between measured and interpolated values (dark grey lines) are reported to facilitate the interpretation of the phenomenon (continuous line). The interpolation curves at the 10 th and 90 th percentiles of the raw data are reported (pale blue band) as a measure of its variability. while ensuring contemporaneity between the GNSS and PS-InSAR measurements. It is also necessary to evaluate the relationship of the displacements with thermal and hydrological forcing factors over a more consistent temporal time span, distinguishing between the emptying, storage, and filling periods over different years. It is planned to complete the analysis using images acquired by the COSMO-SkyMed constellation, which have a higher spatial resolution (up to 1 m) and lower revisit time (e.g., up to 24 h using the full four satellite constellation), thus allowing more PS points to be obtained over the dam and covering the period over which GNSS measurements are currently available. Additionally, the use of the Capella's [81] high revisit SAR X-band 18 satellites constellation (36, once fully operational) will allow the production of interferometric images at the resolution down to 0.5 m and hourly revisit time, which looks promising.