Spatiotemporal Pattern Detection of Ground Deformations Induced by Extreme Rainfall using InSAR EGMS: The case of Cortina d’Ampezzo after Vaia Storm

Abstract. During October 2018 Vaia Storm occurred in the north of Italy, resulting in a huge amount of rainfall that was recorded. The focus here is given to Cortina d’Ampezzo area in the Veneto Region, due to the high importance of the area from touristic and sport perspectives and the presence of landslides. This study is devoted to investigating the impact of the severe sudden rainfall caused by this extreme atmospheric disturbance on the trends of ground deformations over this area, adopting a risk assessment perspective. The ground deformation Time Series (TS) have been derived from the European Ground Motion Service (EGMS) Ortho products derived from Sentinel-1 InSAR data. Then, according to the daily precipitation records and considering the time of this event as a turning temporal point, the TSs of all data points have been divided into pre-event and post-event phases. After obtaining the displacement rates in each phase, the quantified magnitude of changes in the pre-post rates has been calculated through a proposed simple formulation. The spatial distribution of the deformation parameters (i.e., pre-event displacement velocity and change in the pre-post displacement velocities) is found to be a practical tool for gaining comprehensive knowledge regarding the ground deformation and the effect of the extreme weather conditions on the displacement trends over the area. Furthermore, the positioning of the occurrence of deformation parameters has been compared to the landslide inventory of the area. The results showed that the extreme rainfall caused severe acceleration of displacements, more significant in horizontal East-West direction rather than vertical Up-Down direction. Some slight deceleration has been also detected. No initiation (or reactivation) of the stable zones was witnessed, and the portions with high magnitude of pre-event velocities are the ones whose displacement rates have been remarkably modified due to the severe event.