Monitoring of Critical Infrastructures by Micro-Motion Estimation: the Mosul Dam Destabilization

TL;DR

This paper introduces a satellite-based micro-motion estimation method for monitoring critical infrastructure, specifically applied to assess the destabilization of the Mosul Dam, revealing areas of resonance and crack development.

Contribution

The paper presents a novel satellite data analysis procedure combining Doppler tracking and multi-chromatic analysis for detailed dam stability monitoring.

Findings

Detection of resonance areas indicating cracks

Northern part of dam accelerating rapidly

High correlation between satellite and GNSS measurements

Abstract

In this paper, authors propose a new procedure to provide a tool for monitoring critical infrastructures. Particularly, through the analysis of COSMO-SkyMed satellite data, a detailed and updated survey is provided, for monitoring the accelerating destabilization process of the Mosul dam, that represents the largest hydraulic facility of Iraq and is located on the Tigris river. The destructive potential of the wave that would be generated, in the event of the dam destruction, could have serious consequences. If the concern for human lives comes first, the concern for cultural heritage protection is not negligible, since several archaeological sites are located around the Mosul dam. The proposed procedure is an in-depth modal assessment based on the micro-motion estimation, through a Doppler sub-apertures tracking and a Multi-Chromatic Analysis (MCA). The method is based initially on the Persistent Scatterers Interferometry (PSI) that is also discussed for completeness and validation. The modal analysis has detected the presence of several areas of resonance that could mean the presence of cracks, and the results have shown that the dam is still in a strong destabilization. Moreover, the dam appears to be divided into two parts: the northern part is accelerating rapidly while the southern part is decelerating and a main crack in this north-south junction is found. The estimated velocities through the PS-InSAR technique show a good agreement with the GNSS in-situ measurements, resulting in a very high correlation coefficient and showing how the proposed procedure works efficiently.