Ten-Year Monitoring of the Grandes Jorasses Glaciers Kinematics. Limits, Potentialities, and Possible Applications of Different Monitoring Systems

Abstract

In the Ferret Valley (NW Italy), anthropic activities coexist close to the Grandes Jorasses massif’s glaciological complex. In the past, break-off events have caused damage to people and infrastructure. These events concerned two specific sectors: the Montitaz Lobe (Planpincieux Glacier) and the Whymper Serac (Grandes Jorasses Glacier). Since 2010, permanent and discontinuous survey campaigns have been conducted to identify potential failure precursors, investigate the glacier instability processes, and explore different monitoring approaches. Most of the existing terrestrial apparatuses that measure the surface kinematics have been adopted in the Grandes Jorasses area. The monitoring sites in this specific area are characterized by severe weather, complex geometry, logistic difficulties, and rapid processes dynamics. Such exceptional conditions highlighted the limitations and potentialities of the adopted monitoring approaches, including robotic total station (RTS), GNSS receivers, digital image correlation applied to time-lapse imagery, and terrestrial radar interferometry (TRI). We examined the measurement uncertainty of each system and their monitoring performances. We discussed their principal limitations and possible use for warning purposes. In the Grandes Jorasses area, the use of a time-lapse camera appeared to be a versatile and cost-effective solution, which, however is not suitable for warning applications, as it does not guarantee data continuity. RTS and GNSS have warning potentialities, but the target installation and maintenance in remote environments remain challenging. TRI is the most effective monitoring system for early warning purposes in such harsh conditions, as it provides near-real-time measurements. However, radar equipment is very costly and requires extreme logistic effort. In this framework, we present data integration strategies to overcome the abovementioned limits and we demonstrate that these strategies are optimal solutions to obtain data continuity and robustness.