Glacier modeling with geophysical data constraints: a case study on the Indren Glacier (NW Italy).

The increase in global temperature over the last years has caused the loss of a significant amount of ice bodies all over the world. In particular, mountain or alpine glaciers have shown higher sensitivity to climate variations compared to other glacial environments due to their elevation and reduced areal extent. The consequences of ice melting in Alpine regions include natural hazards, shortage of the water resource for drinking, agricultural and power generation purposes, ecological impacts and economic repercussions on local communities. In these areas, it is therefore essential to analyze variations in ice volume to understand the evolution of glaciers and their response to climate change, as well as to implement effective adaptation measures for these highly vulnerable spots. This thesis aims to utilize acquisition and modeling techniques to estimate glacial thickness, with the goal of characterizing and monitoring the impacts of climate change on Alpine Glaciers. The Indren Glacier (NW Italian Alps) is selected as test site for the application of the considered methodologies. An analysis of both external and internal variations is carried out on this glacier. The first fast assessment of ice thickness variations over time was conducted considering the Digital Elevation Models of the area for three different years (1999, 2008 and 2018), covering a time span of more than 20 years from the present days. Despite the different resolution of the considered models, this first study provides a rough estimation of the variations in the glacier’s surface topography over the last two decades. It was obtained that the highest elevation variations have occurred between 2008 and 2018. These results are also confirmed by a temperature increase registered over this decade at the closest weather station. For the analysis of the internal variations, the measurement and quantification of the ice thickness was required. First, Ground Penetrating Radar (GPR) data, acquired in 2020 with a 200-MHz and 70-MHz antenna, were processed and interpreted. This geophysical instrument is ideal for depth estimation in glacial environments due to the low electrical conductivity of ice, which preserves the electromagnetic signal from strong attenuation and enables deep penetration. However, this device loses effectiveness when encountering water-rich or temperate ice. In addition, since GPR data is usually acquired over a sparse network of linear profiles, a bottom topography modeling was required to obtain ice thickness in areas not covered by radar surveys. For this purpose, it was chosen to combine the GPR data with the glaciological model of Clarke et al. (2013) through the Glacier Thickness Estimation (GlaTE) algorithm, which is able to minimize the mismatch between observed and predicted data. The application of GlaTE model to the Indren Glacier demonstrated the benefits of introducing empirical data to constrain the theoretical model, which otherwise significantly underestimated the ice thickness. Finally, a preliminary temporal study of the Indren Glacier was also performed, exploiting historical open access data and the Minimal Glacier Model, as tool for the analysis of internal variations. This model allowed for the investigation of the fundamental connections between the glacier’s length and the climate, as well as ice thickness. The model’s simplicity and limited historical data for calibration prevented robust results, but it could be a starting point for more complex models.