An overview of GPR investigation in the Italian Alps

2015 
Different applications of Ground Penetrating Radar (GPR) in glaciology are discussed through examples of mapping bedrock or internal features of glaciers or the characterization of snow properties and frozen materialsphysical parameters like electromagnetic velocity and density. A first example focuses on the appli¬cation of GPR to the estimate of snow water equivalent, density at scale of basin, of interest for the analysis of the hydrological behaviour during the snow melt. Examples on the radar survey to map bedrock, investigate the inner features of glaciers and monitor its evolution with time are herein discussed. We focus particularly on the radar survey of the Cevedale glacier, to get information on the thickness of glacier. Another example shows the result of geophysical characterization of iced-bodies in the Canin massif, located in the north-east part of the Italian Alps. Moreover, an example of a 4D GPR data survey is provided, demonstrat¬ing the applicability of GPR as an efficient tool to estimate the seasonal mass balance of a glacier, with a higher overall accuracy than direct methods. Ground Penetrating Radar (GPR) is generally used for locating targets in ice, determining ice and snow thickness, glacialogical studies and crevasse detection. In glaciology, the low electrical conductivity and reduced water content of glaciers allows penetration depths sufficient to detect the bedrock in most glaciers, with frequency ranging from 50 MHz to 200 MHz or even higher. The variations of electromagnetic properties of the inner features causes reflections that are well detectable (Godio and Rege, 2015) and provide extremely valuable data in glaciological studies of the hydrology and structural evolution of glaciers, for mapping and monitoring permafrost evolution (Carturan et al., 2012; Colucci et al., 2014).
    • Correction
    • Source
    • Cite
    • Save
    • Machine Reading By IdeaReader
    0
    References
    10
    Citations
    NaN
    KQI
    []