We apply an automated picking and inversion algorithm to a 3-D GPR data set acquired on an alpine glacieret, to study its internal stratigraphy, density distribution, total volume, and water content. GPR surveys are particularly useful for glaciological studies, since the transmitted signal can propagate efficiently through the entire glacier volume, while the large number of recorded traces makes any quantitative analysis statistically sound. The applied auto-picking algorithm is designed to accurately and objectively identify the main reflections within a GPR data set, and to characterize them in terms of their peak amplitudes, travel times, and polarities. The inversion algorithm then uses these quantities to recover the subsurface stratigraphy and EM velocity distribution along each GPR profile. In air-ice mixtures, the EM velocity is linked to the density through well-known empirical formulas. Therefore, our inversion algorithm is able to recover the density distribution within a glacier, and combine it with the internal stratigraphy to estimate its water content. By applying this procedure to a 3-D GPR data set, we can obtain an accurate model of an entire glacier, while 4-D surveys can be used to monitor its temporal changes and estimate its annual and seasonal mass balances.
