Analysis of H/V spectral ratio curves from passive seismic data acquired on glaciers worldwide

Estimations of bedrock topography below glaciers and ice thickness are vital for quantifying freshwater availability for surrounding populations and understanding the contribution of melting glaciers to sea-level rise in the context of global warming. While active seismology is commonly used for ice thickness estimation, the utilization of passive methods remains relatively rare. Passive seismology solutions offer cost-effectiveness, non-invasiveness and continuous monitoring capabilities that present valuable benefits in glaciological research.

Over the past two decades, numerous seismic stations have been deployed on glaciers worldwide for various purposes. Through passive seismology approaches, these seismic stations could show their potential as new sources of ice thickness measurements and feed the related database. For this purpose, we analyzed data of 3-components seismic sensors from different deployments as well as data from open access databases, such as IRIS, employing the Horizontal-to-Vertical Spectral Ratio (HVSR) technique. HVSR has been predominantly used in microzonation studies to determine site effects and the thickness of sediments in sedimentary basins.  Even though the use of this technique in glacial seismology is quite new, HVSR has been already utilized to estimate in-situ ice thickness, to retrieve the basal properties or to detect cavities under the ice.

Our primary objective is to demonstrate the potential of the HVSR technique to retrieve in-situ ice thickness on different glaciers. Subsequently, we will compare the HVSR results with different data sources including models, ground-penetrating radar or active seismology. By performing this comparison we evaluate the limitations of the HVSR method in an icy environment. We investigate these limitations by studying the effect of other natural agents such as wind on the H/V amplitude and fundamental frequency retrieved from the HVSR curves. Having a global understanding of these influences will eventually help deciphering variations in continuous H/V monitoring.