Determining Two-Dimensional Subglacial Drainage Systems of an Alpine Glacier by Solving Inverse Problems

Abstract:

The growth of data collection acquisition and advances in numerical modelling have improved our understanding of subglacial systems over the last decades. However, integrating data sets into increasingly complex numerical models remains challenging. Here we present a framework which enables to infer two-dimensional subglacial channels from water pressure and tracer-transit times at different snapshots across the melt season. First, we use a geostatistical subglacial channel generator based on flow routing algorithms, which produces different scenarios of likely channel networks. This is relevant as flow routing algorithms are sensitive to small-scale features and uncertainties in bed elevation data sets can be significant. Second, a steady-state flow model is used compute water pressure and transit times in the subglacial system. Last, a likelihood function is used to find the set of subglacial channel networks that are consistent with observed water pressure and tracer-transit times. The framework is applied to the Gorner Glacier, Switzerland, which presents one of the most complete currently available data sets, including borehole water pressure, tracer experiments and meteorological variables. Results indicate that it is possible to identify locations where subglacial channels are more likely. In addition, we show that different network structures can equally satisfy the field data. Even in the presence of a dense dataset, observations are too sparse to fully characterize the subglacial system, highlighting the importance of working with multiple scenarios.