Quantifying Subglacial Hydrologic Uncertainty with Stochastic Simulation

Abstract:

Subglacial topography exerts an important control on the routing of water beneath glaciers, yet it remains difficult to quantify hydrologic uncertainty with respect to topographic uncertainty. Topographic interpolations of ice-penetrating radar bed measurements are typically made with kriging, as well as with mass conservation, where ice flow dynamics are used to constrain bed geometry. However, these techniques generate bed topographic models that are unrealistically smooth at small scales, which biases subglacial water flowpath models and makes it difficult to rigorously quantify uncertainty in subglacial drainage patterns. To address this challenge, we adapt a geostatistical simulation method with probabilistic modeling to stochastically simulate multiple realizations of bed topography such that the interpolated topography reproduces the spatial statistics of the ice-penetrating radar data. We use a Markov model for cross-covariance to integrate mass conserving topography as a secondary constraint. We demonstrate this technique for Jakobshavn Glacier in Greenland and apply a water routing model to each of the simulated realizations. Our results show that many of the water flowpaths significantly change with each topographic realization, thereby demonstrating the importance of quantifying topographic uncertainty. This also shows that our proposed geostatistical simulation method can be useful for assessing uncertainty in subglacial flowpaths.