Modelling the transition in ice-dynamics from land- to lake-terminating glaciers: a case study in Iceland

Glaciers interact with adjacent proglacial lakes through a range of thermomechanical processes. These interactions occur in addition to climate-driven ablation but are capable of amplifying or modifying climatic effects through various feedback mechanisms. In particular, the connection between lake water-level and the subglacial hydrological system can reduce basal friction, which in turn leads to increased glacier flow and dynamic thinning. This creates a positive feedback loop in which decreased effective pressure, also driven potentially by negative surface mass balance, enhances flow velocity, in line with similar processes observed at marine-terminating glaciers.

Our aim in this study is to develop a simple model that can be used to understand the critical controls on the dynamic behaviour of glaciers as they transition from land- to lake-terminating systems. Here, we investigate the behaviour of Skaftafellsjökull in Iceland, which has undergone such a transition over the past twenty-five years. More specifically, we use the Shallow Shelf Approximation (SSA) in Elmer Ice to model ice dynamics, incorporating a water pressure-dependant friction law to model basal sliding with a simple parameterization of basal water pressure.

The model successfully reproduces the observed velocity patterns, capturing the shift from deceleration near the front in 2010 to pronounced acceleration in 2018–2020, reflecting the growing influence of the proglacial lake. We find a threshold behaviour between basal water pressure and ice velocity, whereby small increases in water pressure beyond a critical value led to strong acceleration, consistent with previous empirical observations. Furthermore, our results imply that surface thinning exerts a stronger control on the near terminus acceleration than the observed terminus retreat.  Our results suggest that the modelling framework developed provides a valuable tool for simulating these complex interactions in a computationally efficient manner.