Abstract. Subarctic peatlands underlain by permafrost contain significant amounts of
organic carbon. Our ability to quantify the evolution of such permafrost
landscapes in numerical models is critical for providing robust predictions of
the environmental and climatic changes to come. Yet, the accuracy of
large-scale predictions has so far been hampered by small-scale physical processes
that create a high spatial variability of thermal surface conditions,
affecting the ground thermal regime and thus permafrost degradation
patterns. In this regard, a better understanding of the small-scale
interplay between microtopography and lateral fluxes of heat, water and snow
can be achieved by field monitoring and process-based numerical modeling.
Here, we quantify the topographic changes of the Šuoššjávri
peat plateau (northern Norway) over a three-year period using drone-based
repeat high-resolution photogrammetry. Our results show thermokarst
degradation is concentrated on the edges of the plateau, representing 77 %
of observed subsidence, while most of the inner plateau surface exhibits no
detectable subsidence. Based on detailed investigation of eight zones of the
plateau edge, we show that this edge degradation corresponds to an annual
volume change of 0.13±0.07 m3 yr−1 per meter of retreating
edge (orthogonal to the retreat direction). Using the CryoGrid3 land surface model, we show that these degradation
patterns can be reproduced in a modeling framework that implements lateral
redistribution of snow, subsurface water and heat, as well as ground
subsidence due to melting of excess ice. By performing a sensitivity test
for snow depths on the plateau under steady-state climate forcing, we obtain
a threshold behavior for the start of edge degradation. Small snow depth
variations (from 0 to 30 cm) result in highly different degradation
behavior, from stability to fast degradation. For plateau snow depths in the range of field measurements, the simulated annual volume changes are broadly in agreement with the results of the drone survey. As snow depths are clearly correlated with ground surface temperatures, our results indicate
that the approach can potentially be used to simulate climate-driven
dynamics of edge degradation observed at our study site and other peat
plateaus worldwide. Thus, the model approach represents a first step
towards simulating climate-driven landscape development through thermokarst
in permafrost peatlands.