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.