Quantifying the influence of soil, snowpack, topography and vegetation properties on soil hydro-thermal behavior across an Arctic watershed in a discontinuous permafrost environment

In Arctic regions, understanding the link between soil physical properties, soil thermal behavior and landscape properties is particularly challenging yet is critical for predicting the storage and flux of carbon and water in a changing climate. This study aims at improving the understanding of the various subsurface hydro-thermal behaviors and the multi-dimensional relationships between subsurface and surface properties in discontinuous permafrost environments. Our work takes place in a watershed near Nome (Alaska) that shows significant heterogeneity in vegetation, snowpack, geomorphic and subsurface characteristics. We use a variety of aerial and ground-based measurements, including a novel Distributed Temperature Profiling (DTP) system that provides unprecedented vertical and horizontal distribution of soil temperature. These measurements complement electrical imaging, seismic refraction, CO₂ efflux and water content measurements, soil sample analysis and UAV-based mapping of snow thickness and vegetation characteristics. Data integration and analysis is supported by numerical approaches that simulate hydrological, thermal and biogeochemical processes.

Overall, this study enables the identification of watershed structure and associated subsurface and landscape properties. Our unique dataset has highlighted significant relationships between above- and belowground characteristics including: (1) the effects of topographic lows and tall shrubs on thick snowpack, and with subsurface characteristics on the distribution of taliks (year-round unfrozen soil); (2) the significant spatial co-variability between permafrost characteristics, vegetation, and geomorphology, with graminoid covered areas corresponding to zones having the shallowest permafrost table; and (3) the significant influence of soil hydrological and thermal behavior on soil CO₂ efflux. We are also using numerical models with adequate level of process representation to improve our understanding of how near-surface permafrost transition to talik and absence of permafrost. The obtained information is expected to be useful for improving predictions of Arctic ecosystem feedbacks to climate.