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Modeling the spatio-temporal variability in subsurface thermal regimes across a low-relief polygonal tundra landscape...

Publication Type
Journal
Journal Name
The Cryosphere
Publication Date
Page Numbers
2241 to 2274
Volume
10
Issue
5

Vast carbon stocks stored in permafrost soils of Arctic tundra are
under risk of release to atmosphere under warming climate. Ice--wedge
polygons in the low--gradient polygonal tundra create a complex mosaic
of microtopographic features. The microtopography plays a critical
role in regulating the fine scale variability in thermal and
hydrological regimes in the polygonal tundra landscape underlain by
continuous permafrost. Modeling of thermal regimes of this sensitive
ecosystem is essential for understanding the landscape behaviour under
current as well as changing climate. We present here an end-to-end
effort for high resolution numerical modeling of thermal hydrology at
real--world field sites, utilizing the best available data to
characterize and parameterize the models. We develop approaches to
model the thermal hydrology of polygonal tundra and apply them at four
study sites at Barrow, Alaska spanning across low to
transitional to high-centered polygon, representing a broad polygonal tundra
landscape. A multi--phase subsurface thermal hydrology model
(PFLOTRAN) was developed and applied to study the thermal regimes at
four sites. Using high resolution LiDAR DEM, microtopographic features
of the landscape were characterized and represented in the high
resolution model mesh. Best available soil data from field
observations and literature was utilized to represent the complex
hetogeneous subsurface in the numerical model. Simulation results
demonstrate the ability of the developed modeling approach to model
the complex thermal regimes across the sites, and help explain the
role of microtopographic features in regulating the thermal dynamics
in permafrost soils. Analysis of the modeling results also highlights
the importance of field--based observations of soil
thermal and hydraulic properties and provides motivation for future
field--based observations by identifying gaps in our understanding of the
system.