Geophysical estimation of shallow permafrost distribution and properties in an ice-wedge polygon-dominated Arctic tundra region

Abstract

Shallow permafrost distribution and characteristics are important for predicting ecosystem feedbacks to a changing climate over decadal to century timescales because they can drive active layer deepening and land surface deformation, which in turn can significantly affect hydrologic and biogeochemical responses, including greenhouse gas dynamics. As part of the U.S. Department of Energy Next-Generation Ecosystem Experiments-Arctic, we have investigated shallow Arctic permafrost characteristics at a site in Barrow, Alaska, with the objective of improving our understanding of the spatial distribution of shallow permafrost, its associated properties, and its links with landscape microtopography. To meet this objective, we have acquired and integrated a variety of information, including electric resistance tomography data, frequency-domain electromagnetic induction data, laboratory core analysis, petrophysical studies, high-resolution digital surface models, and color mosaics inferred from kite-based landscape imaging. The results of our study provide a comprehensive and high-resolution examination of the distribution and nature of shallow permafrost in the Arctic tundra, including the estimation of ice content, porosity, and salinity. Among other results, porosity in the top 2 m varied between 85% (besides ice wedges) and 40%, and was negatively correlated with fluid salinity. Salinity directly influenced ice and unfrozen water content and indirectly influenced the soil organic matter content. A relatively continuous but depth-variable increase in salinity led to a partially unfrozen saline layer (cryopeg) located below the top of the permafrost. The cryopeg environment could lead to year-round microbial production of greenhouse gases. Results also indicated a covariability between topography and permafrost characteristics including icewedge and salinity distribution. In addition to providing insight about the Arctic ecosystem, through integration of lab-based petrophysical results with field data, this study also quantified the key controls on electric resistivity at this Arctic permafrost site, including salinity, porosity, water content, ice content, soil organic matter content, and lithologic properties.

Coincident aboveground and belowground autonomous monitoring to quantify covariability in permafrost, soil, and vegetation properties in Arctic tundra

“…In general, pure ice is formed during freezing and solutes are rejected into the unfrozen solute [e.g., Hivon and Sego , ; Marion , ]. A simple and commonly used conceptual model is that the increase in the in situ solute concentration is proportional to the decrease in the unfrozen water due to salt exclusion during ice formation [ Hivon and Sego , ; Minsley et al ., ; Dafflon et al ., ]. Minsley et al [] added an exponent to the saturation term to account for variable loss of solute from the pore space due to diffusion or other transport processes, so the equation is given by where C 0 is the initial solute concentration (referred as solute concentration in fluid extracted of a core sample after being thawed) and W 0 is the total water content.…”

“…Minsley et al [] added an exponent to the saturation term to account for variable loss of solute from the pore space due to diffusion or other transport processes, so the equation is given by where C 0 is the initial solute concentration (referred as solute concentration in fluid extracted of a core sample after being thawed) and W 0 is the total water content. Setting the exponent a equal to 1 assumes that increase in in situ solute concentration fully balances the decrease in the unfrozen water content W [ Dafflon et al ., ]. Setting a to 0.8 implies variable loss of solute from the pore space [ Minsley et al ., ], and setting it to 0 means no change in solute concentration in the remaining unfrozen water content during freezing.…”

“…In particular, the total water content and initial solute concentration were estimated using a linear relationship observed between total water content and initial solute concentration (extracted from collocated core samples), the relationships expressed in equations to , and by assuming the exponent a equal to 1. Dafflon et al [] also showed that due to uncertainty and simplification associated with the petrophysical relationships described above, uncertainty in the estimation of total water content, initial solute concentration, and in situ unfrozen water content were each on the order of 20–30%.…”

Mapping snow depth within a tundra ecosystem using multiscale observations and Bayesian methods

“…1). This study domain has been characterized intensively in the NGEE Arctic project, leading to various ecosystem and subsurface datasets, including snow depth measurements (Wainwright et al, 2015;Dafflon et al, 2016). Mean annual air temperature at the Barrow site is −11.3 • C and mean annual precipitation is 173 mm (Liljedahl et al, 2011).…”

Modeling the spatiotemporal variability in subsurface thermal regimes across a low-relief polygonal tundra landscape

“…While PFLOTRAN has the ability to capture and model such cryostructures (via heterogeneous subsurface structure and properties but not their formation and evolution), we lack any quantitative data to characterize them for representation in the model. Ongoing efforts under the NGEE Arctic project by Kneafsey and Ulrich (2016) and Dafflon et al (2016) using X-ray computed tomography (CT) scanner technology on ice cores from BEO can potentially provide detailed 3-D soil structure and density information and to help address this missing piece.…”