Impacts of microtopographic snow redistribution and lateral subsurface processes on hydrologic and thermal states in an Arctic polygonal ground ecosystem: a case study using ELM-3D v1.0

Abstract

Abstract. Microtopographic features, such as polygonal ground, are characteristic sources of landscape heterogeneity in the Alaskan Arctic coastal plain. Here, we analyze the effects of snow redistribution (SR) and lateral subsurface processes on hydrologic and thermal states at a polygonal tundra site near Barrow, Alaska. We extended the land model integrated in the E3SM to redistribute incoming snow by accounting for microtopography and incorporated subsurface lateral transport of water and energy (ELM-3D v1.0). Multiple 10-year-long simulations were performed for a transect across a polygonal tundra landscape at the Barrow Environmental Observatory in Alaska to isolate the impact of SR and subsurface process representation. When SR was included, model predictions better agreed (higher R 2 , lower bias and RMSE) with observed differences in snow depth between polygonal rims and centers. The model was also able to accurately reproduce observed soil temperature vertical profiles in the polygon rims and centers (overall bias, RMSE, and R 2 of 0.59 • C, 1.82 • C, and 0.99, respectively). The spatial heterogeneity of snow depth during the winter due to SR generated surface soil temperature heterogeneity that propagated in depth and time and led to ∼ 10 cm shallower and ∼ 5 cm deeper maximum annual thaw depths under the polygon rims and centers, respectively. Additionally, SR led to spatial heterogeneity in surface energy fluxes and soil moisture during the summer. Excluding lateral subsurface hydrologic and thermal processes led to small effects on mean states but an overestimation of spatial variability in soil moisture and soil temperature as subsurface liquid pressure and thermal gradients were artificially prevented from spatially dissipating over time. The effect of lateral subsurface processes on maximum thaw depths was modest, with mean absolute differences of ∼ 3 cm. Our integration of three-dimensional subsurface hydrologic and thermal subsurface dynamics in the E3SM land model will facilitate a wide range of analyses heretofore impossible in an ESM context.

Mechanistic Modeling of Microtopographic Impacts on CO2 and CH4 Fluxes in an Alaskan Tundra Ecosystem Using the CLM‐Microbe Model

“…The variations in our estimates for seven landscape types were potentially biased because they ignored the lateral surface hydrologic and thermal processes. The spatial variability in soil moisture and soil temperature can be overpredicted if the lateral subsurface hydrologic and thermal processes are excluded (Bisht et al, ), and the same is true for the spatial variability in CH 4 emissions in Arctic polygonal landscapes. By incorporating these surface processes, the CH 4 models can improve the representation of lateral hydrologic and thermal transport, and thereby improve the accuracy of estimations (Aas et al, ).…”

Pathways of ice-wedge degradation in polygonal tundra under different hydrological conditions

“…1a and c). The polygonal tundra on Samoylov Island has been previously investigated in a number of studies, with a particular focus on measuring its water and energy balances (Boike et al, 2008;Langer et al, 2011a, b;Helbig et al, 2013). Moisture levels on the island are spatially variable with a high abundance of polygonal ponds and a few larger water bodies in its central part and dryer, welldrained areas towards the margins of the island (Muster et al, 2012).…”

“…We used an instantaneous infiltration scheme which assumes rapid vertical water flow compared to the rates of other processes represented in the model. This is a valid assumption for the upper soil layers of tundra wetlands, which are typically characterized by large hydraulic conductivities (Boike et al, 2008) and in which infiltration into the active layer is mainly controlled by thaw depth (Zhang et al, 2010).…”

Development and Verification of a Numerical Library for Solving Global Terrestrial Multiphysics Problems

“…A major weakness of current generation LSMs is the numerical techniques used to obtain solution of the linear and nonlinear system of equations (SoE) that result from spatial and temporal discretization of one‐dimensional biophysical processes (Clark & Kavetski, ). For example, the numerical algorithm that solves for canopy and soil skin temperatures in the nonlinear canopy radiative model of the Community Land Model (CLM; Oleson et al, ) and the E3SM Land Model (ELM; Bisht et al, ; Riley et al, ; Tang & Riley, ) accepts the last solution iteration when maximum allowable iteration count is reached even though the change in iterate value remains larger than the tolerance value (Oleson et al, ). Analysis by Kavetski and Clark () using eight time stepping schemes for six hydrologic models in 13 basins showed that unreliable time stepping schemes, irrespective of model structure, lead to serious numerical artifacts.…”

“…Furthermore, current generation LSMs have been desgined to only simulate one‐dimensional processes while several recent studies have demonstrated the need to explicitly account for lateral subsurface processes. Bisht et al () showed that inability of ELM to include lateral redistribution of water and energy in the subsurface leads to an overestimation of spatial variability of soil moisture and soil temperature in Arctic polygonal ground ecosystem. Chang et al () demonstrated that incorporation of lateral water flow and water vapor diffusion within the soils in a watershed scale model leads to an improved prediction of the transpiration to evapotranspiration ratio.…”