Topographic controls on soil moisture scaling properties in polygonal ground using idealized high-resolution surface–subsurface simulations

Abstract. Microtopographic features, such as polygonal ground, are characteristic sources of landscape heterogeneity in the Alaskan Arctic coastal plain. Here, we analyze the hypothesis that microtopography is a dominant controller of soil moisture in polygonal landscapes. We perform multi-year surface–subsurface isothermal flow simulations using the PFLOTRAN model for summer months at six spatial resolutions (0.25–8 m, in increments of a factor of 2). Simulations are performed for four study sites near Barrow, Alaska that are part of the NGEE-Arctic project. Results indicate a non-linear scaling relationship for statistical moments of soil moisture. Mean soil moisture for all study sites is accurately captured in coarser resolution simulations, but soil moisture variance is significantly under-estimated in coarser resolution simulations. The decrease in soil moisture variance in coarser resolution simulations is greater than the decrease in soil moisture variance obtained by coarsening out the fine resolution simulations. We also develop relationships to estimate the fine-resolution soil moisture probability distribution function (PDF) using coarse resolution simulations and topography. Although the estimated soil moisture PDF is underestimated during very wet conditions, the moments computed from the inferred soil moisture PDF had good agreement with the full model solutions (bias < ± 4 % and correlation > 0.99) for all four sites. Lastly, we develop two spatially-explicit methods to downscale coarse-resolution simulations of soil moisture. The first downscaling method requires simulation of soil moisture at fine and coarse resolution, while the second downscaling approach uses only topographical information at the two resolutions. Both downscaling approaches are able to accurately estimate fine-resolution soil moisture spatial patterns when compared to fine-resolution simulations (mean error for all study sites are < ± 1 %), but the first downscaling method more accurately estimates soil moisture variance.