Abstract

The Piedmont region of the southeastern United States experienced a period of accelerated erosion in the 1800s. Clear-cutting of the forests coupled with soil tilling and inadequate erosion control practices led to substantial soil redistribution and loss. This redistribution exposed the subsoil clay (argillic) horizon in many locations and altered hydrologic processes (i.e., infiltration or interflow) across the landscape. Describing the current hydrologic and biogeochemical processes in this landscape requires a spatially explicit mapping of soil re-distribution and the current depth to the argillic horizon. To achieve this mapping, we measured the depth to the argillic horizon in highly eroded (historically farmed) and undisturbed hillslopes (reference areas) by direct measures—soil augur and tile push probe—and by electromagnetic induction (EMI) combined with ancillary data (i.e., terrain features). Direct measures indicated that the depth to the argillic horizon in the historically farmed watersheds ranged from 26 ± 2 to 87 ± 12 cm in ridge-top and toe-slope, respectively, while in the reference hillslopes depths from ridge-top to toe-slope only ranged from 30 ± 3 to 48 ± 12 cm. Using remotely-sensed data, the best predictive models of the depth to the argillic horizon were based on measurements of the site topographic characteristics (percent slope and hillslope position), along with the following EMI data products: the 2 m horizontal coplanar (HCP) EMI measurement and some of its derivatives (i.e., 2 m HCP – 2 m perpendicular, 2 m HCP – 1 m HCP). Our data suggest that in this previously farmed and reforested landscape, geophysical sensing is an efficient means of predicting depth-to-clay when combined with landscape feature characteristics (R2 = 0.69).

Citation

Ryland, Rachel C., Aaron Thompson, Lori A.Sutter, Daniel Markewitz (2020): Mapping depth to the argillic horizon on historically farmed soil currently under forests. Geoderma 369, Article 114291. DOI: 10.1016/j.geoderma.2020.114291

This Paper/Book acknowledges NSF CZO grant support.