Predicting soil thickness on soil mantled hillslopes

Nicholas R. Patton, Kathleen A. Lohse (), Sarah E. Godsey, Benjamin T. Crosby and Mark S. Seyfried
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Nicholas R. Patton: Idaho State University
Kathleen A. Lohse: Idaho State University
Sarah E. Godsey: Idaho State University
Benjamin T. Crosby: Idaho State University
Mark S. Seyfried: Northwest Watershed Research Center

Nature Communications, 2018, vol. 9, issue 1, 1-10

Abstract: Abstract Soil thickness is a fundamental variable in many earth science disciplines due to its critical role in many hydrological and ecological processes, but it is difficult to predict. Here we show a strong linear relationship (r2 = 0.87, RMSE = 0.19 m) between soil thickness and hillslope curvature across both convergent and divergent parts of the landscape at a field site in Idaho. We find similar linear relationships across diverse landscapes (n = 6) with the slopes of these relationships varying as a function of the standard deviation in catchment curvatures. This soil thickness-curvature approach is significantly more efficient and just as accurate as kriging-based methods, but requires only high-resolution elevation data and as few as one soil profile. Efficiently attained, spatially continuous soil thickness datasets enable improved models for soil carbon, hydrology, weathering, and landscape evolution.

Date: 2018
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DOI: 10.1038/s41467-018-05743-y

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