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Predicting soil thickness on soil mantled hillslopes.


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.

SUBMITTER: Patton NR 

PROVIDER: S-EPMC6102209 | biostudies-literature | 2018 Aug

REPOSITORIES: biostudies-literature

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Predicting soil thickness on soil mantled hillslopes.

Patton Nicholas R NR   Lohse Kathleen A KA   Godsey Sarah E SE   Crosby Benjamin T BT   Seyfried Mark S MS  

Nature communications 20180820 1


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 (r<sup>2</sup> = 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 relationship  ...[more]

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