Articles | Volume 3, issue 1
https://doi.org/10.5194/soil-3-67-2017
https://doi.org/10.5194/soil-3-67-2017
Original research article
 | 
30 Mar 2017
Original research article |  | 30 Mar 2017

A probabilistic approach to quantifying soil physical properties via time-integrated energy and mass input

Christopher Shepard, Marcel G. Schaap, Jon D. Pelletier, and Craig Rasmussen

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Interactive discussion

Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision
ED: Reconsider after major revisions (18 Jan 2017) by Peter Finke
AR by Christopher Shepard on behalf of the Authors (16 Feb 2017)  Author's response   Manuscript 
ED: Publish as is (24 Feb 2017) by Peter Finke
ED: Publish as is (05 Mar 2017) by Kristof Van Oost (Executive editor)
AR by Christopher Shepard on behalf of the Authors (08 Mar 2017)
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Short summary
Here we demonstrate the use of a probabilistic approach for quantifying soil physical properties and variability using time and environmental input. We applied this approach to a synthesis of soil chronosequences, i.e., soils that change with time. The model effectively predicted clay content across the soil chronosequences and for soils in complex terrain using soil depth as a proxy for hill slope. This model represents the first attempt to model soils from a probabilistic viewpoint.