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RCCZO -- Soil Survey -- Predicting Soil Thickness -- Reynolds Creek Experimental Watershed -- (2014-2016)

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Created: Nov 19, 2019 at 7:10 a.m.
Last updated: Apr 24, 2020 at 5:36 p.m.
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Soil thickness is a fundamental variable in many earth science disciplines but difficult to predict. We find a strong inverse linear relationship between soil depth and hillslope curvature (r2=0.89, RMSE=0.17 m) at a field site in Idaho. Similar relationships are present across a diverse data set, although the slopes and y-intercepts vary widely. We show that the slopes of these functions vary with the standard deviations (SD) in catchment curvatures and that the catchment curvature distributions are centered on zero. Our simple empirical model predicts the spatial distribution of soil depth in a variety of catchments based only on high-resolution elevation data and a few soil depths. Spatially continuous soil depth datasets enable improved models for soil carbon, hydrology, weathering and landscape evolution.

Subject Keywords



Coordinate System/Geographic Projection:
WGS 84 EPSG:4326
Coordinate Units:
Decimal degrees
Place/Area Name:
Reynolds Creek Experimental Watershed, Johnston Draw
North Latitude
East Longitude
South Latitude
West Longitude


Start Date:
End Date:


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Additional Metadata

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BSU ScholarWorks Link
Recommendation Citation Patton, Nicholas R.; Lohse, Kathleen A.; Godsey, Sarah E.; Seyfried, Mark S.; and Crosby, Benjamin T.. (2017). Dataset for Predicting Soil Thickness on Soil Mantled Hillslopes [Data set]. Retrieved from


Funding Agencies

This resource was created using funding from the following sources:
Agency Name Award Title Award Number
National Science Foundation Reynolds Creek Critical Zone Observatory EAR-1331872


People or Organizations that contributed technically, materially, financially, or provided general support for the creation of the resource's content but are not considered authors.

Name Organization Address Phone Author Identifiers
USDA-ARS Northwest Watershed Research Center Reynolds Creek Experimental Watershed Boise, ID
Idaho State University Pocatello, ID

How to Cite

Patton, N., K. Lohse, S. Godsey, M. Seyfried, B. Crosby (2020). RCCZO -- Soil Survey -- Predicting Soil Thickness -- Reynolds Creek Experimental Watershed -- (2014-2016), HydroShare,

This resource is shared under the Creative Commons Attribution CC BY.


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