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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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Abstract

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.

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Coverage

Spatial

Coordinate System/Geographic Projection:

WGS 84 EPSG:4326

Coordinate Units:

Decimal degrees

Place/Area Name:

Reynolds Creek Experimental Watershed, Johnston Draw

North Latitude

43.1335°

East Longitude

-116.7753°

South Latitude

43.1201°

West Longitude

-116.8027°

Temporal

Start Date:
End Date:

Content

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Additional Metadata

Name	Value
DOI	https://doi.org/10.18122/B2PM69
BSU ScholarWorks Link	https://scholarworks.boisestate.edu/reynoldscreek/3/
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 https://doi.org/10.18122/B2PM69

Credits

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

Contributors

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, http://www.hydroshare.org/resource/6d3e785feb364ae79f88fa57432a7e92

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

http://creativecommons.org/licenses/by/4.0/

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