RCCZO -- GIS / Map Data, Regolith Survey, Geomorphology -- Predicting Soil Thickness -- Reynolds Creek Experimental Watershed -- (2014-2017)

Authors:

Nicholas R. Patton Kathleen A. Lohse Sarah E. Godsey Mark S. Seyfried Benjamin T. Crosby

Owners:

CZO Reynolds CZO National

Type:

Resource

Storage:

The size of this resource is 5 bytes

Created:

Feb 25, 2020 at 5:13 p.m.

Last updated:

Apr 24, 2020 at 5:25 p.m.

Citation:

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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.

Subject Keywords

Coverage

Spatial

Coordinate System/Geographic Projection:

WGS 84 EPSG:4326

Coordinate Units:

Decimal degrees

Longitude

-116.7443°

Latitude

43.2018°

Streets Terrain Satelite

Spatial Extent

Content

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Additional Metadata

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

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
Idaho State University

How to Cite

Patton, N. R., K. A. Lohse, S. E. Godsey, M. S. Seyfried, B. T. Crosby (2020). RCCZO -- GIS / Map Data, Regolith Survey, Geomorphology -- Predicting Soil Thickness -- Reynolds Creek Experimental Watershed -- (2014-2017), HydroShare, http://www.hydroshare.org/resource/940903bdae5f4a7eb21e37708f2e8eb5

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

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

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