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


Authors:
Owners: This resource does not have an owner who is an active HydroShare user. Contact CUAHSI (help@cuahsi.org) to determine if accessing this resource is possible.
Resource type: Composite 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: See how to cite this resource
Sharing Status: Discoverable
Views: 694
Downloads: 0
+1 Votes: Be the first one to 
 this.
Comments: No comments (yet)

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

Deleting all keywords will set the resource sharing status to private.

Resource Level Coverage

Spatial

Coordinate System/Geographic Projection:
WGS 84 EPSG:4326
Coordinate Units:
Decimal degrees
Longitude
-116.7443°
Latitude
43.2018°

Content

  You do not have permission to see these content files. Please contact an Owner if you wish to obtain access.

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/
CC-BY

Comments

There are currently no comments

New Comment

required