Dataset Listing

Calhoun CZO - Soil Texture - Argillic Horizon (2016-2017)

Variables:  Slope(%), Aspect(degree), Tile Push Probe Depth(cm), Depth to Bt, Landscape Position, Clay(%), Sand(%), Silt(%), EMI

Date Range:  (2016-01-30 to 2017-03-15)

Dataset Creators/Authors:  Ryland, Rachel C.

Contact:  Rachel Ryland, Department of Crop & Soil Sciences, University of Georgia, Athens, GA, rryland@uga.edu

Field Area:   Calhoun CZO Research Area 2 | Calhoun CZO Research Area 3 | Calhoun CZO Research Area 4

Description
Keywords & XML
Citation
  • Description

    Historic agricultural practices throughout the Piedmont region of the southeastern United States from ~1820 to 1940 led to accelerated erosion. Practices, such as tilling, degraded soil quality altering hydrologic processes on the landscape by limiting infiltration and leading to overland flow and erosion. Erosion due to these practices has substantially redistributed sediment from upper to lower landscape positions, causing a change in the depth-to-argillic horizon along hillslopes. By mapping the depth to argillic horizon within watersheds that have a history of farming and watersheds with little evidence of agricultural disturbance, a better understanding of the effects of farming practices on erosion and sediment redistribution can be made. This study uses extensive soil sampling within historically farmed and unfarmed watersheds to map spatial variations in the depth to argillic horizon. In addition to sampling, Electro-magnetic Induction (EMI) is being tested and calibrated to clay content and other topographic characteristic (i.e. landscape position, aspect, percent slope) from which the depth to argillic horizon can be predicted. Current hillslope and watershed hydrologic models use characteristics from soil classification maps for parameterization, however, these soil maps may lack sufficient spatial detail and may not accurately represent landscapes that have been eroded from historical farming. The results from this study will improve understanding of previous erosion on sediment redistribution and will characterize the potential use of electromagnetic induction as an accurate and efficient means to predict the depth to the argillic horizon. This information will improve parameterization of hillslope and watershed hydrologic models.
  • Keywords

    Argyllic, Clay, Depth, Soil Texture, Slope, Aspect, Landscape Position, EMI

    XML Metadata

    criticalzone.org/national/data/xml-metadata-test/5982/

    XML is in ISO-19115 geographic metadata format, compatible with ESRI Geoportal Server.

  • Citation for This Dataset

    Ryland, R.C., 2017, Calhoun CZO argyllic data, http://criticalzone.org/calhoun/data/dataset/5982

    Citation for This Webpage

    Ryland, Rachel C. (2017). "CZO Dataset: Calhoun CZO - Soil Texture (2016-2017) - Argillic Horizon." Retrieved 19 Feb 2019, from http://criticalzone.org/national/data/dataset/5982/

Data

Calhoun CZO - Argillic Data

(xlsx)   Data Level 1,  Metadata

Data Use Policy
Data Sharing Policy
  • Data Use Policy

    DRAFT v.0.4.0

    1. Use our data freely. All CZO Data Products* except those labelled Private** are released to the public and may be freely copied, distributed, edited, remixed, and built upon under the condition that you give acknowledgement as described below. Non-CZO data products — like those produced by USGS or NOAA — have their own use policies, which should be followed.

    2. Give proper citation and acknowledgement. Publications, models and data products that make use of these datasets must include proper citation and acknowledgement. Most importantly, provide a citation in a similar way as a journal article (i.e. author, title, year of publication, name of CZO “publisher”, edition or version, and URL or DOI access information. See http://www.datacite.org/whycitedata). Also include at least a brief acknowledgement such as: “Data were provided by the NSF-supported Southern Sierra Critical Zone Observatory” (replace with the appropriate observatory name).

    3. Let us know how you will use the data. The dataset creators would appreciate hearing of any plans to use the dataset. Consider consultation or collaboration with dataset creators.

    *CZO Data Products.  Defined as a data collected with any monetary or logistical support from a CZO.

    **Private. Most private data will be released to the public within 1-2 years, with some exceptionally challenging datasets up to 4 years. To inquire about potential earlier use, please contact us.

  • Data Sharing Policy

    DRAFT v.0.2.5

    All CZO investigators and collaborators who receive material or logistical support from a CZO agree to:

    1. Share data privately within 1 year. CZO investigators and collaborators agree to provide CZO Data Products* — including data files and metadata for raw, quality controlled and/or derived data — to CZO data managers within one year of collection of samples, in situ or experimental data. By default, data values will be held in a Private CZO Repository**, but metadata will be made public and will provide full attribution to the Dataset Creators†.

    2. Release data to public within 2 years. CZO Dataset Creators will be encouraged after one year to release data for public access. Dataset Creators may chose to publish or release data sooner.

    3. Request, in writing, data privacy up to 4 years. CZO PIs will review short written applications to extend data privacy beyond 2 years and up to 4 years from time of collection. Extensions beyond 3 years should not be the norm, and will be granted only for compelling cases.

    4. Consult with creators of private CZO datasets prior to use. In order to enable the collaborative vision of the CZO program, data in private CZO repositories will be available to other investigators and collaborators within that CZO. Releasing or publishing any derivative of such private data without explicit consent from the dataset creators will be considered a serious scientific ethics violation.

    * CZO Data Products. Defined as data collected with any monetary or logistical support from a CZO. Logistical support includes the use of any CZO sensors, sampling infrastructure, equipment, vehicles, or labor from a supported investigator, student or staff person. CZO Data Products can acknowledge multiple additional sources of support.

    ** Private CZO Repository. Defined as a password-protected directory on each CZO’s data server. Files will be accessible by all investigators and collaborators within the given CZO and logins will be maintained by that local CZO’s data managers. Although data values will not be accessible by the public or ingested into any central data system (i.e. CUAHSI HIS), metadata will be fully discoverable by the public. This provides the dual benefit of giving attribution and credit to dataset creators and the CZO in general, while maintaining protection of intellectual property while publications are pending.

    † Dataset Creators. Defined as the people who are responsible for designing, collecting, analyzing and providing quality assurance for a dataset. The creators of a dataset are analogous to the authors of a publication, and datasets should be cited in an analogous manner following the emerging international guidelines described at http://www.datacite.org/whycitedata.