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  5. On Interpreting Eddy Covariance In Small Area Agricultural Situations With Contrasting Site Management.
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On Interpreting Eddy Covariance In Small Area Agricultural Situations With Contrasting Site Management.

Date Issued
December 1, 2022
Author(s)
Oetting, Joel
Advisor(s)
Neal Eash
Additional Advisor(s)
Bruce Hicks, James Zahn, John Goddard, Dayton Lambert, Tom Sauer
Permanent URI
https://trace.tennessee.edu/handle/20.500.14382/28811
Abstract

This dissertation examined the carbon sequestration potential of a low C:N soil amendment and its incorporation into the soil over a rolling agricultural field. A segmented planar fit was developed to assess and correct the systematic errors the topography introduces on the carbon dioxide fluxes. The carbon dioxide fluxes were then be partitioned into gross primary productivity and soil respiration to understand the influence of the contrasting management practices, using flux variance partitioning. Concomitant with the partitioning, high resolution temporal and spatial scale remote sensing images were interpolated and standardized to conduct hypothesis testing for treatment effects.

Subjects

eddy covariance

deep learning

flux partitioning

no-till agriculture

flux upscaling

Disciplines
Environmental Monitoring
Other Environmental Sciences
Degree
Doctor of Philosophy
Major
Environmental and Soil Sciences
File(s)
Thumbnail Image
Name

Oetting_Dissertation___Final.docx

Size

11.5 MB

Format

Microsoft Word XML

Checksum (MD5)

d4f875c50331cb6bcf460a1054cadfd7

Thumbnail Image
Name

auto_convert.pdf

Size

5.03 MB

Format

Adobe PDF

Checksum (MD5)

7f60cf15a3a492f1be7ae9297378380d

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