A predictive model for time domain reflectometry soil water content and salinity measurements Public Deposited

http://ir.library.oregonstate.edu/concern/graduate_thesis_or_dissertations/dj52w853g

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  • Soil water content and water potential are two important parameters in determining the status of water in the soil. Improvement in the ability to measure these parameters by way of increased speed, accuracy, resolution, imaging volume, ease of automation, as well as reduced calibration requirements and reduced soil disturbance would be of utility to many applications in agriculture and engineering. To make the measurements economically and without the use of hazardous materials or methods would also be of value. A brief review is given on most of the existing water content and water potential measurement techniques with focus given on electromagnetic and quantum mechanic techniques due to their potential for best balancing the design goals. A review of the theories of electromagnetics and quantum mechanics are presented with applications to soil water content and water potential measurements. One electromagnetic method, Time Domain Reflectometry, or TDR, shows great promise in balancing all the desired design goals. A mathematical model is proposed to be able to predict TDR water content and electrical conductivity (or salinity) measurement results over wide ranges of those parameters. Preliminary validations were performed on the model for both invasive and potentially non-invasive TDR probes in a sandy soil with the results showing good agreement between predictions and actual results but with some model refinements still needed. A proposal for ongoing research is given to refine the models and address the question on the feasibility of using the models in a field grade TDR instrument to measure water content and electrical conductivity (or salinity).
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  • File scanned at 300 ppi (Monochrome, 8-bit Grayscale, 24-bit Color) using ScandAll PRO 1.8.1 on a Fi-6670 in PDF format. CVista PdfCompressor 4.0 was used for pdf compression and textual OCR.
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  • description.provenance : Submitted by Sergio Trujillo (jstscanner@gmail.com) on 2012-11-02T22:07:29Z No. of bitstreams: 1 FlugstadBenjaminA1996.pdf: 6152401 bytes, checksum: ada93df28d737b947e275752ca1021c2 (MD5)
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  • description.provenance : Approved for entry into archive by Patricia Black(patricia.black@oregonstate.edu) on 2012-11-02T22:12:28Z (GMT) No. of bitstreams: 1 FlugstadBenjaminA1996.pdf: 6152401 bytes, checksum: ada93df28d737b947e275752ca1021c2 (MD5)

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