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dc.contributor.advisorLowry, Christopher
dc.contributor.authorCramer, Jennifer
dc.contributor.author0000-0002-5899-8809
dc.date.accessioned2018-10-26T02:56:10Z
dc.date.available2018-10-26T02:56:10Z
dc.date.issued2018
dc.date.submitted2018-08-09 13:44:57
dc.identifier.urihttp://hdl.handle.net/10477/78592
dc.descriptionM.S.
dc.description.abstractLarge-scale particle image velocimetry (LSPIV) is a relatively new method developed for the remote measurement of surface water velocity from video. The technique uses pattern tracking software that performs cross-correlation analysis on video image-pairs to measure the displacement of pixels over time. Research using this technique has quickly moved from mapping surface velocity patterns to gauging stream discharge; yet, even with promising results, the method has not progressed beyond this application. The research presented here is a proof-of-concept to further advance this technology to quantify groundwater-surface water interaction through differential stream gauging. This study employed the use of commercially available imaging technology, smartphone, GoPro, and drones, to film multiple cross-sections along two streams in western-NY. Accurate discharge results (<10%) from LSPIV analysis were obtained for streams exhibiting homogenous steady flow, uniform bathymetry, and well-defined banks, where particle tracer density is distributed, and glare minimal. Additionally, the error was consistently negative relative to the true value. Drones yield the most accurate and precise discharge results as compared to ground-based systems; however, ground-based LSPIV has the potential to yield highly accurate results under ideal stream conditions. LSPIV was able to correctly measure a groundwater gain over an 8 to 10 km reach scale of Elton Creek in Delevan, NY. Error was established according to different conditions of data collection, giving a range of values between which the true discharge could fall. If the error is smaller than the absolute value of differential discharge, then it can be determined whether that stream reach is gaining or losing. The longer the stretch of stream, or reach scale, the larger the magnitude of groundwater contribution, and thus the more quantitative this method becomes.
dc.formatapplication/pdf
dc.language.isoen
dc.publisherState University of New York at Buffalo
dc.relation.haspartSupplementary file: Cramer_Cross-section-Scaling-Example.xlsx (spreadsheet); This is an example of how velocity data from RIVeR is combined with cross-section length and bathymetry data derived from ADV.
dc.rightsUsers of works found in University at Buffalo Institutional Repository (UBIR) are responsible for identifying and contacting the copyright owner for permission to reuse. University at Buffalo Libraries do not manage rights for copyright-protected works and cannot assist with permissions.
dc.subjectHydrologic sciences
dc.subjectRemote sensing
dc.subjectGeology
dc.titleA low-altitude remote sensing approach to monitoring groundwater-surface water interaction using large-scale particle image velocimetry
dc.typeThesis
dc.typeText
dc.rights.holderCopyright retained by author.
dc.contributor.departmentGeology


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