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Data-driven methods for hydrologic inference and discovery

Water flows in the Earth system are complex and difficult to quantify. Using data without recourse to an underlying physical theory has been a hallmark of hydrologic science for many years. Currently the expanding ability to handle large data sets using new methods has led to the development and use of sophisticated data-driven models with the ability to integrate physical theory into model architectures. My dissertation relies on theory-informed data-driven models (DDMs) to answer questions in hydrology. I first explore how theory can be integrated with DDMs. I apply and compare various methods to build DDMs to regionalize measured streamflow information to ungaged catchments where measurements are not available. I expand the work to address questions in sociohydrolgyâan emerging sub-discipline within the hydrologic sciences that seeks to integrate the physical and social aspects of hydrologic systemsâand show how the amount of water used across the U.S. is related to both physical and social variables. Finally, I discuss how DDMs in general, and each of the problems that I address in my dissertation in particular, relate to various forms of logical inference and how the feedback between data analysis and established theory is connate to scientific progress.

Identiferoai:union.ndltd.org:VANDERBILT/oai:VANDERBILTETD:etd-03302018-124729
Date06 April 2018
CreatorsWorland, Scott Campbell
ContributorsGeorge M. Hornberger, Jonathan M. Gilligan, Robert M. Hirsch, Hiba Baroud, Ralf Bennartz
PublisherVANDERBILT
Source SetsVanderbilt University Theses
LanguageEnglish
Detected LanguageEnglish
Typetext
Formatapplication/pdf
Sourcehttp://etd.library.vanderbilt.edu/available/etd-03302018-124729/
Rightsunrestricted, I hereby certify that, if appropriate, I have obtained and attached hereto a written permission statement from the owner(s) of each third party copyrighted matter to be included in my thesis, dissertation, or project report, allowing distribution as specified below. I certify that the version I submitted is the same as that approved by my advisory committee. I hereby grant to Vanderbilt University or its agents the non-exclusive license to archive and make accessible, under the conditions specified below, my thesis, dissertation, or project report in whole or in part in all forms of media, now or hereafter known. I retain all other ownership rights to the copyright of the thesis, dissertation or project report. I also retain the right to use in future works (such as articles or books) all or part of this thesis, dissertation, or project report.

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