Date of Award
May 2018
Degree Type
Thesis
Degree Name
Master of Science (MS)
Department
Earth Sciences
Advisor(s)
Laura K. Lautz
Subject Categories
Physical Sciences and Mathematics
Abstract
The thesis presented herein is a compilation of two different research projects I have been fortunate enough to work on during my graduate career at Syracuse University. The first and most complete project is a data analysis study using linear discriminant analysis to differentiate between sources of groundwater salinity in water samples from shallow groundwater wells. It is a model validation study that builds on previous work spearheaded by the Earth Sciences Department at Syracuse University. It represents some of my best work performed at Syracuse and should be considered the bulk of my thesis submission. Due to successful publication of that research early into my graduate career I had the opportunity to work on another project. The Technical Supplement is a review of the work I have done in collaboration with The Nature Conservancy. The main project goal was to study the hydrologic effects that beaver dam analogues may have on an incised stream system and to understand the utility of drone-derived imagery for hydrologic modeling. During my time working on this project, a lot was learned about best practices and avenues of future research. To make sure that this knowledge is not lost, it is recorded here.
Access
Open Access
Recommended Citation
Chien, Nathaniel, "Discriminant analysis as a decision-making tool for geochemically fingerprinting
sources of groundwater salinity and other work" (2018). Theses - ALL. 203.
https://surface.syr.edu/thesis/203
