Development of precipitation δ18O isoscapes for Canada and application within a tracer-aided hydrological model

dc.contributor.authorDelavau, Carly J.
dc.contributor.examiningcommitteeRasmussen, Peter (Civil Engineering) Buhay, Bill (Geological Sciences) Birks, Jean S. (Guest Member, InnoTech Alberta) James, April (Geography, Nipissing University)en_US
dc.contributor.supervisorStadnyk,Tricia (Civil Engineering)en_US
dc.date.accessioned2016-12-06T21:35:34Z
dc.date.available2016-12-06T21:35:34Z
dc.date.issued2015en_US
dc.date.issued2011en_US
dc.degree.disciplineCivil Engineeringen_US
dc.degree.levelDoctor of Philosophy (Ph.D.)en_US
dc.description.abstractDelineating spatial patterns of precipitation isotopes (“isoscapes”) is important for studies including the hydrology of terrestrial systems, present and past interpretations of climate, and tracer-aided hydrological modelling, among others. However, the extent to which precipitation isoscapes can be predicted across Canada has not been fully articulated. This thesis combines isotopes in precipitation (δ18Oppt) observations from two regional and one global network to create long term and time series precipitation isoscapes for Canada and the northern United States. Multi-linear regressions of a small suite of geographic and climate variables generate the best performing long-term and seasonal models of δ18Oppt. These models are used to develop long term isoscapes for Canada, which capture the general spatial and seasonal trends in δ18Oppt, showing an improvement upon results from previous studies using global models. Building upon long-term δ18Oppt prediction, δ18Oppt observations alongside climatological and geographic predictors are used to create empirical time series prediction models. Five regionalization approaches are used to separate the study domain into isotope zones to explore the effect of spatial grouping on simulations. Generally, the models capture the timing and magnitude of intra-annual (seasonal) δ18Oppt cycles across the study domain while simulating moderate inter-annual variation; however often fail to capture the anomalies in observed δ18Oppt. Uncertainty in predictions is quantified spatially and temporally, and the Köppen-Geiger (Kpn) regionalization is selected as the preferred regionalization scheme for future applications due to adequate model performance and lack of border issues at regional boundaries. Finally, estimates of monthly δ18Oppt from Kpn models, long term annual averages, and daily REMOiso output are used to force an isotope-enabled hydrological model, isoWATFLOOD, in the Fort Simpson Basin, NWT, Canada. Results show streamflow simulations are not significantly impacted by choice of δ18Oppt input; however, oxygen-18 in streamflow and the internal apportionment of water (and model parameterizations) are impacted, particularly during large precipitation and snowmelt events. This work shows how isoWATFLOOD can be used in regions with limited δ18Oppt observations, and that the model can be of value in such regions. This study reinforces that a tracer-aided modelling approach works towards diagnosing issues surrounding model equifinality.en_US
dc.description.noteFebruary 2017en_US
dc.identifier.citationDelavau, C., Chun, S., Stadnyk, T., Birks, S.J., Welker, J. (2015). North American precipitation isotope (delta O-18) zones revealed in time series modeling across Canada and northern United States. Water Resources Research. 51(2): 1284 – 1299. DOI: 10.1002/2014WR015687.en_US
dc.identifier.citationDelavau, C., Stadnyk, T.A., Birks, S. J. (2011). Model based distribution of oxygen-18 isotopes in precipitation across Canada. Canadian Water Resources Journal 36(4): 313-330. DOI: 10.4296/cwrj3604875.en_US
dc.identifier.urihttp://hdl.handle.net/1993/31946
dc.language.isoengen_US
dc.publisherTaylor and Francis, American Geophysical Unionen_US
dc.rightsopen accessen_US
dc.subjectStable water isotopes, Precipitation isoscapes, Isotope hydrology, Hydrological modelling, Uncertaintyen_US
dc.titleDevelopment of precipitation δ18O isoscapes for Canada and application within a tracer-aided hydrological modelen_US
dc.typedoctoral thesisen_US
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