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Advancing Flood Flow Prediction Models for Ungauged Basins

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dc.contributor.advisor Gharabaghi, Bahram Walton, Rachel 2018-08-09T16:40:13Z 2018-08-09T16:40:13Z 2018-06 2018-06-12 2018-08-09
dc.description.abstract Predicting peak flows at ungauged basins has been a notable focus in water resources research, however the majority of methods are only appropriate for a small area, cannot be translated to other jurisdictions, or require variables that are difficult to measure or obtain. Through the analysis of over 7000 stream gauges from the USA, this work presents a simple, unified equation to predict return period peak flows, incorporating influential and easy to obtain input variables. Two novel variables are introduced: the Land Use Soil (LUS) factor and the 2 – year return precipitation effect (PE2). The equation achieved an R2 of 0.95, 0.83 and 0.86 on the training, testing and southern Ontario data sets, respectively, demonstrating high predictive capabilities. This research presents a logical method for predicting return period peak flows while advancing insight on the implications of land use, soil and precipitation on the magnitude of peak flows. en_US
dc.language.iso en en_US
dc.title Advancing Flood Flow Prediction Models for Ungauged Basins en_US
dc.type Thesis en_US Engineering en_US Master of Applied Science en_US School of Engineering en_US
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