Advisor

Scott Wells

Date of Award

1-1-2011

Document Type

Thesis

Degree Name

Master of Science (M.S.) in Civil & Environmental Engineering

Department

Civil and Environmental Engineering

Physical Description

1 online resource (v, 50 p.) : col. ill., col. maps

Subjects

Dynamical Downscaling, Extreme Precipitation, NARCCAP, Climatic changes -- Environmental aspects -- Oregon -- Willamette River Watershed, Precipitation variability -- Oregon -- Willamette River Watershed, Weather -- Environmental aspects -- Oregon -- Willamette River Watershed, Willamette River Watershed (Or.) -- Climate -- Mathematical models

DOI

10.15760/etd.327

Abstract

One important aspect related to the management of water resources under future climate variation is the occurrence of extreme precipitation events. In order to prepare for extreme events, namely floods and droughts, it is important to understand how future climate variability will influence the occurrence of such events. Recent advancements in regional climate modeling efforts provide additional resources for investigating the occurrence of extreme events at scales that are appropriate for regional hydrologic modeling. This study utilizes data from three Regional Climate Models (RCMs), each driven by the same General Circulation Model (GCM) as well as a reanalysis dataset, all of which was made available by the North American Regional Climate Change Assessment Program (NARCCAP). A comparison between observed historical precipitation events and NARCCAP modeled historical conditions over Oregon's Willamette River basin was performed. This comparison is required in order to investigate the reliability of regional climate modeling efforts. Datasets representing future climate signal scenarios, also provided by NARCCAP, were then compared to historical data to provide an estimate of the variability in extreme event occurrence and severity within the basin. Analysis determining magnitudes of two, five, ten and twenty-five year return level estimates, as well as parameters corresponding to a representative Generalized Extreme Value (GEV) distribution, were determined. The results demonstrate the importance of the applied initial/boundary driving conditions, the need for multi-model ensemble analysis due to RCM variability, and the need for further downscaling and bias correction methods to RCM datasets when investigating watershed scale phenomena.

Description

Portland State University. Dept. of Civil & Environmental Engineering

Persistent Identifier

http://archives.pdx.edu/ds/psu/7084

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