First Advisor

Heejun Chang

Date of Publication

Summer 1-1-2012

Document Type


Degree Name

Master of Science (M.S.) in Geography






Johnson Creek Watershed (Clackamas County and Multnomah County (Or.)), Watersheds -- Oregon -- Fanno Creek (Multnomah County and Washington County), Watershed hydrology -- Oregon -- Portland Metropolitan Area, Stream measurements -- Oregon -- Portland Metropolitan Area



Physical Description

1 online resource (v, 49 p.) : ill., col. maps


This study investigates the hydrologic effects of urbanization in two Portland, Oregon streams through a comparison of three hydrologic metrics. Hydrologic metrics used in this study are the mean annual runoff ratio (Qa), mean seasonal runoff ratio (Qw and Qd), and the fraction of time that streamflow exceeds the mean streamflow during the year (TQmean). Additionally, the relative change in streamflow in response to storm events was examined for two watersheds. For this investigation urban development is represented by two urbanization metrics: percent impervious and road density. Descriptive and inferential statistics were used to evaluate the relationship between the hydrologic metrics and the amount of urban development in each watershed. The effect of watershed size was also investigated using nested watersheds, with watershed size ranging from 6 km2 to 138km 2. The results indicate that annual and seasonal runoff ratios have difficulty capturing the dynamic hydrologic behavior in urban watersheds. TQmean was useful at capturing the flashy behavior of the Upper Fanno watershed, however it did not perform as well in Kelley watershed possibly due to the influence of impermeable soils and steep slopes. Unexpected values for hydrologic metrics in Lower Johnson, Sycamore and Kelley watersheds could be the result water collection systems that appear to route surface water outside of their watersheds as well as permeable soils. Storm event analysis was effective at characterizing the behavior for the selected watersheds, indicating that shorter time scales may best capture the dynamic behavior of urban watersheds.


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