Search

Climate change in the Pacific Northwest of America is likely to bring more frequent, heavier winter precipitation as temperature rises. These changes in precipitation patterns have significant implications in hydrology and socioeconomic sectors that could be affected by changes in hydrology. Transportation infrastructure and travel patterns are also vulnerable to potential changes in runoff regimes and stream geomorphology. The 2006 and 2007 winter storms resulted in massive flooding, causing several major road failures in Oregon. While the probability of these extreme events is projected to rise under the global warming scenarios, there is no study investigating this issue in Oregon.The objectives of the project are threefold. First, we investigate the changes in the frequency and magnitude of winter runoff under climate change scenarios. Second, we determine the probability of road closure for representative road bridges under climate change scenarios. Third, we quantify these changes on transportation chokepoints related to flooding.We examined two representative urban streams in the Portland Metro area. Johnson Creek and Fanno Creek were chosen because both creeks have historical flow data and exhibit high flooding potential; each also has high road density with high traffic volume. The hydrological processes of the two watersheds, however, are different (Fanno – highly urbanized and steep slope; Johnson Creek – mixed land use with gentle slope); thus, each serves as a good model for other urban watersheds in Oregon. We used the following methodology to conduct our analysis. 1) Hydro-climate modeling: We applied statistically downscaled climate change scenarios for our study sites to predict the anticipated changes in winter precipitation amount and intensity. The US Geological Survey PRMS hydrologic model, together with a statistical model, were used to estimate runoff changes and resultant changes in flood frequency. 2) Stream geomorphology survey and hydraulic analysis: We surveyed channel profiles, patterns, and dimensions at the multiple cross sections of our study sites. The surveyed data were used to calibrate US Army Corp of Engineers‘ HAC-RAS for hydraulic analysis to project future water levels and identify vulnerable bridges and roads under different discharge scenarios. 3) Traffic analysis: We used Metro‘s travel forecast model to determine the potential impacts of road failure and congestion resulting from flooding. The model served as a reasonable and accurate assessment of the outcomes due to traffic disruption.Our results show that there is a nonlinear relation between precipitation change and urban flooding and that impacts on travel disruption are subject to local hydroclimate and watershed land use conditions. This study is one of few interdisciplinary attempts to assess potential impacts of climate change on the transportation sector. Such integrated knowledge and spatially-explicit modeling is essential for establishing proactive flood and transportation management planning and policies under increasing climate uncertainty.

Water quality varies along the stream network; thus, considering the directional, dendritic nature of stream networks with surrounding landscape variables is essential in explaining spatial variations of water quality. Using a spatially extensive stream temperature monitoring effort in the Clackamas River Basin in the United States, we first compare spatial scales of analysis of atmospheric, landscape, and in-stream explanatory variables through their correlation with summer stream temperatures. We then derive a predictive stream temperature model with factors representing the spatial variation of local climate, recent wildfire effects, and discharge. Finally, we compare nonspatial multiple linear regression to a spatial stream network (SSN) model to assess the combined importance of the spatial scale of analysis and flow-connected stream distance in explaining total variation in stream temperatures. Most explanatory variables show the most highly significant relationships to stream temperature when derived as a percentage of the total upstream area above observation sites. Elevation and vegetation cover, however, were most significantly correlated to stream temperature at the riparian buffer area scale and the local reach contributing area scale, respectively. Multiple regression analysis using total upstream burned area, total upstream area with underlying High Cascades geology, and the elevation within the 100-m-wide riparian area explained 81 percent of variation in stream temperature. SSN outperformed this nonspatial statistical model, however, in explaining the total variation in stream temperature. These comparisons of scaled data sets demonstrate both the local and cumulative upstream effects on stream temperature, providing a spatial network-informed framework to those prioritizing watershed restoration and wildfire recovery activities. [ABSTRACT FROM AUTHOR]