Scales of Connectivity within Stream Temperature Networks of the Clackamas River Basin, Oregon
Bibliographic Data
| ID | 3775281 |
|---|---|
| Authors | Michael Krochta (0009-0008-9098-0423, Portland State University, corresponding author), Heejun Chang (0000-0002-5605-6500, Portland State University) |
| Year | 2024 |
| Volume | 114 |
| Issue | 8 |
| Pages | 1653-1667 |
| Publication date | 2024-09-13 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Annals of the American Association of Geographers (JOURNAL) |
| Journal identifiers | ISSN: 2469-4452 • E-ISSN: 2469-4460 |
| Publisher | Informa UK Limited (PUBLISHER • GB) |
| DOI | 10.1080/24694452.2023.2289981 |
| OpenAlex | W4391025220 |
| Language | EN |
| References cited | 49 |
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. Key Words: scale, spatial stream network, stream temperature, water quality
Cartography · Drainage basin · Elevation (ballistics · Geography · Habitat · Hydrology (agriculture · Physical geography · Riparian zone · Scale (ratio · Spatial ecology · Spatial variability · Statistics · STREAMS · Upstream (networking · Upstream and downstream (DNA · Watershed · Environmental Science · Fish Ecology and Management Studies · Hydrology and Sediment Transport Processes · Hydrology and Watershed Management Studies · Mathematics · Ecology · Geology
| Citation velocity | historical |
|---|---|
| Highly cited | No |