Citation:

Fuller, M., N. Detenbeck, P. Leinenbach, R. Labiosa, AND D. Isaak. Spatial and temporal variability in stream thermal regime drivers for three river networks during the summer growing season. JOURNAL OF THE AMERICAN WATER RESOURCES ASSOCIATION. American Water Resources Association, Middleburg, VA, , 1-22, (2023). https://doi.org/10.1111/1752-1688.13158

Impact/Purpose:

Stream temperatures are driven by both natural processes (e.g., weather) and anthropogenic impacts (e.g., land-use change/alteration). This research addresses the need to better understand patterns of stream temperatures across river networks and how natural and anthropogenic controls balance with each other. To do this, we developed a model selection process that uses statistical spatial stream network models in which various land-use, climate, and water management processes compete and/or combine with each other to predict stream temperature patterns. We tested this model selection process across three study basins of the Pacific Northwest, USA during three months of the growing season (May [start], August [warmest], and September [last]). The results from this work provide insight into how restoration of streams (including the landscapes they intersect) could be managed to maintain and restore cold-water habitat for cold-water species (e.g., Pacific salmon).

Description:

Many cold water-dependent aquatic organisms are experiencing habitat and population declines from increasing water temperatures. Identifying mechanisms which drive local and regional stream thermal regimes facilitates restoration at ecologically relevant scales. Stream temperatures vary spatially and temporally both within and among river basins. We developed a modeling process to identify statistical relationships between drivers of stream temperature and covariates representing landscape, climate, and management-related processes. The modeling process was tested in three study areas of the Pacific Northwest United States during the growing season (May [start], August [warmest], September [end]). Across all months and study systems, covariates with the highest relative importance represented the physical landscape (elevation [1st], catchment area [3rd], main channel slope [5th]) and climate covariates (mean monthly air temperature [2nd] and discharge [4th]). Two management covariates (groundwater use [6th] and riparian shade [7th]) also had high relative importance. Across the growing season (for all basins), local reach slope had high relative importance in May, but transitioned to a regional main channel slope covariate in August and September. This modeling process identified regionally similar and locally unique relationships among drivers of stream temperature. High relative importance of management-related covariates suggested potential restoration actions for each system.

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