Relation Between Stream Temperature and Landscape Characteristics Using Distance Weighted Metrics

Stream ecosystems have experienced significant negative impacts from land use, resource exploitation, and urban development. Statistical models allow researchers to explore the relations between these landscape variables and stream conditions. Weighting the relevant landscape variables based on hydrologically defined distances offers a potential method of increasing the predictive capacity of statistical models. Using observations from three grouped watersheds in the Portland-Vancouver Metro Area (n = 66), we explored the use of three different weighting schemes against the standard method of weighted areal average. These four different model groups were applied to four stream temperature metrics: mean seven-day moving average maximum daily temperature (Mean7dTmax), number of days exceeding 17.8 °C (Tmax7d >17.8), mean daily range in stream temperature (Mean_DTR), and the coefficient of variation in maximum daily temperature (CV_Tmax) for each month in the 2011 dry season. The results demonstrate mixed effectiveness of the weighting schemes, dependent on both the stream temperature metric being predicted as well as the time scale under investigation. Models for Mean7dTmax showed no benefit from the inclusion of distance weighted metrics, while models for Mean_DTR consistently improved using distance weighted explanatory variables. Trends in the models for Tmax7d > 17.8 and CV_Tmax varied based on temporal scale. Additionally, all model groups demonstrated greater explanatory power in early summer months than in late summer months.