Bayesian Hierarchical Regression To Assess Variation Of Stream Temperature With Atmospheric Temperature In A Small Watershed

This paper described the variability of stream temperature, T-s, and compared relationships between T-s and air temperature, T-a, at 10 sites along a 1.2 km reach in a 2 km(2) basin in New Jersey, USA, using Bayesian Hierarchical Regression. Mean daily mean T-s was significantly cooler at two sites and significantly warmer at three sites relative to the mean daily T-s for all sites combined. Seasonal daily mean T-s showed the greatest variation between sites in the summer within the reach for both daily mean and daily maximum temperatures. Posterior distributions for slope parameters (beta(j)) for regressions varied significantly by season and showed the greatest variation in summer. The strongest relationships occurred in autumn with beta = 0.743 +/- 0.019 (beta = 0.712 +/- 0.022), and the weakest relationships occurred in the summer with beta = 0.254 +/- 0.030 (beta = 0.193 +/- 0.039). Results support the conclusion that riparian shading impacts the effect of T-a on T-s, and that T-s shows a stronger relationship with measured T-a at sites in open areas that are more likely to have meteorologic conditions similar to bulk conditions.