Bayesian Hierarchical Regression to Assess Variation of Stream Temperature with Atmospheric Temperature in a Small Watershed

Abstract

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 ( β j ) for regressions varied significantly by season and showed the greatest variation in summer. The strongest relationships occurred in autumn with β = 0 . 743 ± 0 . 019 ( β = 0 . 712 ± 0 . 022 ), and the weakest relationships occurred in the summer with β = 0 . 254 ± 0 . 030 ( β = 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.

Keywords

• Bayesian hierarchical regression
• stream temperature variation
• headwater
• local-scale
• microhabitat