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

Joseph Daraio,Abena Amponsah,Kenneth Sears

doi:10.3390/hydrology4030044

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.

Highlights

Stream temperature (Ts ) is an important water quality parameter that has direct effects on a wide range of important processes in rivers
The Bayesian hierarchical analysis as applied to the Chestnut Branch watershed provides a straightforward method for identifying local scale variability in the relationship between stream temperature and air temperature
This approach can be applied at relatively small scales to identify areas where different local scale processes may be contributing to the response of stream temperature to different drivers in daily to seasonal time frames

Summary

Introduction

Stream temperature (Ts ) is an important water quality parameter that has direct effects on a wide range of important processes in rivers. It plays a significant role in freshwater ecosystems through direct and indirect impacts on aquatic organisms [1,2,3]. Stream temperature directly affects the timing of fish spawning [4], controls freshwater mussel life cycles [5], and high Ts can have lethal affects on most organisms. Ts has been rising along with global air temperatures throughout most of the world [9,10], and will likely have a significant impact on many fish species, such as salmonids and trout, that are sensitive to high Ts as well as other aquatic organisms [11]. Daraio et al [13]

Methods

Results

Discussion

Conclusion