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Hydrology 2017, 4(3), 44; doi:10.3390/hydrology4030044

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

1
Faculty of Engineering and Applied Science, Memorial University of Newfoundland, St. John’s, NL A1B 3X5, Canada
2
Department of Civil and Environmental Engineering, Carnegie Mellon University, Pittsburgh, PA 15213, USA
*
Author to whom correspondence should be addressed.
Received: 31 July 2017 / Revised: 12 September 2017 / Accepted: 13 September 2017 / Published: 15 September 2017
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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. View Full-Text
Keywords: Bayesian hierarchical regression; stream temperature variation; headwater; local-scale; microhabitat Bayesian hierarchical regression; stream temperature variation; headwater; local-scale; microhabitat
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Daraio, J.A.; Amponsah, A.O.; Sears, K.W. Bayesian Hierarchical Regression to Assess Variation of Stream Temperature with Atmospheric Temperature in a Small Watershed. Hydrology 2017, 4, 44.

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