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 ( 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

Implications of Climatic Variations in Temporal Precipitation Patterns for the Development of Design Storms in Newfoundland and Labrador

The distribution of precipitation in time is an important aspect for the development of design storms for storm water infrastructure design. The current set of mass curves used throughout the province of Newfoundland and Labrador (NL) may not be justified. In order to identify variation in mass curves across NL, and compare results with existing mass curves, hourly precipitation data from 10 stations were used. Bayesian k-means clustering was used to identify dimensionless mass curves to represent precipitation patterns. Eight distinct temporal patterns of precipitation were identified and further regrouped into four, useful for making recommendations on the choice of mass curve. Crosstabulation applied to the patterns were found to be significantly influenced by event duration, depth and climate zone. Results support the conclusion that climate was an important determinant of temporal distribution of precipitation, and it is important to determine which pattern is dominant in a given region.The accepted manuscript in pdf format is listed with the files at the bottom of this page. The presentation of the authors' names and (or) special characters in the title of the manuscript may differ slightly between what is listed on this page and what is listed in the pdf file of the accepted manuscript; that in the pdf file of the accepted manuscript is what was submitted by the author