EFFECTS OF CURRENT AND HISTORIC FOREST PRACTICES ON STREAM TEMPERATURE

2013 ◽  
Author(s):  
B.D. Sugden ◽  
R.L. Steiner
Author(s):  
Daniel J. Isaak ◽  
Seth J. Wenger ◽  
Erin E. Peterson ◽  
Jay M. Ver Hoef ◽  
Steven W. Hostetler ◽  
...  
Keyword(s):  

2016 ◽  
Author(s):  
Carol Mankiewicz ◽  
◽  
Emma C. Koeppel ◽  
Rebecca L. Clow
Keyword(s):  

Water ◽  
2021 ◽  
Vol 13 (7) ◽  
pp. 990
Author(s):  
Tariq M. Munir ◽  
Cherie J. Westbrook

Beaver dam analogues (BDAs) are becoming an increasingly popular stream restoration technique. One ecological function BDAs might help restore is suitable habitat conditions for fish in streams where loss of beaver dams and channel incision has led to their decline. A critical physical characteristic for fish is stream temperature. We examined the thermal regime of a spring-fed Canadian Rocky Mountain stream in relation to different numbers of BDAs installed in series over three study periods (April–October; 2017–2019). While all BDA configurations significantly influenced stream and pond temperatures, single- and double-configuration BDAs incrementally increased stream temperatures. Single and double configuration BDAs warmed the downstream waters of mean maxima of 9.9, 9.3 °C by respective mean maxima of 0.9 and 1.0 °C. Higher pond and stream temperatures occurred when ponding and discharge decreased, and vice versa. In 2019, variation in stream temperature below double-configuration BDAs was lower than the single-configuration BDA. The triple-configuration BDA, in contrast, cooled the stream, although the mean maximum stream temperature was the highest below these structures. Ponding upstream of BDAs increased discharge and resulted in cooling of the stream. Rainfall events sharply and transiently reduced stream temperatures, leading to a three-way interaction between BDA configuration, rainfall and stream discharge as factors co-influencing the stream temperature regime. Our results have implications for optimal growth of regionally important and threatened bull and cutthroat trout fish species.


2021 ◽  
Vol 122 ◽  
pp. 107229
Author(s):  
Zachary C. Johnson ◽  
Brittany G. Johnson ◽  
Martin A. Briggs ◽  
Craig D. Snyder ◽  
Nathaniel P. Hitt ◽  
...  

2016 ◽  
Vol 9 (12) ◽  
pp. 4491-4519 ◽  
Author(s):  
Aurélien Gallice ◽  
Mathias Bavay ◽  
Tristan Brauchli ◽  
Francesco Comola ◽  
Michael Lehning ◽  
...  

Abstract. Climate change is expected to strongly impact the hydrological and thermal regimes of Alpine rivers within the coming decades. In this context, the development of hydrological models accounting for the specific dynamics of Alpine catchments appears as one of the promising approaches to reduce our uncertainty of future mountain hydrology. This paper describes the improvements brought to StreamFlow, an existing model for hydrological and stream temperature prediction built as an external extension to the physically based snow model Alpine3D. StreamFlow's source code has been entirely written anew, taking advantage of object-oriented programming to significantly improve its structure and ease the implementation of future developments. The source code is now publicly available online, along with a complete documentation. A special emphasis has been put on modularity during the re-implementation of StreamFlow, so that many model aspects can be represented using different alternatives. For example, several options are now available to model the advection of water within the stream. This allows for an easy and fast comparison between different approaches and helps in defining more reliable uncertainty estimates of the model forecasts. In particular, a case study in a Swiss Alpine catchment reveals that the stream temperature predictions are particularly sensitive to the approach used to model the temperature of subsurface flow, a fact which has been poorly reported in the literature to date. Based on the case study, StreamFlow is shown to reproduce hourly mean discharge with a Nash–Sutcliffe efficiency (NSE) of 0.82 and hourly mean temperature with a NSE of 0.78.


2016 ◽  
Vol 20 (8) ◽  
pp. 3411-3418 ◽  
Author(s):  
Masahiro Ryo ◽  
Marie Leys ◽  
Christopher T. Robinson

Abstract. Temperature models that directly predict ecologically important thermal attributes across spatiotemporal scales are still poorly developed. This study developed an analytical method based on Fourier analysis to estimate seasonal and diel periodicities, as well as irregularities in stream temperature, at data-poor sites. The method extrapolates thermal attributes from highly resolved temperature data at a reference site to the data-poor sites on the assumption of spatial autocorrelation. We first quantified the thermal attributes of a glacier-fed stream in the Swiss Alps using 2 years of hourly recorded temperature. Our approach decomposed stream temperature into its average temperature of 3.8 °C, a diel periodicity of 4.9 °C, seasonal periodicity spanning 7.5 °C, and the remaining irregularity (variance) with an average of 0.0 °C but spanning 9.7 °C. These attributes were used to estimate thermal characteristics at upstream sites where temperatures were measured monthly, and we found that a diel periodicity and the variance strongly contributed to the variability at the sites. We evaluated the performance of our predictive mechanism and found that our approach can reasonably estimate periodic components and extremes. We could also estimate the variability in irregularity, which cannot be represented by other techniques that assume a linear relationship in temperature variabilities between sites. The results confirm that spatially extrapolating thermal attributes based on Fourier analysis can predict thermal characteristics at a data-poor site. The R scripts used in this study are available in the Supplement.


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