Estimating Hourly Water Temperatures in Rivers Using Modified Sine and Sinusoidal Wave Functions
Publication: Journal of Hydrologic Engineering
Volume 21, Issue 10
Abstract
Air temperature is often used to estimate stream water temperature by developing regression models. A method using modified sine functions and sinusoidal wave functions (MSSWF) was proposed for estimating hourly water temperatures in rivers. Estimates of daily maximum and minimum water temperatures from sine functions (SFs) were corrected using linear regressions as functions of deviations of estimates of daily maximum and minimum air temperatures from SFs, and then modified sinusoidal wave functions (SWFs) were used to estimate hourly water temperatures. Excellent agreement was found between observed and estimated hourly water temperatures using MSSWF models developed for 13 rivers in Alabama. The average Nash-Sutcliffe efficiency (NSE) for the MSSWF models developed for individual rivers is 0.94. The distance of a river monitoring station from the weather station has very little effect on the performance of individual MSSWF models when the distance is less than approximately 300 km. A lumped MSSWF model was also developed by combining water temperature data from all 13 rivers. The average NSE of 0.87 from the lumped MSSWF model indicates that the model can be applied to other rivers in Alabama that lack water temperature observations. The procedure to develop a MSSWF model was applied to four rivers in other regions.
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Acknowledgments
The author, Gang Chen, wishes to express his gratitude to the Chinese Scholarship Council for financial support pursuing his graduate study at Auburn University. The authors would like to also thank Michael A. Perez, at Auburn University, and two anonymous reviewers for their review comments on this paper.
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© 2016 American Society of Civil Engineers.
History
Received: May 8, 2015
Accepted: Mar 30, 2016
Published online: Jun 14, 2016
Published in print: Oct 1, 2016
Discussion open until: Nov 14, 2016
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