Estimating Hourly Water Temperatures in Rivers Using Modified Sine and Sinusoidal Wave Functions

Abstract

AbstractAir 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 MSS...