A four parameter, logistic stream temperature model has been previously developed to
describe the S-shaped, weekly stream temperature/air temperature relationship (Mohseni et al.,
1998). The four model parameters, evaluated by nonlinear, least squares regression, have
specific physical interpretations. However, the least squares estimate of the model parameter
representing upper bound stream temperature has been found to have several deficiencies. The
deficiencies associated with the nonlinear, least squares fitting method with respect to the
estimate of upper bound stream temperature are frequent underestimation, highly variable
estimation with respect to record length and an insensitivity to the actual trends occurring at the
extreme upper end of the stream temperature/air tern perature relationship. Two alternate
statistical methods were therefore considered for the estimation of upper bound stream
temperature that focused exclusively on the uppennost stTeam temperatures: the standard
deviate method and the frequency distribution method.
Grazing Land Research Laboratory, US Department of Agriculture; Mid-Continent Ecology Division, US Environmental Protection Agency
Erickson, Troy R.; Mohseni, Omid; Stefan, Heinz G..
Estimation of an Upper Bound for Weekly Stream Temperatures.
St. Anthony Falls Laboratory.
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