JSM 2004 - Toronto

Abstract #300853

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Activity Number: 231
Type: Contributed
Date/Time: Tuesday, August 10, 2004 : 10:30 AM to 12:20 PM
Sponsor: Section on Statistics and the Environment
Abstract - #300853
Title: Empirical Modeling of Limnetic Temperature Profile and Estimating Thermocline Depth
Author(s): Victor Chan*+
Companies: Western Washington University
Address: Dept. of Mathematics, Bellingham, WA, 98225,
Keywords: nonlinear regression ; confidence intervals ; correlated errors
Abstract:

A reasonably precise estimate of the thermocline depth or other well-defined boundaries in the temperature profile of a lake is of interest to limnologists. I propose an empirical model based on a statistical distribution to describe the temperature profile. Using the model, the thermocline depth and other well-defined boundaries could easily be estimated. The nonlinear Gauss-Newton method is used to fit the model to the profile data. Examples and the model-fitting procedure are illustrated using the data from Lake Whatcom, WA. I will also present a method to construct an approximate confidence interval for the thermocline depth based on the estimated asymptotic covariance matrix for the OLS estimators.

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Revised March 2004