Notes: An Empirical Method for the Prediction of Daily Water Temperatures in the Littoral Zone of Temperate Lakes

Abstract

We used daily air and water temperatures from 14 lakes in Ontario to develop and test a simple method for constructing lake-specific empirical models for predicting daily littoral water temperatures. Data requirements for prediction are modest (average air temperature, day of the year) and the method is robust and practical, requiring only a few (15)(16)(17)(18)(19)(20) well-spaced water temperature observations to construct a single-year model that can generate reasonably accurate predictions for an entire ice-free season. The ability of a singe-lake model to predict several years of temperature data is significantly improved by explicitly including information on ice-out date in the model. Our multiyear model for Lake Opeongo described most (18 of 22) years well. Years that were not well described were usually coincident with El Nifio Southern Oscillation events. Used with caution, the method can be an effective tool for supplementing direct monitoring of littoral water temperatures and for generating historical water temperature estimates when direct estimates are lacking. These capabilities should be of particular use to fisheries biologists studying or managing populations of fish species with critical life stages that are affected by littoral water temperatures.

Littoral water temperature response to experimental shoreline logging around small boreal forest lakes

“…In lakes, water temperature is influenced by a complex and interacting suite of factors, including air temperature, altitude, direct and indirect solar energy, wind, fetch, water clarity, and depth, with different factors dominating at different locations and different spatial or temporal scales (Mazumder and Taylor 1994;Fee et al 1996). The relevant physical processes are well understood (Edinger et al 1968), and good empirical models (based mainly on air temperature and lake morphometry) are available for predictions of whole-lake and littoral water temperatures (Shuter et al 1983;Matuszek and Shuter 1996;Håkanson 1996). However, little is known about lake temperature response to forest disturbance.…”

A Model to Approximate Lake Temperature from Gridded Daily Air Temperature Records and Its Application in Risk Assessment for the Establishment of Fish Diseases in the UK

“…It is well documented that air temperature is a reliable predictor of lake surface water temperature, and models of varying complexity have been published (Matuszek and Shuter, 1996; Honzo and Stefan, 1993; Robertson and Ragotzkie, 1990; McCombie, 1959; Livingstone and Padisák, 2007). Sharma et al.…”

“…A linear regression model based on the method described by Matuszek and Shuter (1996) was developed to approximate daily average still-water surface temperatures using average air temperatures of preceding days combined with a time function:…”

“…It is well documented that air temperature is a reliable predictor of lake surface water temperature, and models of varying complexity have been published (Matuszek and Shuter, 1996;Honzo and Stefan, 1993;Robertson and McCombie, 1959;Livingstone and Padisák, 2007). Sharma et al (2008) reported that multiple regression provided the best approach to modelling lake water temperatures, based on model performance and computational complexity, in a comparison of techniques including regression tree, artificial neural network and Bayesian methodology.…”

Large‐scale coherence in the response of lake surface‐water temperatures to synoptic‐scale climate forcing during summer

“…Recent analyses of LSWT have shown that in the long term (from year to year), it can respond coherently to climatic forcing on scales of several hundred kilometers (e.g., Benson et al 2000;Straile and Adrian 2000;Livingstone and Dokulil 2001). In the short term (from day to day), Matuszek and Shuter (1996) showed that water temperatures in the littoral zone of lakes in Ontario can be modeled empirically on the basis of air temperatures measured as far as 300 km away, which they attributed to the lack of physical relief in the region. In mountainous regions, a coherent response of day-to-day variations in LSWT to meteorological forcing on smaller spatial scales has been demonstrated, specifically for the lakes of the Swiss Plateau (Livingstone and Lotter 1998) and the Swiss Alps (Livingstone et al 1999(Livingstone et al , 2005a.…”