STRATIFICATION VARIABILITY IN THREE MORPHOMETRICALLY DIFFERENT LAKES UNDER IDENTICAL METEOROLOGICAL FORCING¹

Abstract

Synoptic water temperature measurements were taken in three temperate lakes located within 25 km of one another to study the effects of morphometry (and changes in weather) on seasonal and short‐term thermal stratification characteristics. Two of the lakes had nearly the same surface areas and two had nearly identical mean depths; all were exposed to identical weather conditions. The dominance of weather over morphometry on the water surface temperature response was illustrated by the synoptic measurements in two different years. Stratification structure was also found to be dominated by weather for sufficiently deep lakes. Surface area effects were most subtle but explainable as sheltering effects. The onset of stratification was not, as traditionally described, a simple, gradual response of a lake to the annual solar radiation cycle. Rather it depends on a series of alternating heating, cooling, and mixing cycles similar to annual and diel cycles but with a period of approximately five days. These were in direct response to the passage of major weather systems and displayed no apparent time lag. No comparable synoptic water temperature data set could be found in the literature.

Simulated long term temperature and dissolved oxygen characteristics of lakes in the north‐central United States and associated fish habitat limits

“…This model has been successfully applied to simulate hydrothermal processes and water quality in lakes for a variety of meteorological conditions (e.g. Ford and Stefan 1980a;Riley and Stefan 1987;Hondzo and Stefan 199 1, 1993a). The water-quality model was verified for 16 lakes of different morphometries and trophic levels, and with different meteorological conditions (Hondzo and Stefan 19933;Stefan et al 1993;Fang 1993, 1994).…”

“…The rest of the lakes are expected to be dimictic. Solar radiation and wind also play an important role in lake stratification but are less variable from lake to lake in a given region than is lake morphometry (Ford and Stefan 1980a). Secchi depth was chosen as a lake trophic state indicator (Heiskary and Wilson 1988) because it is a commonly available parameter and can be related to direct indicators of primary productivity through Carlson's trophic state index (Carlson 1977) (Fig.…”

Convective motions in the sidearm of a small reservoir

“…rapid horizontal flows and repeated formation and destruction of diurnal mixed layers, which took place between 22 and 28 February, the one-dimensional temperature structure measured on 28 February was very similar to that measured at the start of the trip. It seems likely that a onedimensional mixed-layer model (Ford and Stefan 1980;Patterson et al 1984;Spigel et al 1986) could be used to model evolution of the thermal stratification with acceptable accuracy. By neglecting horizontal processes such as the thermally driven exchange of waters between a sidearm and the main ba-…”

“…During the day, a layer several degrees warmer than the wakers below and a few meters deep forms through the combined actions of surface heating and wind mixing; at night, this layer deepens considerably and cools convectively in association with surface heat losses . Weekly variations in surface fluxes associated with the movements of synoptic weather systems introduce corresponding variations in the depth and heat content of the surface mixed layer, such that the daily repetition of this cycle results in the formation of a complex, layered stratification called the metalimnion Ford and Stefan 1980). Periods of strong winds can disrupt this pattern and, in some cases, completely eliminate all vertical stratification (Mortimer 19 5 3).…”

“…Periods of strong winds can disrupt this pattern and, in some cases, completely eliminate all vertical stratification (Mortimer 19 5 3). Both the diurnal and seasonal cycles of stratification can be predicted with reasonable accuracy (Ford and Stefan 1980;Spigel et al 1986) because they are largely the result of one-dimensional processes (Patterson et al 1984) and only require first-order models of two-dimensional processes such as wind-forced currents (Spigel and Imberger 1980), or inflows and outflows (Hurley Octavia et al 1977). The comparison of predicted and measured temperature distributions, however, is somewhat forgiving: if the simulated surface mixed layer is warmer and shallower than the observed layer, it will lose more heat and deepen further at night.…”