Title: Some like it hot: Stratification, circulation and turbulence in a shallow, tropical reservoir
by Prof. Stephen Monismith
For the most part, the study of lakes and reservoirs has focused on systems found at temperate latitudes. These are systems that generally have seasonal cycles of temperature stratification and thus exhibit motions and patterns of mixing that are best described as perturbations of the seasonal structure. In contrast, tropical lakes, especially ones that are shallow have received little attention despite their importance to water supplies throughout Asia as well as being important ecosystems in their own right. In my talk I will discuss field work and computations that we1 have carried out over the last decade in Kranji Reservoir (Singapore) studying the fundamental hydrodynamics of the reservoir. This includes studies of the basic circulation dynamics of the reservoir including motions generated by wind stresses, inflows, and by nighttime cooling. A key feature of the lake is that there is nearly as much variation in temperature in one week as there is in one year. As a consequence, there are no discernable seasonal variations in stratification, and thus diurnal stratification variations play a central role in the hydrodynamics of the lake. For example, wind stresses force complex baroclinic motions that are not seiching because internal seiche periods are generally longer than the time over which stratification develops due to heating and then decays due to surface cooling. Inflow events, which are short-lived, usually lasting a few hours, and intense, bring relatively large volumes of colder water into the reservoir, creating the most stable and long-lived stratification. Because winds are generally relatively weak on the lake, flows driven by cooling of shallow regions are an important mechanism for transporting materials from the shallow areas away from the dam, towards the deeper waters near the dam.
The talk will focus on synthesizing work done collaboratively with the School of Civil and Environmental Engineering at the Nanyang Technological University (NTU), Singapore, and in particular the Ph.D. theses of Dr. Zing Zikun and Dr. Yang Peipei, work that involved significant contributions from Prof. Edmond Lo of NTU and Dr. Derek Fong from Stanford.
Because the practical motivation for our work was concern over nutrient-driven eutrophication, particularly involving the cyanobacteria Microcystis aeruginosa , much of our effort has focused on quantifying rates of vertical turbulent mixing using temperature microstructure profiling. While the near-surface structure of turbulent mixing (turbulent kinetic energy, dissipation rates, etc.) is well described by the existing concepts of surface mixed layer dynamics, more complicated and variable rates of mixing are observed below the mixed layer depending on the nature of the flows generated by cooling and by inflows. Nonetheless, consistent with observed stratification variations, vertical mixing is sufficiently rapid to ensure nearly complete vertical mixing throughout the water column every day, suggesting that given a very shallow photic zone, positively buoyant phytoplankton like Microcystis may be able to effectively compete with negatively buoyant ones like most diatoms. Overall, flows and the temperature structure in the reservoir appear to be quite three dimensional, suggesting that modeling transport processes in the lake require a 3D model. I will show limited results from the application of the model ELCOM, developed by Prof. Jörg Imberger and his group in Western Australia. While the 3D model captures much of the general features of flows in Kranji, there are also significant differences between model and observations, something that may be at least partly an effect of the spatially limited meteorological data we used to force the model. Finally, given the importance of inflows in shaping reservoir thermal structure and to the influx of nutrients, the fact that (so far) predicting inflow temperature is not yet possible means that our ability to predict in particular how the lake will respond to climate change is somewhat limited.
This work was supported by the Singapore Stanford Partnership, a collaboration between Nanyang Technological University and Stanford University.