Using Predictive Lake Modeling to Assess the Development of Cyanobacteria Blooms


Richard Kiesling
Hydrologist, U.S. Geological Survey

October 28, 2016


The U.S Geological Survey (USGS), in partnership with the Minnesota Department of Natural Resources (MDNR), the St. Croix Watershed Research Station, and the National Park Service (NPS), has developed a number of mechanistic, bio-physical lake models that simulate trophic dynamics and track changes in algal populations, including dominance by Cyanobacteria. For a variety of Minnesota Sentinel Lakes, models were used to evaluate changes in biomass of major algal groups under changing nutrient loading and meteorological stressor gradients. Model simulations successfully tracked the seasonal dominance of cyanophytes as well as the development of lake-specific algal biomass distributions. In Lake St. Croix, a multi-basin, riverine glacial scour lake, a calibrated model was able to simulate the spatial and temporal development of a Cyanobacteria bloom. The calibrated model was used to evaluate how the biomass distribution of major algal groups changed under different scenarios of nutrient and organic matter loading. Lake St. Croix model scenarios revealed how specific parameters were driving algal bloom dynamics. Model simulations provided an understanding of how cyanobacterial production and biomass accumulation in Lake St. Croix result from complex interactions between algal physiology, lake stratification, and hypoxia in deep pools of the lake.  In all of the lakes modeled to date, dissolved oxygen distributions reflect the interactions between lake stratification, primary production in the upper mixed layer of the lake, and water column oxygen demand below the photic zone. Dynamic, mechanistic models provide the necessary tool to simultaneously evaluate the influence of multiple stressors on complex lake ecosystems.