Numerical Modeling, Simulation, and Parameter Estimation with Water Quality Data

Abstract

In some areas of Wisconsin, the lakes tend to get a lot of phosphorus runoff from farms resulting in severe algal blooms due to a cycle of burgeoning cyanobacterial populations during the summer months. We examined two mathematical models to help forecast bloom conditions and severity. In both models the dependent variable is chlorophyll concentration which acts as a proxy for the bacteria population. One model forecasts the time required for a bloom to occur and for the lake to turn green from excess biomass in the absence of further flushing. The other model describes the concentration’s dynamics spatially and temporally to discover the optimal conditions for an algae bloom. Both of these models can take proposed solutions and test them for feasibility and effectiveness before expensive policy plans are put into place.