A linked hydrodynamic, water quality and algal biomass model for a large, multi-basin lake: A working management tool

This paper describes a simple modelling framework to predict water quality and algal biomass in large, complex lakes with insufficient and often multifarious data and challenging logistics. We applied a linked model design to Lake of the Woods (LOW) as a case study, using output from hydrodynamic, mass balance and empirical models to predict spatial differences in nutrients (total phosphorus (TP)), and algal and cyanobacterial standing stock (chlorophyll-a (chla), biovolume-derived biomass and cyanobacterial dominance). Our models reproduced observed temporal and spatial distribution of TP and chla well. The central and south segments behaved like shallow lakes with strong variability in TP and phytoplankton biomass, whereas two relatively isolated and deeper segments in the north were characterized with less variability in TP and lower phytoplankton biomass. Algal biomass and cyanobacterial dominance were best predicted in the more eutrophic southern sectors; however the fit was strongly dependent on the source of biomass data. The results reinforce the need to apply a multi segmental model to these systems which cannot be effectively modelled using a single box approach because of spatial differences in hydrodynamics and topography.