Modeling macroalgae growth to optimize biomass.

The EFDC-MPI model was amended to include the growth kinetics of macroalgae (seaweed) in the water-quality and hydrodynamic calculations. While EFDC has historically simulated macroalgae grown only on the sediment bed, this restriction was lifted to facilitate simulation of kelp farms where the macroalgae substrate was specified at the depth in the water column yielding maximum growth due to optimum light intensity and temperature. The vegetative drag forces on the water column (along with commensurate changes to turbulence intensity and its length scale) were calculated using a new approach based on aquaculture studies and their effects on flow. The macroalgae metabolized nitrates (NO3) or ammonium (NH4) and phosphates (PO4) into dissolved organic nitrogen and phosphorus as well as both labile and refractory particulate organic nitrogen and phosphorus according to the CE-QUAL water-quality model built into EFDC. The ability to specify both nutrient concentrations and point-source masses was added to simulate “fertilization” (supplementation of nutrient-rich water at various locations in the kelp farm). Finally, data assimilation was included to nudge the open boundary conditions to ensure stability when all boundaries were specified-pressure time series, which allowed this model to be forced by a regional-scale EFDC or ROMS model. Developments integrated with a domain decomposition-based MPI parallelization for computational efficiency and results output in CF-compliant NetCDF. This model was developed to support uncertainty quantification and sensitivity analyses with the goal of maximizing biomass production by optimizing nutrient loading, depth in the water column (to control sunlight intensity and temperature), and location of fertilization points (to minimize “nutrient shadows” downstream in the kelp farm). Large (100-ha) kelp farms are under consideration by the Department of Energy as a source of biofuel (MARINER Program) and numerical modeling is required to ensure that these systems are developed in the most cost-effective manner.