Developing a Genetic Algorithm for Selecting Infrastructure Modifications that Optimize Hydrodynamic Flushing in Old Tampa Bay

Abstract

Impermeable infrastructure such as traffic causeways can reduce the natural hydrodynamic flushing of an estuary, resulting in reduced water quality and increased incidence of harmful algal blooms (HABs). A series of cuts through the three causeways spanning Old Tampa Bay, FL, (OTB) are being considered to help restore the natural circulation of the region, but the number of possible location combinations is computationally challenging to fully assess. A prototype genetic algorithm (GA) was developed to identify the optimal configuration of these cuts through one of the bridge sections that maximizes flushing as represented in a numerical ocean circulation model of OTB. Flushing was measured by integrating the trajectories of over 21,000 passive Lagrangian “particles” using the model velocity fields. The rate of loss of particles initialized near Feather Sound (a region subject to frequent HABs) was used to quantify the “fitness” over which the configurations were optimized. The highest-scoring solution produced a 42% increase in net flushing compared to a no-change baseline. Six independently initialized applications of the GA were conducted. All converged to the same solution within no more than 7 generations. The small population size of the prototype allowed testing of the complete solution space, and verification the found solution was optimal. Elitism (preservation of the highest-ranking solution) was required for convergence. The GA also identified configurations that had similar, but slightly slower, flushing rates. These results will help area managers prioritize or rank combinations of causeway modifications to improve overall water quality conditions in Tampa Bay.