OPTIMIZATION METHOD USING GENETIC ALGORITHMS AND PARTICLE SWARM OPTIMIZATION FOR PARAMETER ESTIMATION OF DISTRIBUTED RAINFALL-RUNOFF AND QUASI-2D FLOOD FLOWS MODEL

Abstract

 The parameter optimization method based on observed water level for distributed rainfall-runoff and quasi-2D flood flows simulation models were examined. The Genetic Algorithms(GA) and Particle Swarm Optimization(PSO) were used for the optimization method. The rainfall runoffs were simulated by a distributed hydrological model using a high-resolution scheme. The flood flows in the main river and a tributary were simulated simultaneously by the quasi-2D unsteady free-surface flow model. The flooding event in the Hikosan river basin in July 2012 were simulated by the model. The simulated results were compared with the observed water level. It shows that the proposed optimization method was a useful tool for parameter estimation.