Automatic Calibration of SWAT model Using Particle Swarm Optimization and Ant Colony Optimization Algorithm.

In this research, the Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO) algorithms are applied to investigate the automatic calibration of the Soil and Water Assessment Tool (SWAT). The calibrated SWAT model simulated well the daily stream flow of the watershed outlet for a 4-year calibration period and 1 year validation period. PSO and ACO algorithms are two evolutionary heuristics techniques based on population search methods. In other words, PSO and the ACO move from a set of points (population) to another set of points in a single iteration with likely improvement using a combination of deterministic and probabilistic rules. The computational efforts of these two optimization methods are compared with genetic algorithm (GA) technique.