Application of Ant Algorithm in Calibration of Rainfall-Runoff Model

The successful application of a conceptual rainfall-runoff (CRR) model depends on how it is calibrated. The CRR models generally represent the soil moisture accounting phase of the hydrologic cycle as several interconnected subsystems, each representing a certain component in the processing of the hydrologic event. Despite the popularity of CRR models, reports in the literature indicate that difficulties in calibrating the parameters. Ant Colony Optimization (ACO) is one of the recent optimization methods which is inspired by the fact that ants are able to find the shortest route between their nest and a food source. This is accomplished by using pheromone trails as a form of indirect communication. In this paper, calibration of a rainfall-runoff model is presented by using Ant Colony Optimization (ACO) method. The results are compared with the conventional calibration methods.