Estimation of nonlinear parameters of the type 5 Muskingum model using SOS algorithm

The Symbiotic Organisms Search Algorithm (SOS) is used as an algorithm based on the social behavior of Symbiotic Organisms in optimization of Non-linear 5 model parameters for flood routing. The data used in this article is 4 day observations from 30 November 2008 to 3 December 2008, which is located between the Molasani, and Ahwaz station on the Karun River. The time series data used included river inflow, storage volume, and river outflow. The results of the developed model with the Symbiotic Organisms Search Algorithm (SOS) were compared with the other Evolutionary algorithms including Genetic Algorithm (GA, and Harmony Search Algorithm (HS). The analysis showed that the best solutions achieved from the objective function by the SOS, GA, and HS algorithms were 143052.02, 143252.35, and 142952.45, respectively. The processes of these datasets determined that the SOS algorithm was premiere to GA, and HS algorithms on the optimal flood routing river problem. • In this article applied the Symbiotic Organisms Search Algorithm for Estimation of nonlinear parameters of the Muskingum hydrologic model of the Karun River located in Iran. • This method can be useful for managers of water, and wastewater companies, water resource facilities for predicting the flood process downstream of the rivers. • The present algorithm performs better than the other algorithms in the discussion of the optimization of Nonlinear 5 parameters of Muskingum model in flood routing.