Estimation of Nonlinear Parameters of Type 6 Hydrological Method in Flood Routing With the Spotted Hyena Optimizer Algorithm (SHO)

In this study, The Spotted hyena optimizer Algorithm (SHO) is used to optimize the parameters of the Non-linear type 6 Muskingum model for flood routing. To evaluate the performance of the SHO in the Non-linear Muskingum models, The Wilson River and the Wye River are applied by many researchers for validation. Moreover, in these studies, the Non-linear Muskingum parameters were estimated by the SHO Algorithm. The SSQ and DPO were considered as objective functions between computed and observed data. According to the results of Wilson river flood, the values of these objective functions for the NL3 model are 128.781, and 0.92 m 3 /s, and for the NL6 model, are 3.20 and 0.027, respectively. The results of the Wye River flood with the SHO showed that the SSQ and DPO for the NL3 model are 34789.39 and 90.05, and for the NL6 model are 30812.07 and 72.35, respectively. The results show that the proposed algorithm can be applied confidently to estimate the parameter optimal values of the nonlinear Muskingum model. Moreover, this algorithm may be applicable to any continuous engineering optimization problems.