Sharif University of TechnologySharif Journal of Civil Engineering2676-476837.22.120210823Parameter Estimation of the Nonlinear Muskingum Flood-Routing Model Using The new dragonfly algorithmParameter Estimation of the Nonlinear Muskingum Flood-Routing Model Using The new dragonfly algorithm3102217210.24200/j30.2020.55391.2726FAS. KhalifehDept. of Water Science and Engineering Ferdowsi University of Mashhad0000-0002-6472-6471S.R. KhodashenasDept. of Water Science and Engineering Ferdowsi University of Mashhad0000000332479653K. EsmailiDept. of Water Science and Engineering Ferdowsi University of Mashhad0000000153540949Journal Article20200127Flood routing is one of the most complex problems investigated in hydrologic engineering and it can help design engineers to recognize the impacts of riverine projects. Among the different flood routing methods, the Muskingum model as the best hydrologic method of flood routing is widely used with high accuracy in river flood studies. In this paper, DragonFly Algorithm (DA) was used to this end. The results of the DragonFly Algorithm (DA) were compared with GA and HS algorithms. The results showed that DragonFly algorithm (DA (was capable to provide satisfactory estimates of nonlinear Muskingum parameters. The results showed that the DragonFly Algorithm (DA) could provide an appropriate estimation of the optimal values of nonlinear Muskingum model parameters so that for the Sum Squares Deviations (SSQ) and RMSE, the values for rainfed algorithm were 4/5551 and 0/711, respectively, for the DragonFly Algorithm (DA). The DragonFly Algorithm (DA) can be used for any continuous engineering problem.Flood routing is one of the most complex problems investigated in hydrologic engineering and it can help design engineers to recognize the impacts of riverine projects. Among the different flood routing methods, the Muskingum model as the best hydrologic method of flood routing is widely used with high accuracy in river flood studies. In this paper, DragonFly Algorithm (DA) was used to this end. The results of the DragonFly Algorithm (DA) were compared with GA and HS algorithms. The results showed that DragonFly algorithm (DA (was capable to provide satisfactory estimates of nonlinear Muskingum parameters. The results showed that the DragonFly Algorithm (DA) could provide an appropriate estimation of the optimal values of nonlinear Muskingum model parameters so that for the Sum Squares Deviations (SSQ) and RMSE, the values for rainfed algorithm were 4/5551 and 0/711, respectively, for the DragonFly Algorithm (DA). The DragonFly Algorithm (DA) can be used for any continuous engineering problem.https://sjce.journals.sharif.edu/article_22172_2a990501cfca44b803dc2d5c24421f7a.pdf