Assessment of Modified Honey Bee Mating Optimization for Parameter Estimation of Nonlinear Muskingum Models

Because the nonlinear Muskingum model continues to be popular, the need for precise calibration of the model parameters provides an active area of research in hydrologic engineering. Although various techniques have been proposed to estimate the three parameters in the nonlinear Muskingum model, a more accurate method with the fast convergence rate is still required to improve the computational precision. In this research, the modified honey bee mating optimization (MHBMO) algorithm with the modified routing procedure is used for the estimation of Muskingum parameters using two different objective functions. The proposed algorithm is applied to two case studies from previous literature and the results are compared with those of other methods. The results demonstrate that the MHBMO algorithm not only converges fast but it also captures the best optimal parameter values. The sensitivity analyses, carried out on the MHBMO algorithm control parameters, show that for each parameter, the results are stable for a wide range. Based on the results, it is concluded that the MHBMO algorithm can be used confidently to estimate the parameters of the nonlinear Muskingum model. (C) 2014 American Society of Civil Engineers.