Effects of uncertainty in determining the parameters of the linear Muskingum method using the particle swarm optimization (PSO) algorithm

Abstract

The Muskingum method is one the simplest and most applicable methods of flood routing. Optimizing the coefficients of linear Muskingum is of great importance to enhance accuracy of computations on an outflow hydrograph. In this study, considering the uncertainty of flood in the rivers and by application of the particle swarm optimization (PSO) algorithm, we used the data obtained from three floods simultaneously as basic flood to optimize parameters of linear Muskingum (X, K and ), rather than using inflow and outflow hydrographs of a single basic flood (observational flood), and optimized the outflow discharge at the beginning of flood (O1) as a percentage of inflow discharge at the beginning of flood (I1). The results suggest that the closer inflow discharge variation of basic flood to the inflow discharge variation of observational flood, the greater the accuracy of outflow hydrograph computations. Moreover, when the proposed approach is used to optimize parameters of X, K and , the accuracy of outflow hydrograph computations will increase too. In other words, if rather than using a single basic flood, the proposed approach is applied, the average values of mean relative error (MRE) of total flood for the first, second, third and fourth flood will be improved as 31, 13, 39 and 33%, respectively. HIGHLIGHTS Optimization of the parameters of the linear Muskingum method.; Using the PSO algorithm to optimize the parameters.; To consider the uncertainty of the flood.; Considering the inflow and outflow hydrographs of three floods simultaneously to the basic flood.; Optimizing the outflow discharge at the start of the flood (O1) as a fraction of the inflow discharge at the start of the flood (I1).;

Keywords

• basic flood
• linear muskingum method
• parameters optimization
• particle swarm optimization (pso) algorithm
• uncertainty