With the application of Muskingum routing method,Muskingum water-level simulating method and diffusion wave nonlinear water-level method,flood is forecasted and regulated in the part basin between Wa.

In order to solve the problem of complexity and poor accuracy for parameter estimation in Muskingum model,the chaos was incorporated into particle swarm optimization,chaotic particle swarm optimization algorithm to estimate the parameter of Mustingum model was set up.

The paper approaches and analyzes the application of linear regression method,Muskingum method and method of confluence coefficient to the calculation of low flow of Ning-Meng section of the Yellow River based on the principle of hydrology of flow routing and taking a day as time step.

Then the general design flood with flood peak of 1132m3/s is gained by Muskingum method and sup.

Taking gradient and slope angle as main factors,a watershed is discretized into some sub-catchments according to natural draining divide,and aiming at characteristics of the research area,a rainfall-runoff distributed hydrological model orienting to catchment scale is established in this thesis with combination of runoff yielding and water routing model of SCS and Muskingum method.

Chaos high efficient genetic algorithm for parameter optimization of Muskingum routing model;

Differential Evolution Algorithm for Parameter Optimization of Muskingum Routing Model

By making use of the ant colony algorithm in the continuous space optimization problems,the parameter estimation of Muskingum routing model is solved.

For the parameter estimation problem of flood calculation of Muskingum model,first,it is summed up as a non-linear parameter optimization problem,and then solved by adaptive accelerating differential evolution(AADE).

The parameter of Muskingum equation is usually ascertained by the trial way that were complex and the optimized results not gotten.

Stability Condition Analysis of Muskingum-Cunge Flood Routing Method;