Abstract: In this study,a new method,Gray Code Hybrid Accelerating Genetic Algorithm (GCHAGA),and its detailed steps are developed to identify water environment model parameters.With the shrinking of searching range,the method gradually directs to optimal result by the excellent individuals obtained by gray code genetic algorithm (GCGA) embedding with simplex searching operator and simplex algorithm.Further,the convergence and global optimization of the GCHAGA is discussed theoretically and practically,and its high precision on global optimization is ascertained over such parameters as river transverse diffuse coefficients model.Compared with the GCGA and the conventional optimization methods,the GCHAGA remarkably improves convergence speed and calculation accuracy.It proves a good nonlinear optimal method that can search both global solution and fractional one in greater probability,and could be applied to various water environment optimization issues.