Multi-Objective Optimization of Hydrological Model Parameters Based on the Stage-Weighted Ideal Point Method

Because of the complexity of calculation and the contradiction between multiple objectives in the multi-objective optimization of hydrological model parameters, a multi-objective optimization method based on the stage-weighted ideal point method was proposed. Taking the ABCD hydrological model as a monthly runoff prediction model, four kinds of objective functions, namely, overall water balance error, average relative error, Nash-Sutcliffe coefficient of high flow, and Nash-Sutcliffe coefficient of low flow, were constructed. The multi-objective functions were converted into a single objective by the stage-weighted ideal point method and solved by particle swarm optimization. The models were applied to the simulation of monthly runoff in the Jinghe River Basin. Four simulation schemes were set up, namely, full period(A), wet period(B), dry period(C), and staged simulation combination(D). The simulation results under different schemes were analyzed. The results show that in the full period(A)simulation scheme, the multi-objective optimization scheme(A5)can effectively represent multiple hydrological process characteristics and coordinate the mutual exclusion relationship between objective functions. Moreover, the simulation effects of multi-objective optimization are better than those of single-objective optimization. In the staged simulation combination scheme, the sub-scheme can not only reflect the hydrological characteristics of the objective function reasonably, but also take into account other objective functions when the weights of the rainy-period and low-water objectives are 0.75; thus, this scheme is better than the other schemes. The staged simulation combination scheme had a better simulation effect than the multi-objective optimization scheme in the high-flow and low-flow periods. The correlation and efficiency coefficients of the evaluation indices are all greater than 0.8, and the average absolute percentage error is less than 1%. This finding shows that the scheme of the staged simulation combination scheme can effectively improve the simulation accuracy of the model. © 2021, Editorial Board of Journal of Tianjin University(Science and Technology). All right reserved.