The Study on Equifinality of Hydrological Model Parameters and Runoff Simulation Based on the Improved Simulation-optimization Algorithm

被引：0
|
作者：
Xing Z. [1 ,2 ]
Wang L. [1 ]
Wang X. [3 ]
Fu Q. [1 ,2 ]
Ji Y. [1 ,2 ]
Li H. [1 ,2 ]
Liu Y. [1 ]
机构：
[1] School of Water Conservancy and Civil Engineering, Northeast Agricultural University, Harbin
[2] Collaborative Innovation Centre of Promote Grain Production in Heilongjiang Province, Harbin
[3] Key Laboratory of Yellow River Sediment of the Ministry of Water Resources, Yellow River Institute of Hydraulic Research, Zhengzhou
来源：
Yingyong Jichu yu Gongcheng Kexue Xuebao/Journal of Basic Science and Engineering | 2020年 / 28卷 / 05期
关键词：
Equifinality; Likelihood weight; Nash model; Parameter calibration; Runoff simulation; SCE-UA; Uncertainty;
D O I：
10.16058/j.issn.1005-0930.2020.05.008
中图分类号：
学科分类号：
摘要：
In order to study the influence of equifinality phenomenon on the accuracy of hydrological forecasting and improve the accuracy, the Nash model parameters were calculated by using the simulation-optimization model, and the equifinality phenomenon was studied in this paper. The traditional SCE-UA algorithm was improved by using the multi-criteria likelihood weight to reduce the equifinality of the parameters and improve the prediction accuracy of the Hydrological Model. Firstly, the SCE-UA algorithm was coupled with the Nash model to build a Simulation-optimization algorithm. The optimal parameter sets of the Nash model were obtained by a large number of cycles of the Simulation-optimization algorithm, and then the characteristics of the equifinality were analyzed. Secondly, the optimal parameter sets were screened again by a Screening Method based on Multi-criteria Likelihood Weight (SMMLW), and then a final optimal parameter set was obtained. Finally, the final optimal parameter set was substituted into the Nash model flood forecasting, and then the floods in verification period was simulated. The 90% confidence interval of flood forecasting was calculated from the Nash model with the optimal parameters sets. The uncertainty of the forecast results was analyzed by 4 evaluation indexes. To compare the effectiveness of the method proposed in this paper, the simulation results based on the SMMLW was compared with that of the SCE-UA algorithm and the AM-MCMC algorithm. The results were shown as below:(1)The influence of equifinality on the Nash model parameters was shown in two aspects, that is, the influence of the value range of the optimal parameters and the influence on the number of optimal parameter sets; (2)The influence degree of the two characteristics of equifinality was both associated with the values of the flood volume and the flood peak. Specifically, the equifinality phenomenon was more obvious with the increasing of the values of the flood volume and the flood peak. (3)For a flood, the simulation accuracy based on the SMMLW was higher than that of the SCE-UA algorithm and the AM-MCMC algorithm. (4)By analyzing the uncertainties of the results of runoff prediction, it was found that the forecast results of Nash model based on SMMLW could well analyze the uncertainties of the forecast results due to the uncertainty of Nash model parameters and get higher accuracy prediction. © 2020, The Editorial Board of Journal of Basic Science and Engineering. All right reserved.
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页码：1091 / 1107
页数：16
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