水文模型参数多目标率定及最优非劣解优选

发布时间：2018-03-18 00:08

  本文选题：水文模型参数率定　切入点：多目标优化　出处：《水文》2017年02期 　论文类型：期刊论文

【摘要】：针对概念性水文模型参数众多、相互制约,且多目标参数优化率定最优参数求解困难、易受决策者主观因素影响的问题,采用多目标优化算法对水文模型参数进行率定,得到模型参数最优非劣解集,在此基础上,引入最小最大后悔值决策理论,并结合Pareto支配基本理论,提出了一种多目标最优非劣解选取准则。以柘溪流域为研究对象,采用三目标MOSCDE优化率定新安江模型的参数,并与单目标SCE-UA优化结果进行对比分析。结果表明,提出的非劣解选取方法可以有效从大规模非劣解集中筛选出最优非劣解,大大缩短参数率定耗时。
[Abstract]:According to the conceptual hydrological model has many parameters and restrict each other, and multi-objective parameter optimization and calibration of the optimal parameters is difficult to be influenced by the decision-maker's subjective factors, using a multi-objective optimization algorithm for calibration of hydrological model parameters, get the optimal model parameters of non inferior solutions, on the basis of introducing the minimum maximum regret value decision theory, and combined with Pareto control theory, a multi-objective optimal Pareto selection criterion is proposed. In order to Zhexi basin as the research object, using the three parameter optimization target MOSCDE rate model of Xin'An River, and the single target SCE-UA optimization results were compared and analyzed. The results show that the proposed selection method of non inferior solution can from a large non inferior solution set to select the best non inferior solution, greatly shorten the calibration time.

【作者单位】： 华中科技大学水电与数字化工程学院;大连理工大学水利工程学院;
【基金】：国家自然科学基金重大研究计划重点支持项目(91547208);国家自然科学基金项目(51579017) 水利部公益性行业科研专项经费项目(201401014-2)
【分类号】：P333
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本文编号：1627103