摘要
针对概念性水文模型如HYMOD模型参数不确定性问题,先对HYMOD模型进行改进,将模型设计成基于子流域的分散式;接着引入参数估计的SCE-UA和SCEM-UA两类算法,以湘江洣水流域为研究区域,对改进的HYMOD模型进行参数优化和不确定性进行了研究。结果表明,两种算法都能搜索到HYMOD模型的最优参数,使模型取得较好的径流模拟结果;但SCEM-UA算法可得到模型参数的后验概率分布,充分考虑模型参数的不确定性,具有更大的优势。
Aiming at the parameter uncertainty of conceptual hydrological model, the HYMOD model is improved and designed the distributed model based on the sub-basin division. And then two types of hydrological model parameter estimation algorithms （i. e. SCE-UA and SCEM-UA algorithms） are introduced. Taking MJshui basin as a case study, it studies the parameters optimization and uncertainty of improved HYMOD model. The results show that two algorithms can search the model＇s optimal parameters and get good runoff simulation; but the SCEM-UA algorithm can obtain the posterior probahility distribution of the mode parameters and consider fully the parameters uncertainty of the model, which has more advantages.
出处
《水电能源科学》
北大核心
2013年第11期17-20,共4页
Water Resources and Power
基金
水利部公益性行业科研专项基金资助项目(201101018)
