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 problem of the uncertainty of the conceptual hydrological model such as HYMOD model, the HYMOD model is improved and the model is designed to be based on the decentralized sub-basin. Secondly, SCE-UA and SCEM-UA are used to estimate the parameters. The Huangshui River Basin is the research area, and the parameters optimization and uncertainty of the improved HYMOD model are studied. The results show that both algorithms can search the optimal parameters of the HYMOD model and make the model get better runoff simulation results. However, the posterior probability distribution of the model parameters can be obtained by the SCEM-UA algorithm, taking into account the uncertainty of the model parameters , Has a greater advantage.