三种水文模型不确定性分析方法比较

模型不确定性研究是水文科学的重要课题。以尼泊尔Bagmati流域为案例,采用了马尔科夫链蒙托卡罗(Markov Chain Monte Carlo)、蒙托卡罗(Monte Carlo)和拉丁超立方体(Latin Hypercube)等三种方法,分析了水箱模型输出成果的不确定性,并将三种方法所获得参数不确定性进行了比较。另外,运用Meta-Gaussian模型计算了总体不确定性,在基于所采用的似然函数基础上,对由参数导致模型输出的不确定性和模型输出的总体不确定性进行了比较。结果显示,模型的不确定性比参数不确定性更为重要,同时也表明,尽管蒙托卡罗和拉丁超立方体两种模拟方法产生几乎相同的结果,但两者都与马尔科夫链蒙托卡罗方法有很大的不同。

Comparison of Three Methods for Uncertainty Analysis of Hydrologic Models

The uncertainty study on models is an important issue for hydrological science.The case study of the Bagmati river basin in Nepal was applied to analyze the uncertainty of tank model on the basis of three methods including Markov Chain Monte Carlo(MCMC),Monte Carlo simulation(MCS) and Latin Hypercube simulation(LHS).The parameter uncertainty calculated by these three methods was compared with each other.In addition,the total uncertainty was also assessed by the Meta-Gaussian model.The comparison between uncertainty in the model output only with parameter estimates and those with total error implies that the model uncertainty is more important than the parameter uncertainty based on the likelihood function used.The result also indicates that the MCS and LHS give very different estimates from the MCMC in this case,although the former two produce almost the same results with each other.