新安江模型参数有效优化及不确定性评估  

Effective optimization and uncertainty assessment of Xin'anjiang model parameters

作　　者：王文川[1,2] 程春田[1] 邱林[2] 杨斌斌[1] 

机构地区：[1]大连理工大学水电与水信息研究所,辽宁大连116085 [2]华北水利水电学院,郑州450011

出　　处：《中国工程科学》2010年第3期100-107,112,共9页Strategic Study of CAE

基　　金：国家自然科学基金(50679011);水利部公益性行业科研专项(200801015);华北水利水电学院高层次人才科研启动资助项目(200821)

摘　　要：应用新安江模型进行水文模拟时,由于模型本身的不足及参数多、信息量少等原因,会出现率定的最优参数组不唯一、不稳定等问题。考虑到以往的参数优选,都只得出一个参数组,不能反映出其不确定性状况。提出应用基于马尔可夫链蒙特卡罗(MCMC)理论的SCEM-UA算法,通过双牌流域以1 h为时段间隔的36场典型洪水数据对新安江模型参数进行优选和不确定性评估。结果表明,该算法能很好地推出新安江模型参数的后验概率分布;率定和检验结果分析也表明,应用SCEM-UA算法对新安江模型进行优选和不确定评估是有效和可行的。While Xin＇anjiang model is applied to simulate hydrograph,the ＂best＂ parameter set calibrated may be not unique and uncertain because of model limitation,more parameters and limited information.Considering previously parameter optimization of Xin＇anjiang model,there is only a unique ＂best＂ parameter set to be found and it doesn＇t describe uncertainty of parameter.This paper presents using SCEM-UA algorithm based Markov Chain Monte Carlo（MCMC） methods for optimization and uncertainty assessment of Xin＇anjiang model parameters by means of 36 historical floods data with one hour interval.The results demonstrate that SCEM-UA algorithm is well suited to infer the posterior distribution of Xin＇anjiang model parameters.The results of calibration and validation indicate that it is feasible and effective for optimization and uncertainty assessment of Xin＇anjiang model parameters.

关 键 词：新安江模型 参数率定 不确定性评估 SCEM-UA 

分 类 号：P338.9[天文地球—水文科学]