两变量设计洪水估计的不确定性及其对水库防洪安全的影响

在两变量水文频率分析中,样本系列容量一般较小,使得水文设计值估计具有不确定性。本文基于Copula函数和Parametric Bootstrap方法,并考虑联合设计值的最可能组合模式,建立可描述两变量设计洪水估计不确定性的C-PBU(Copula-based Parametric Bootstrap Uncertainty)模型,同时提出了定量评价两变量不确定性的度量指标,分析了联合设计值估计不确定性对水库最高调洪水位的影响,并对比了不同典型洪水选取模式下的水位不确定性。以隔河岩水库为例,推求了两变量设计值估计的95%置信区域;比较了不同样本容量对不确定性的影响。结果表明:设计洪水估计和典型洪水选择具有较大的不确定性,可采用C-PBU模型推求置信区间,来考虑设计洪水估计不确定性对水库防洪安全的影响。

Uncertainty of bivariate design flood estimation and its impact on reservoir flood prevention

The limited sample size would induce quantile estimation uncertainty in bivariate hydrological frequency analysis. A copula-based parametric bootstrap uncertainty (C-PBU) model considering the most likely realization to characterize the uncertainty of bivariate design flood estimation is proposed,and the quantitative uncertainty evaluation indexes are presented. The impacts of joint quantile estimation uncertainty on reservoir operation are explored and such uncertainty of highest reservoir water level derived from different typical flood hydrograph (TFH) schemes were compared. The 95% confidence regions of bivariate quantile estimation in the Geheyan reservoir are derived, and the influences of different sample sizes on uncertainty are investigated. The results demonstrate that the bivariate quantile estimation and TFH selection have large uncertainty. It is suggested to consider the uncertainty of reservoir flood prevention in practice by using of the C-PBU model.