基于非平稳GEV模型的黄河源区枯季径流演变特征分析

为剖析气候变化对水文极值非平稳性的影响，采用5 a滑动平均和Mann-Kendall突变检验法对黄河唐乃亥水文站1957—2018年最枯多日平均流量进行非平稳检验；根据Kendall等级相关分析法优选气候指数，以时间和气候指数为协变量构建非平稳广义极值分布(generalized extreme value, GEV)模型，并进行参数估计与模型优选，对比平稳与非平稳GEV模型在枯季径流模拟中的应用效果。研究结果表明：黄河源区枯季径流呈现明显的非平稳特征；平稳GEV模型的模拟值偏高，以西太平洋指数为协变量的非平稳GEV模型对极值的拟合效果较好，且能较好地解释极端枯水事件的波动性。

Study on evolution characteristics of dry season runoff using a non-stationary GEV model in Source Region of the Yellow River

The non-stationary characteristics of the average runoff in driest days are tested in this paper based on the measured runoff data of Tangnaihai Hydrological Station from 1957 to 2018 using the 5-year moving average and Mann-Kendall abrupt change test to analyze the effect of climate change on the non-stationary of hydrological extreme value. According to the Kendall rank correlation analysis method, the climate index was selected, and the non-stationary generalized extreme value distribution model (generalized extreme value, GEV) was constructed with time and climate index as covariates. Parameter estimation and model selection were carried out, and application effects of the stationary and non-stationary GEV models in the runoff simulation of dry season were compared. The results indicated that the dry season runoff shows obvious non-stationary characteristics. Meanwhile, the simulated value of the stationary GEV model is higher than the measured value, and the GEV model with the western Pacific index as covariate produces better fit for the extreme value, which better explained the volatility of extreme dry events.