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为探索气候变化影响下水文极值的非平稳性和预测方法,建立了水文极值非平稳广义极值(GEV)分布的统计预测模型。利用1952—2010年淮河上游流域累计面雨量和流量年最大值资料、同期500 h Pa环流特征量资料以及17个CMIP5模式对环流特征量的模拟结果,筛选出对水文极值影响显著的年平均北半球极涡强度指数作为GEV分布参数的预测因子。分析了在RCP2.6、RCP4.5和RCP8.5情景下2006—2050年淮河上游流域水文极值对气候变化的响应。结果表明,10年以下与10年以上重现期的水文极值在非平稳过程中呈现前者下降而后者上升的相反变化趋势;多模型预测的集合平均在未来情景中均呈现上升趋势,情景排放量越大增幅越大,重现期越长增幅也越大。与极值的常态相比,极值的极端态更易受气候变化影响。
In order to explore the non-stationarity and prediction methods of hydrological extremes under the influence of climate change, a statistical prediction model of the distribution of extreme non-stationary and extreme values of hydrology (GEV) was established. Based on the data of accumulated annual rainfall and annual maximum flow in the upper reaches of the Huaihe River Basin from 1952 to 2010, the circulation characteristics of 500 h Pa in the same period and the simulation results of 17 CMIP5 models, the annual mean Polar Vortex Intensity Index in the Northern Hemisphere as a predictor of GEV distribution parameters. In the RCP2.6, RCP4.5 and RCP8.5 scenarios, the response of the hydrological extremes of the Huaihe River upstream to climate change from 2006 to 2050 was analyzed. The results show that the hydrological extremums below 10 years and above 10 years show the opposite trend of the former decreasing and the latter rising in the non-stationary process. The average of the sets of multi-model predictions shows an upward trend in future scenarios, The greater the amount of larger increase, the longer the return period the greater the increase. Compared with the extreme normal, the extreme state of the extreme is more susceptible to climate change.