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Analysis and simulation of extreme flow events at Yichang station under climate change

机译:气候变化下宜昌站极端水流事件的分析与模拟

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摘要

The annual maximum, annual minimum and annual average flow data of Yichang station during 1882 –2001 were used to explore the statistical law of extreme flow events through the methods of descriptive analysis, frequency analysis, linear trend analysis, linear regression test and Mann-Kendall test. Then annual maximum flow series were respectively simulated by the generalized extreme value distribution model (GEV) and generalized Pareto distribution model (GPD), and the point and interval estimations of annual maximum flow with the return periods of 10 years, 50 years, 100 years, 200 years and 500 years were derived by the maximum likelihood estimates (MLE) and profile -likelihood method. The results showed that three flow series decreased slowly during 1882 –2001, in which linear trend of annual maximum flow series was not significant, yet the opposite for annual minimum and average flow series. Compared with GPD model, GEV model was more fitting for extreme flow of Yichang station, indicating that the annual maximum flow over that period followed GEV distribution. Estimated values of annual maximum runoff were 67802m3/s and 69263m3/s for 50 and 100 years' return period, which increased with return period.
机译:通过描述性分析,频率分析,线性趋势分析,线性回归检验和Mann-Kendall等方法,利用宜昌站1882-2001年的年最大,年最小和年平均流量数据,探索极端流量事件的统计规律。测试。然后分别用广义极值分布模型(GEV)和广义Pareto分布模型(GPD)分别模拟年最大流量序列,并以10年,50年,100年的回报期对年最大流量进行点和区间估计。通过最大似然估计(MLE)和概貌似然法得出200年和500年。结果表明,三个流量序列在1882年至2001年期间缓慢下降,其中年最大流量序列的线性趋势不明显,而年最小流量和平均流量序列则相反。与GPD模型相比,GEV模型更适合宜昌站的极端流量,表明该期间的年最大流量遵循GEV分布。 50年和100年回归期的年最大径流量估算值为67802m 3 / s和69263m 3 / s,并随着回归期的增加而增加。

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