Comparison and evaluation of uncertainties in extreme flood estimations of the upper Yangtze River by the Delta and profile likelihood function methods

• Published in: Stochastic environmental research and risk assessment Vol. 31; no. 9; pp. 2281 - 2296
• Main Authors: Wang, Jianhua, Lu, Fan, Lin, Kairong, Xiao, Weihua, Song, Xinyi, He, Yanhu
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.11.2017; Springer Nature B.V
• Subjects: Aquatic Pollution; Asymmetry; Chemistry and Earth Sciences; Computational Intelligence; Computer Science; Confidence intervals; Design floods; Earth and Environmental Science; Earth Sciences; Environment; Extreme values; Flood discharge; Floods; Hydrologic research; Hydrology; Math. Appl. in Environmental Science; Mathematical analysis; Original Paper; Physics; Probability Theory and Stochastic Processes; Quantiles; River basins; Rivers; Stations; Statistical analysis; Statistics for Engineering; Tributaries; Uncertainty analysis; Waste Water Technology; Water Management; Water Pollution Control; Weibull distribution; Yangtze River; Uncertainty; Extreme flood; Profile likelihood function; Delta method; Yangtze River
• ISSN: 1436-3240; 1436-3259
• DOI: 10.1007/s00477-016-1370-z

Frequency calculation for extreme flood and methods used for its uncertainty estimation are popular subjects in hydrology research. In this study, uncertainties in extreme flood estimations of the upper Yangtze River were investigated using the Delta and profile likelihood function (PLF) methods, which were used to calculate confidence intervals of key parameters of the generalized extreme value distribution and quantiles of extreme floods. Datasets of annual maximum daily flood discharge (AMDFD) from six hydrological stations located in the main stream and tributaries of the upper Yangtze River were selected in this study. The results showed that AMDFD data from the six stations followed the Weibull distribution, which has a short tail and is bounded above with an upper bound. Of the six stations, the narrowest confidence interval can be detected in the Yichang station, and the widest interval was found in the Cuntan station. Results also show that the record length and the return period are two key factors affecting the confidence interval. The width of confidence intervals decreased with the increase of record length because more information was available, while the width increased with the increase of return period. In addition, the confidence intervals of design floods were similar for both methods in a short return period. However, there was a comparatively large difference between the two methods in a long return period, because the asymmetry of the PLF curve increases with an increase in the return period. This asymmetry of the PLF method is more proficient in reflecting the uncertainty of design flood, suggesting that PLF method is more suitable for uncertainty analysis in extreme flood estimations of the upper Yangtze River Basin.