Regional Frequency Analysis: An Approach Based on L-Moments
Extreme environmental events, such as floods, droughts, rainstorms, and high winds, have severe consequences for human society. Regional frequency analysis helps to solve the problem of estimating the frequency of these rare events at one site by using data from several sites. This book is the first complete account of the L-moment approach to regional frequency analysis. Regional Frequency Analysis comprehensively describes the theoretical background to the subject, is rich in practical advice for users, and contains detailed examples that illustrate the approach. This book will be of great value to hydrologists, atmospheric scientists and civil engineers, concerned with environmental extremes.
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Chapter 1 Regional frequency analysis
Chapter 2 Lmoments
Chapter 3 Screening the data
Chapter 4 Identification of homogeneous regions
Chapter 5 Choice of a frequency distribution
Chapter 6 Estimation of the frequency distribution
Chapter 7 Performance of the regional Lmoment algorithm
Chapter 8 Other topics
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annual maximum streamﬂow approximately at-site estimation at-site frequency distributions basin calculated characteristics cluster analysis correlation cumulative distribution function deﬁned in Eq Deﬁnition discordant drainage basin estimated growth curve estimated quantiles example extreme-value distribution ﬁnal ﬁrst ﬁt ﬁtted distribution ﬁtting ﬂood gaging Gumbel Gumbel distribution heterogeneity measure heterogeneous regions homogeneous region Hosking and Wallis index-ﬂood procedure inﬂuence intersite dependence kappa distribution kurtosis L-CV and L-skewness L-skewness and L-kurtosis logistic logistic distribution lognormal distribution methods misspeciﬁcation nonexceedance probability number of sites parameters Pareto Pareto distribution Pearson type probability weighted moments quantile estimates quantile function random variable record length Region R2 regional average L-moment regional average relative regional estimation regional frequency analysis regional frequency distribution regional growth curve regional L-moment algorithm regional shape estimation relative bias RMSE of estimated sample L-moment ratios shape parameter signiﬁcance Simulation results skewness speciﬁcation Stedinger type III distribution variability variation Wakeby distribution zero