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Nonparametric Kernel Estimation of Flood Frequencies
Author(s) -
Adamowski Kaz
Publication year - 1985
Publication title -
water resources research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.863
H-Index - 217
eISSN - 1944-7973
pISSN - 0043-1397
DOI - 10.1029/wr021i011p01585
Subject(s) - nonparametric statistics , parametric statistics , kernel density estimation , kernel (algebra) , statistical inference , flood myth , statistics , econometrics , estimation , probability distribution , empirical distribution function , mathematics , distribution (mathematics) , computer science , engineering , geography , estimator , archaeology , systems engineering , combinatorics , mathematical analysis
A currently used approach to flood frequency analysis is based on the concept of parametric statistical inference. In this analysis the assumption is made that the distribution function describing flood data is known, for example, a log‐Pearson type III distribution. However, such an assumption is not always justified and often leads to other difficulties; it could also result in considerable variability in the estimation of design floods. A new method is developed in this article based on the nonparametric procedure for estimating probability distribution function. The results indicate that design floods computed from the different assumed distribution and from the nonparametric method provide comparable results. However, the nonparametric method is a viable alternative with the advantage of not requiring a distributional assumption, and has the ability of estimating multimodal distributions.