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The use of the exponent K(q) function to delimit homogeneous regions in regional frequency analysis of extreme annual daily rainfall
Author(s) -
GarcíaMarín A. P.,
Estévez J.,
SangüesaPool C.,
PizarroTapia R.,
AyusoMuñoz J. L.,
JimenezHornero F. J.
Publication year - 2014
Publication title -
hydrological processes
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.222
H-Index - 161
eISSN - 1099-1085
pISSN - 0885-6087
DOI - 10.1002/hyp.10284
Subject(s) - quantile , homogeneous , multifractal system , frequency analysis , exponent , extreme value theory , series (stratigraphy) , scaling , environmental science , mathematics , homogeneity (statistics) , statistics , climatology , meteorology , statistical physics , geography , geology , physics , fractal , mathematical analysis , geometry , linguistics , philosophy , paleontology
Abstract The regional frequency analysis of extreme annual rainfall data is a useful methodology in hydrology to obtain certain quantile values when no long data series are available. The most crucial step in the analysis is the grouping of sites into homogeneous regions. This work presents a new grouping criterion based on some multifractal properties of rainfall data. For this purpose, a regional frequency analysis of extreme annual rainfall data from the Maule Region (Chile) has been performed. Daily rainfall data series of 53 available stations have been studied, and their empirical moments scaling exponent functions K(q) have been obtained. Two characteristics parameters of the K(q) functions ( γ max and K(0) ) have been used to group the stations into three homogeneous regions. Only five sites have not been possible to include into any homogenous regions, being the local frequency analysis of extreme daily rainfall the most appropriate method to be used at these locations. Copyright © 2014 John Wiley & Sons, Ltd.