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Probability Distribution of Flood Flows in Tunisia : Volume 12, Issue 3 (06/05/2008)

By Abida, H.

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Book Id: WPLBN0003977360
Format Type: PDF Article :
File Size: Pages 12
Reproduction Date: 2015

Title: Probability Distribution of Flood Flows in Tunisia : Volume 12, Issue 3 (06/05/2008)  
Author: Abida, H.
Volume: Vol. 12, Issue 3
Language: English
Subject: Science, Hydrology, Earth
Collections: Periodicals: Journal and Magazine Collection (Contemporary), Copernicus GmbH
Historic
Publication Date:
2008
Publisher: Copernicus Gmbh, Göttingen, Germany
Member Page: Copernicus Publications

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Ellouze, M., & Abida, H. (2008). Probability Distribution of Flood Flows in Tunisia : Volume 12, Issue 3 (06/05/2008). Retrieved from http://www.worldlibrary.org/


Description
Description: Department of Earth Sciences, Faculty of Science, Sfax, BP 802, 3018 Tunisia. L (Linear) moments are used in identifying regional flood frequency distributions for different zones Tunisia wide. 1134 site-years of annual maximum stream flow data from a total of 42 stations with an average record length of 27 years are considered. The country is divided into two homogeneous regions (northern and central/southern Tunisia) using a heterogeneity measure, based on the spread of the sample L-moments among the sites in a given region. Then, selection of the corresponding distribution is achieved through goodness-of-fit comparisons in L-moment diagrams and verified using an L moment based regional test that compares observed to theoretical values of L-skewness and L-kurtosis for various candidate distributions. The distributions used, which represent five of the most frequently used distributions in the analysis of hydrologic extreme variables are: (i) Generalized Extreme Value (GEV), (ii) Pearson Type III (P3), (iii) Generalized Logistic (GLO), (iv) Generalized Normal (GN), and (v) Generalized Pareto (GPA) distributions. Spatial trends, with respect to the best-fit flood frequency distribution, are distinguished: Northern Tunisia was shown to be represented by the GNO distribution while the GNO and GEV distributions give the best fit in central/southern Tunisia.

Summary
Probability distribution of flood flows in Tunisia

Excerpt
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