Maximum Monthly Rainfall Analysis Using L-Moments for an Arid Region in Isfahan Province, Iran

S. Saeid Eslamian Department of Civil and Environmental Engineering, Princeton University, Princeton, New Jersey

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Hussein Feizi Isfahan University of Technology, Isfahan, Iran

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Abstract

Developing methods that can give a suitable prediction of hydrologic events is always interesting for both hydrologists and statisticians, because of its importance in designing hydraulic structures and water resource management. Because of the computer revolution in statistical computation and lack of robustness in at-site frequency analysis, since early 1990 the application of regional frequency analysis based on L-moments has been considered more for flood analysis. In this study, the above-mentioned method has been used for the selection of parent distributions to fit maximum monthly rainfall data of 18 sites in the Zayandehrood basin, Iran, and as a consequence the generalized extreme-value and Pearson type-III distributions have been selected and model parameters have been estimated. The obtained extreme rainfall values can be used for meteorological drought management in the arid zone.

* Current affiliation: Department of Water Engineering, Ishafan University of Technology, Isfahan, Iran

Corresponding author address: S. Saeid Eslamian, Associate Professor, Department of Water Engineering, Isfahan University of Technology, Isfahan, Iran. Email: saeid@cc.iut.ac.ir

Abstract

Developing methods that can give a suitable prediction of hydrologic events is always interesting for both hydrologists and statisticians, because of its importance in designing hydraulic structures and water resource management. Because of the computer revolution in statistical computation and lack of robustness in at-site frequency analysis, since early 1990 the application of regional frequency analysis based on L-moments has been considered more for flood analysis. In this study, the above-mentioned method has been used for the selection of parent distributions to fit maximum monthly rainfall data of 18 sites in the Zayandehrood basin, Iran, and as a consequence the generalized extreme-value and Pearson type-III distributions have been selected and model parameters have been estimated. The obtained extreme rainfall values can be used for meteorological drought management in the arid zone.

* Current affiliation: Department of Water Engineering, Ishafan University of Technology, Isfahan, Iran

Corresponding author address: S. Saeid Eslamian, Associate Professor, Department of Water Engineering, Isfahan University of Technology, Isfahan, Iran. Email: saeid@cc.iut.ac.ir

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