Regionalization of maximum daily precipitation of Iran

Document Type : Research Article

Authors

• F. Khamchin Moghadam ¹
• H. Sedghi ²
• F. Kaveh ¹
• M. Manshouri ¹

¹ Islamic Azad University, Science and Research Branch – Tehran

² Tehran Science and Research branch, Islamic Azad University, Tehran, Iran

10.22067/jsw.v0i0.2924

Abstract

Abstract
Most heavy storms result in destructive floods. One of the basic elements in analyzing floods in watersheds without data is hourly storms. The Determination of the storm of the watershed needs regional analysis of storms and transferring them to the gravity center of the watershed. Maximum daily precipitation ( ), is the most accessible storm in any region, which can be converted to hourly precipitation. The analysis of the point and regional is one of climate studies requirement. Regionalization of , can be an influential step toward analyzing storms and floods. In order to accomplish such a task, two approaches are possible, one is using the old methods of geographical regionalization and the other one is using the new methods like "Cluster Analysis" and "L-Moments Homogenous Tests". In this paper second approach was employed. All existing rain-gauge stations (N=396) were considered and their available data were collected in this study. Basic tests were applied and 266 stations were removed due to the lack of the required conditions and only 130 stations were used in analysis. "Principal Components" method was used to omit the uninfluential variables (only 6 variables out of 21 were proved as basic and important). "Hierarchical Clustering" was used in the process of regionalization of the stations indicated of seven different regions. These regions were distributed in different locations throughout the country and the regionalization map is presented. The "L-Moments Homogenous Tests" were also employed for further indication. According to the final results, the regionalization of of Iran's rain-gauge stations can be defined as 7 homogenous regions.

Keywords: Regionalization, Maximum daily precipitation, Principal Components, Cluster Analysis, L-Moment

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