Title: The clustering analysis and spatial interpolation of intense rainfall data

Authors: Zhi-Mou Chen; Yi-Lung Yeh; Ting-Chien Chen

Addresses: Institute of Disaster Prevention on Hillslopes and Water Resources Engineering, National Pingtung University of Science and Technology, 1, Shuefu Road, Neipu, Pingtung 91201, Taiwan ' Department of Civil Engineering, National Pingtung University of Science and Technology, 1, Shuefu Road, Neipu, Pingtung 91201, Taiwan ' Department of Environmental Science and Engineering, National Pingtung University of Science and Technology, 1, Shuefu Road, Neipu, Pingtung 91201, Taiwan

Abstract: The measurement of rainfall data during disaster periods is an important task. Unfortunately, some rainfall data will be missed owing to unpredictable factors. Therefore, this study first collected the hourly rainfall records from past disaster events. Next, a statistic cluster analysis method was used to analyse the correlation between the rainfall records in each station. Finally, a spatial interpolation computing method was applied within each cluster to predict reliable rainfall estimates for the areas that lacked past rainfall records. The cluster analysis results showed that selecting the nearby three to four rainfall stations for the spatial interpolation analysis simplified the calculation process. In particular, the result of grouped cluster analysis could enhance the accuracy of the rainfall estimation in the mountainous areas. This study established a reliable rainfall estimation method as a basis for future regional disaster analysis.

Keywords: intense rainfall; cluster analysis; spatial interpolation computing; rainfall estimation.

DOI: 10.1504/IJEM.2018.090882

International Journal of Emergency Management, 2018 Vol.14 No.2, pp.122 - 136

Received: 16 Feb 2016
Accepted: 27 Jun 2016

Published online: 07 Mar 2018 *

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