Application of factor analysis in defining drought prone areas in Lake Urmia Basin

Marzie Ghorbani-Aghdam (), Yagob Dinpashoh and Ali Mostafaeipour

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2013, vol. 69, issue 1, 267-277

Abstract: Data reduction methods such as principal components analysis and factor analysis can be used to define drought prone areas of a basin. In this study, factor analysis method applied for the purpose of projecting the information space on the few dominant axes. The main aim of this study is regionalization of Lake Urmia Basin from the view of drought using factor analysis. For this purpose, monthly precipitation data of 30 weather stations in the period 1972–2009 were used. For each of the selected stations, 3- and 12-month Standardized Precipitation Index (SPI) values were calculated. Factor analysis conducted on SPI values to delineate the study area with respect to drought characteristics. Homogeneity of obtained regions tested using the S statistics proposed by Wiltshire. Results of factor analysis of 3- and 12-month SPI values showed that 5 (6) factors having eigenvalues >1 accounted for 68.08 (78.88) % of total variance. The Lake Urmia Basin was delineated into the five distinct homogeneous regions using the 3-month SPI time series. This was six in the case of the 12-month SPI time series. It can be concluded that there are different distinct regions in Lake Urmia Basin according to drought characteristics. The map of regions defined using the 3- and 6-month SPI time series presented in this paper for Lake Urmia Basin. Copyright Springer Science+Business Media Dordrecht 2013

Keywords: Eigenvalue; SPI index; Factor analysis; Drought; Principal component; Lake Urmia (search for similar items in EconPapers)
Date: 2013
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Citations: View citations in EconPapers (3)

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DOI: 10.1007/s11069-013-0706-y

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