Factor analysis and multiple regression between topography and precipitation on Jeju Island, Korea

Myoung Jin Um, Hyeseon Yun, Chang Sam Jeong, Jun Haeng Heo

Research output: Contribution to journalArticlepeer-review

39 Citations (Scopus)


In this study, new factors that influence precipitation were extracted from geographic variables using factor analysis, which allow for an accurate estimation of orographic precipitation. Correlation analysis was also used to examine the relationship between nine topographic variables from digital elevation models (DEMs) and the precipitation in Jeju Island. In addition, a spatial analysis was performed in order to verify the validity of the regression model. From the results of the correlation analysis, it was found that all of the topographic variables had a positive correlation with the precipitation. The relations between the variables also changed in accordance with a change in the precipitation duration. However, upon examining the correlation matrix, no significant relationship between the latitude and the aspect was found. According to the factor analysis, eight topographic variables (latitude being the exception) were found to have a direct influence on the precipitation. Three factors were then extracted from the eight topographic variables. By directly comparing the multiple regression model with the factors (model 1) to the multiple regression model with the topographic variables (model 3), it was found that model 1 did not violate the limits of statistical significance and multicollinearity. As such, model 1 was considered to be appropriate for estimating the precipitation when taking into account the topography. In the study of model 1, the multiple regression model using factor analysis was found to be the best method for estimating the orographic precipitation on Jeju Island.

Original languageEnglish
Pages (from-to)189-203
Number of pages15
JournalJournal of Hydrology
Issue number3-4
Publication statusPublished - 2011 Nov 22

Bibliographical note

Funding Information:
This research was supported by a Grant ( 09CCTI-B054362 ) from “ Hydrologic Impact Analysis and Outlook due to Climate Change Project ” from the Construction Technology Innovation Program (CTIP) funded by the Ministry of Land, Transportation, and Maritime Affairs (MLTM) of Korean government. And this work was supported in part by the Yonsei University Research Fund of 2010.

All Science Journal Classification (ASJC) codes

  • Water Science and Technology


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