Spatio-Temporal delineation of Iran’ s Precipitation Climate and Selection of Indicator Stations Using the Multivariate Statistical Methods

Q: How can I download an article?

To download an article from SID, first log in to the site, search for the article title, and click on the 'Download Article' option.

Q: How can I download an ISI article?

To download an ISI article on SID, enter the keyword or article title in the search bar, view the relevant results, click on the desired article, and select the 'Download Article' option.

Q: How can I access the SID database?

To access the SID database, visit SID.ir, create an account, and log in to access scientific resources.

Q: Is downloading articles from SID free?

Some articles on SID are available for free, while others require payment. Details are specified on the article's page.

Isazadeh M.; DINPASHOH Y.

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Journal Paper

Paper Information

Journal: WATER AND SOIL SCIENCE (AGRICULTURAL SCIENCE) Year:2018 | Volume:28 | Issue:3 Page(s): 169-181

Download Full-Text

Persian Verion

View:

454

Download:

Cites:

Information Journal Paper

Title

Spatio-Temporal delineation of Iran’ s Precipitation Climate and Selection of Indicator Stations Using the Multivariate Statistical Methods

Author(s)

Isazadeh M. | DINPASHOH Y. | Issue Writer Certificate

Keywords

ClimateQ3

Cluster analysisQ3

IranQ2

Multivariate methodsQ3

PrecipitationQ1

Principal component analysisQ2

Abstract

In the present study, the information of 31 synoptic weather stations in the period of 1987-2010 were used to delineate Iran’ s Precipitation regions. For this purpose, each month’ s data were standardized and written in the (n*m) matrix, where n is the number of stations (31) and m is the number of months (12). Principal component analysis was conducted on the mentioned matrix. The main components were determined according to the criterion of having an eigen value greater than one. Then principal components scores were calculated for the selected components. These valeus were used as an input for Ward method of Cluster analysis. Then according to the cluster diagram, Precipitation Climates of the country were identified. The Procrustes analysis (PA) was used to answer the question of which stations could be considered as the indicator of rainfall Climates? Furthermore, from this method those months, which their Precipitation can be recognized as an indicator of annual rainfall, were selected. Results showed that the first three components incorporated more than 97% of total variance. Based on the selected components the six distinct Precipitation regions were distinguished across the country. Furthermore, PA results indicated that the Precipitation of May, August and December approximately had whole of the annual Precipitation information. Moreover, it was found that seven stations located in different points of the country namely Zahedan, Tehran, Urmia, Ilam, Yasooj, Gorgan and Rasht could be considered as the indicator stations. These stations incorporated over 87 percent of total variance of data of all selected stations in the country.

Cites

No record.

References

No record.

Cite

APA: Copy

Isazadeh, M., & DINPASHOH, Y.. (2018). Spatio-Temporal delineation of Iran’ s Precipitation Climate and Selection of Indicator Stations Using the Multivariate Statistical Methods. WATER AND SOIL SCIENCE (AGRICULTURAL SCIENCE), 28(3 ), 169-181. SID. https://sid.ir/paper/147690/en

Vancouver: Copy

Isazadeh M., DINPASHOH Y.. Spatio-Temporal delineation of Iran’ s Precipitation Climate and Selection of Indicator Stations Using the Multivariate Statistical Methods. WATER AND SOIL SCIENCE (AGRICULTURAL SCIENCE)[Internet]. 2018;28(3 ):169-181. Available from: https://sid.ir/paper/147690/en

IEEE: Copy

M. Isazadeh, and Y. DINPASHOH, “Spatio-Temporal delineation of Iran’ s Precipitation Climate and Selection of Indicator Stations Using the Multivariate Statistical Methods,” WATER AND SOIL SCIENCE (AGRICULTURAL SCIENCE), vol. 28, no. 3 , pp. 169–181, 2018, [Online]. Available: https://sid.ir/paper/147690/en

Related Journal Papers