Trend Analysis of Dusty Days Frequency and its Correlation with Climatic Variables (Case Study: Lorestan Province)

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.

Ansari Ghojghar Mohammad; ARAGHINEJAD SHAHAB; BAZRAFSHAN JAVAD; HOORFAR ABDOLHOSEIN

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

Journal Paper

Paper Information

Journal: Iranian Journal of Soil and Water Research Year:2020 | Volume:50 | Issue:9 Page(s): 2289-2301

Download Full-Text

Persian Verion

View:

452

Download:

Cites:

Information Journal Paper

Title

Trend Analysis of Dusty Days Frequency and its Correlation with Climatic Variables (Case Study: Lorestan Province)

Author(s)

Ansari Ghojghar Mohammad | ARAGHINEJAD SHAHAB | BAZRAFSHAN JAVAD | HOORFAR ABDOLHOSEIN | Issue Writer Certificate

Keywords

Dust StormQ1

Non-parametric TestQ1

Kolmogorov-Smirnov TestQ2

Pearson CorrelationQ1

Abstract

In this research in order to find and investigate the trend of dusty day events and their relation to climatic variables (maximum temperature and maximum wind speed), hourly and daily dust data and also weather data of 10 synoptic stations with common period (2000-2014) in Lorestan province were studied. For this purpose, data normalization was examined by Kolmogorov-Smirnov Test. The non-parametric Mann-Kendall and Spearman’ s tests at 95 percent confidence level were used to investigate the trend of dusty events. Inverse distance weighting (IDW) method in Arc GIS software was employed for zoning Mann-Kendall indices of dust and climatic variables. In order to find a correlation between climatic variables and dust events, the weather data (as independent variables) and the frequency of dusty days (as a dependent variable) were analyzed by Pearson Correlation method. Among ten series of seasonal data, Azna, Aligudarz and Kuhdasht stations had a high significant correlation between climatic variables and the frequency of dusty days. As in Azna station, the maximum wind speed variable (with 0. 55 correlation coefficient), in Aligudarz station, the maximum temperature variable (with 0. 78 correlation coefficient), and in Kuhdasht station, the maximum wind speed variable (with 0. 82 correlation coefficient) had the highest correlation with dust events.

Cites

No record.

References

No record.

Cite

APA: Copy

Ansari Ghojghar, Mohammad, ARAGHINEJAD, SHAHAB, BAZRAFSHAN, JAVAD, & HOORFAR, ABDOLHOSEIN. (2020). Trend Analysis of Dusty Days Frequency and its Correlation with Climatic Variables (Case Study: Lorestan Province). IRANIAN JOURNAL OF SOIL AND WATER RESEARCH, 50(9 ), 2289-2301. SID. https://sid.ir/paper/225364/en

Vancouver: Copy

Ansari Ghojghar Mohammad, ARAGHINEJAD SHAHAB, BAZRAFSHAN JAVAD, HOORFAR ABDOLHOSEIN. Trend Analysis of Dusty Days Frequency and its Correlation with Climatic Variables (Case Study: Lorestan Province). IRANIAN JOURNAL OF SOIL AND WATER RESEARCH[Internet]. 2020;50(9 ):2289-2301. Available from: https://sid.ir/paper/225364/en

IEEE: Copy

Mohammad Ansari Ghojghar, SHAHAB ARAGHINEJAD, JAVAD BAZRAFSHAN, and ABDOLHOSEIN HOORFAR, “Trend Analysis of Dusty Days Frequency and its Correlation with Climatic Variables (Case Study: Lorestan Province),” IRANIAN JOURNAL OF SOIL AND WATER RESEARCH, vol. 50, no. 9 , pp. 2289–2301, 2020, [Online]. Available: https://sid.ir/paper/225364/en

Related Journal Papers