Mapping of Dusty Stormy Days in Iran Using Geostatistical and Mathematical Methods

Subject Areas : GIS

Hassan Fathizad ¹ , Ali Khanamani ² , mohammad zare ³

1 - Ph.D., Combat Desertification, Department of Arid and Desert Regions Management, College of Natural Resources and Desert, Yazd University, Iran.
2 - Ph.D., Combat Desertification, Department of Arid and Desert Regions Management, College of Natural Resources and Desert, Yazd University, Iran.* (Corresponding Author)
3 - Associate Professor, Department of Arid and Desert Regions Management, College of Natural Resources and Desert, Yazd University, Iran.

Received: 2017-12-25 Accepted : 2018-10-17 Published : 2020-10-22

Keywords: Kriging, dust storm, Interpolation, Iran, Visibility,

Abstract :

Background and Objective: The number of stormy days is determined by various factors such as wind speed, rainfall, soil moisture and so on. The study of this index in the country can be considered in various plans. The purpose of this research is mapping of the number of dusty stormy days in Iran and selecting the best model based on the climatic data of 150 meteorological stations for the period of 25 years (1986-2010). Method: Dust stormy days’ data of the studied stations were analyzed using variogram curves to represents their spatial correlation. Gaussian variogram (R2=0.96) shows the highest correlation between the data. Then, map of the number of dust stormy days in Iran were prepared using different geostatistical and mathematical methods. For this purpose, several mathematical interpolation methods including Inverse Distance Method (IDW), Global Polynomial Interpolation (GPI), Radial Basis Function (RBF), Local Polynomial Interpolation (LPI), and geostatistical method of Kriging were used. To select the best interpolation method among several geostatistical and mathematical methods, statistical indicators of Root Mean Square (RMS) and correlation coefficient between observed and predicted data were used. Findings: Results show that the highest correlation between predicted and observed data (R2 = 0.74) was found in kriging indicator method. The southeast and southwest of the country have the highest number of dust storm days. Discussion and Conclusion: High number of dust stormy days in the southeast is resulting from drying of Hammon lakes and blowing of 120-day winds in Sistan plain, and entering of dust from Arabic countries form the direction of southwest. North part of the country has the lowest number of dust storm days.

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