Analysis of the Trend of Dust Changes in Ardestan Region, Iran

Document Type: Original Article

Authors

1 Assistant professor, Faculty of Geography and Environmental Sciences, Hakim Sabzevari University

2 Department of Rehabilitation of Arid and Mountainous Regions, University of Tehran, Iran

10.22052/jdee.2019.173755.1049

Abstract

Dust storms in central Iran are a natural hazard, and Tigris-Euphrates alluvial plain has been recognized as the main dust source in this area. In the present study, changes in dust events during the studied months, seasons and years (2000-2013) for Ardestan synoptic station, and their relationship to drought Standardized Precipitaion Index (SPI) were evaluated. The index is an standard indicator for precipitation. Additionally, non-parametric procedures in statistics, including Mann-Kendall and Sen-Stimator, were utilized to identify the changes trend in frequency of days with dust storms on monthly and annual scales. For this purpose, the statistics of selected station was utilized in a 14-year period. Codes extraction related to dust event (06 and 07) and data analysis were conducted using the MATLAB software, and to study the changes trend in monthly and annual time series, non-parametric test statistics were calculated, and then their significance was evaluated at 5 and 1 percentage error. The results showed that may and spring had the most dust events number compared to other months and seasons. Furthermore, results showed that there was a direct relationship between dust event and drought and years having intensive drought, resulted in more duct events. The results indicated that in Mann-Kendall procedure, of total 13 data series, annual data series and in San-Estimator method, August had positive significant trend at 1% probability level and in San-Estimator method, data series in April and June months had an increasing trend at 5% confidence level. The results of spatial analysis of anemometer data using WR plot showed that direction of dominant winds was toward south. The results showed that the integration of dust model and satellite images of dust could be used as an effective system to assess and alert the dust crisis rapidly.

Keywords