| چکیده انگلیسی مقاله |
Extended abstract 1- Introduction Dust has a significant impact on radiation budget, global biogeochemical cycles, soil structure, atmospheric chemical composition, air quality and public health. Natural and human factors have increased the frequency and severity of dust storms in the country in recent years. The most important natural factors are rainfall, drought persistence and global warming, and human factors include surface water control, agricultural development and uncontrolled groundwater consumption, land degradation and excessive use of climatic and ecological potential of the region. These factors can lead to the development of dust centers and increase their activity. 2- Methodology This study was conducted in Central Iran, where one of the most important environmental problems in this region is the occurrence of destructive dust storms. Arid and semi-arid climate, bare soil with sparse vegetation and severe storms are the characteristics of the central region of Iran that prepare the conditions for the occurrence of dust storms. The provinces of Kerman, Yazd, Isfahan, western parts of Sistan and Baluchestan, Semnan province, Khorasan Razavi are directly affected by the consequences of these events. In order to analyze the frequency of dust days, dust codes taken from 37 synoptic meteorological stations with longer statistics were used. For each station, the number of dust days on an annual scale in the statistical period 1999 to 2018 was extracted. In order to analyze the frequency of dust days, Professional5 Easyfit statistical software was used, based on which the most appropriate statistical distribution function for each synoptic station was selected. EasyFit Professional software fits data into 61 distribution functions. Then, using the Kolmogorov-Smirnov test, the most appropriate probability distribution function was determined. 3- Results The results show that the statistical distribution of Johnson SB was found to have the highest frequency in the study area. The Log-Logistic (3P) statistical distribution ranks next. A number of stations such as Bam, Kerman, Nain, Arak, Saveh, Mahallat, Zabol, Semnan, Qom, Zahedan, Yazd and Tabas can have more than 100 days of dust in the return period of 50 or 100 years. Also, Tabas, Qom, Yazd, Zabol, Zahedan and Arak stations show at least 50 days of dust every year. The zoning of dust days with a return period of 5 years also shows that the southeastern parts of the study area, as well as areas in the center and northwest of the basin, can be identified as sources of internal dust. The zoning of dust days with a return period of 25 years shows that the southeastern parts of the study area below the Loot basin and also the northeastern parts of the study area below the central desert basin (desert plain) can have a maximum of 225 dust days in the return period. The results of frequency analysis of dust days with a return period of 50 years show that in some areas of the study area, more than 276 days of dust per year can occur and these areas are identified as dust sources in the study area. 4- Discussion & Conclusions In recent years, dust events in the West Asian region have occurred with greater frequency and intensity. Dust phenomenon in Sistan and Baluchestan, Kerman, Yazd, Isfahan, Semnan and Khorasan Razavi provinces is one of the most important challenges. Identifying and predicting dust source in these areas are of great importance.One of the most important forecasting methods in different return periods is the use of statistical distributions. In this study, using 61 statistical distributions and Easyfit Professional 5.5 software, the most appropriate statistical distributions were determined using the Kolmogorov-Smirnov test, the most appropriate probability distribution function in the study area. Johnson SB statistical distribution was found to have the highest frequency in the study area; also, Log-Logistic (3P) statistical distribution is in the next rank. Then, using statistical distributions to identify indicator stations, the number of dust days in the return period was estimated from 2 to 100. The results showed that Bam, Kerman, Naein, Arak, Saveh, Mahallat, Zabol, Semnan, Qom, Zahedan, Khoor and Biabanak, Yazd and Tabas stations according to the analysis of the frequency and number of dust days estimated in the annual return period to Index station were identified in the study area. Also, changes in the spatial pattern of dust in the return periods of 5, 25 and 50 showed that the southeastern parts of the study area of Kerman, Sistan and Baluchestan provinces due to the proximity of Hamoon and Jazmourian wetlands and 120-day winds of Sistan as one of the dust centers have been identified. |
| نویسندگان مقاله |
فرشاد سلیمانی ساردو | Farshad Soleimani Sardoo
Department of Nature Sciences, Faculty of Natural Resources, University of Jiroft, Kerman, Iran
گروه مهندسی طبیعت، دانشکدهی منابع طبیعی، دانشگاه جیرفت، کرمان، ایران
طیبه مصباح زاده | Tayyebeh MesbahZadeh
Department of Rehabilitation of Arid and Mountainous Regions, Faculty of Natural Resources, University of Tehran, Karaj, Iran.
گروه احیاء مناطق خشک و کوهستانی، دانشکدهی منابع طبیعی، دانشگاه تهران، کرج، ایران
سعیده ناطقی | Saaide Nateghi
Rangeland Research Division, Research Institute of Forests and Rangelands, Agricultural Research Education and Extension Organization (AREEO), Tehran, Iran
بخش تحقیقات مرتع، مؤسسهی تحقیقات جنگلها و مراتع کشور، سازمان تحقیقات، آموزش و ترویج کشاورزی، تهران
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