16 آذر 1400
اسماعيل عباسي

اسماعیل عباسی

مرتبه علمی: استادیار
نشانی: پژوهشکده خلیج فارس - گروه محیط زیست
تحصیلات: دکترای تخصصی / اقلیم شناسی
تلفن: 07731222230
دانشکده: پژوهشکده خلیج فارس

مشخصات پژوهش

عنوان Dust storm source detection using ANP and WRF models in southwest of Iran
نوع پژوهش مقالات در نشریات
کلیدواژه‌ها
Dust storms . Dust sources . The analytic network processes . WRF numerical model . Iran
مجله Arabian Journal of Geosciences
شناسه DOI DOI: 10.1007/s12517-021-07608-z
پژوهشگران اسماعیل عباسی (نفر اول) ، هانا اعتمادی (نفر دوم) ، جوزف اسماک (نفر سوم) ، حمید عمونیا (نفر چهارم) ، محمدحسن ماهوتچی (نفر پنجم)

چکیده

In recent years, dust storms with huge adverse impacts on the environment have become more frequent and intense in the southwest of Iran. The first step to control or influence the dust storm process is source identification. The objective of this study is to detect the major sources of dust storms in Bushehr Province of Iran using the analytic network processes (ANP) and the weather research and forecasting (WRF) models. Five synoptic stations for this purpose were examined over 17 years from 2001 to 2017. The spatial data includes land use, NDVI, slope, aspect-slope, elevation, and soil used as the major layers. The layers were weighted by applying the paired comparison and analytic hierarchy process methods. Also, local scale pressure systems were identified using the WRF numerical model. Results revealed that pressure systems at the local scale in different seasons are located exactly over areas prone to dust storm generation within the study area. Furthermore, the WRF model correctly showed the atmospheric pressure and wind field locations at a local scale. Based on ANP output, more than 25% of Bushehr Province has been active as dust-prone regions at a local scale. The ANP model identified the zones of erosion-prone areas, and the WRF model determined the location of permanent or semi-permanent pressure systems. Results demonstrated that applying the WRF and ANP models provided a useful tool to identify and validate the local dust sources with high accuracy in the study sites.