ارزیابی کارایی شبکه عصبی پرسپترونی چندلایه در پیش‌نگری طوفان‌های گردوغبار برخی ایستگاه‌های سواحل خلیج فارس (آبادان، اهواز و بوشهر)

جغرافیا و مخاطرات محیطی

دوره 14، شماره 2 - شماره پیاپی 54، تیر 1404، صفحه 21-44   

نوع مقاله: مقاله پژوهشی

شناسه دیجیتال (DOI): 10.22067/geoeh.2025.91013.1531

نویسندگان

فاطمه وطن پرست قلعه‌جوق¹؛ برومند صلاحی^{* 2}

¹دانشجوی دکتری آب و هواشناسی، گروه جغرافیای طبیعی، دانشکده علوم اجتماعی، دانشگاه محقق اردبیلی، اردبیل، ایران،

²استاد آب و هواشناسی، گروه جغرافیای طبیعی، دانشکده علوم اجتماعی، دانشگاه محقق اردبیلی، اردبیل، ایران.

چکیده

تغییرات اقلیمی و به دنبال آن رخداد وقایع حدی نظیر طوفان‌های گردوغبار علاوه بر اختلال در محیط‌زیست، تأثیر مستقیم بر سلامت انسان و روند طبیعی زندگی داشته و طی سال‌های اخیر در بخش کشاورزی پیامدهای نامطلوبی را بر جای گذاشته است. در این پژوهش برای پیش‌نگری و مدل‌سازی طوفان‌های گردوغبار، داده‌های ساعتی گردوغبار، میانگین دما، رطوبت نسبی، سرعت و جهت باد در برخی از ایستگاه‌های سواحل خلیج‌ فارس (آبادان، اهواز و بوشهر) با طول دوره آماری ۳۷ سال (۲۰۲۳-۱۹۸۷) گردآوری شد. پیش‌نگری تعداد روزهای همراه با طوفان‌های گردوغبار در مقیاس فصلی با استفاده از مدل‌ شبکه عصبی پرسپترون چندلایه و مدل فصلی SARIMA انجام شد. براساس نتایج حاصل از شبکه عصبی پرسپترون چندلایه، ضریب همبستگی بین مقادیر مشاهداتی و پیش‌نگری شده برای سه ایستگاه همدیدی آبادان، اهواز و بوشهر به ترتیب برابر با ۴۳/۰، ۵۰/۰ و ۹۰/۰ و مقدار RMSE برابر با ۹۶/۶، ۹۷/۱ و ۱۶/۰ بوده و نسبت به مدل SARIMA خطای کمتر، همبستگی بیشتر و عملکرد بهتری در پیش‌نگری داشته است. پیش‌نگری با شبکه عصبی برای ۱۶ سال آینده (۲۰۴۰-۲۰۲۴) بیشترین احتمال رخداد گردوغبار را در فصل بهار و کمترین مقدار را برای پاییز نشان داد. شدت گردوغبار نیز طی دوره‌های مشاهداتی و آینده در آبادان بیشتر از بقیه ایستگاه‌ها بوده است. مسیریابی ذرات گردوغبار با مدل HYSPLIT و  به­روش پسگرد در سه ارتفاع ۲۰۰، ۱۰۰۰ و ۱۵۰۰ متری، ایجاد ذرات گردوغبار در عراق، قسمت‌هایی از سوریه و عربستان و حرکت آن به سمت غرب و جنوب­ غرب ایران را برای تاریخ‌های مشترک در سه ایستگاه تصدیق می‌کند و نتایج آن مطابقت خوبی را با عمق اپتیکی گردوغبار، تراکم گردوغبار سطحی و نحوه حرکت توده غلظت بر اساس مدل‌های NAAPS و COAMPS نمایش می‌دهد. نتایج این مطالعه می‌تواند در مدیریت پیامدهای ناشی از طوفان گردوغبار و برنامه‌های مقابله با بیابان‌زایی در مناطق تحت مطالعه مؤثر باشد.  

کلیدواژه‌ها

پیش‌بینی طوفان گردوغبار؛ شبکه عصبی پرسپترون چندلایه؛ مدل SARIMA؛ مدل مسیر‌یابی HYSPLIT؛ اقلیم سواحل خلیج فارس

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