تجزیه و تحلیل خطر سیل‌گیری با استفاده از روش‌ یادگیری ماشین جنگل تصادفی (مطالعۀ موردی: شهر مشهد)

نوع مقاله : پژوهشی

نویسندگان

1 دکتری آمایش محیط ‏زیست، دانشکدۀ شیلات و محیط‏ زیست، دانشگاه گرگان

2 استاد، دانشکدۀ شیلات و محیط ‏زیست، دانشگاه گرگان

3 دانشیار، دانشکدۀ شیلات و محیط‏ زیست، دانشگاه گرگان

4 دانشیار، دانشکدۀ جغرافیا، دانشگاه رن 2

چکیده

سیل از رایج‌ترین بلایای طبیعی است و خسارت‌های مالی و جانی فراوانی به جای می‏گذارد. اگرچه میزان بارندگی در بسیاری از مناطق ایران کم است، در بسیاری از مناطق، بیشترین میزان بارندگی سالانه تنها در یک روز یا مدت کوتاهی رخ می‏دهد که منجر به سیل می‏شود. آب روان در جریان سیل به دلیل ساختار زمین‌شناسی و همچنین، تخریب اکوسیستم می‏تواند بسیار آلوده باشد و اغلب گل‌و‌لای زیادی به همراه دارد که بر خسارت‌های سیل می‏افزاید. برای کاهش خسار‌ت‌های احتمالی سیل، برنامه‏ریزان و تصمیم‏گیرندگان باید از زمان و مکان وقوع سیل آگاه باشند. این امر مستلزم استفاده از روش‏های جدید پیش‏بینی سیل و جلوگیری از خسارت‏های آن است. در این مطالعه، از روش یادگیری ماشین درخت تصادفی یا Random Forest (RF) برای پیش‌بینی مکان وقوع سیل در شهر مشهد استفاده شد و عملکرد آن مورد بررسی قرار گرفت. همچنین تأثیر هر یک از عوامل ارتفاع و شیب متوسط حوضه، جهت شیب، شاخص رطوبت توپوگرافی، شاخص ‏خشکسالی، فاصله از آبراهه‏ها، زمین‏شناسی، کاربری اراضی، تراکم آبراهه‏ها، آبراهه‏ها و میزان بارش حداکثر متوسط سالانه در این پیش‏بینی مورد بررسی قرار گرفت. نتایج ارزیابی خروجی مدل RF نشان داد مقدار AUC95 درصد است. به طور کلی، نتایج نشان داد مدل RF دارای دقت زیادی در تعیین مناطق حساس به وقوع سیل در حوضۀ شهر مشهد است.

کلیدواژه‌ها

موضوعات


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دوره 10، شماره 1
فروردین 1402
صفحه 1-15
  • تاریخ دریافت: 28 اردیبهشت 1401
  • تاریخ بازنگری: 28 مرداد 1401
  • تاریخ پذیرش: 28 آذر 1401
  • تاریخ اولین انتشار: 28 آذر 1401
  • تاریخ انتشار: 10 مرداد 1402