کاربرد مدلهای شبکه عصبی مصنوعی، نسبت فراوانی و تابع شواهد قطعی در تهیه نقشه حساسیت به وقوع سیل در حوزه آبخیز هراز: الگویی برای مطالعات مخاطرات سیلاب شهری
الموضوعات :
فصلنامه علمی و پژوهشی پژوهش و برنامه ریزی شهری
هیمن شهابی
1
(گروه ژئومورفولوژی، دانشکده منابع طبیعی، دانشگاه کردستان، سنندج، ایران)
تاريخ الإرسال : 24 الأحد , رمضان, 1441
تاريخ التأكيد : 12 الجمعة , ذو القعدة, 1441
تاريخ الإصدار : 13 الجمعة , ذو الحجة, 1442
الکلمات المفتاحية:
شبکه عصبی مصنوعی,
داده‌کاوی,
تابع شواهد قطعی,
نسبت فراوانی,
مخاطرات سیلاب شهری,
ملخص المقالة :
در این تحقیق برای تهیه نقشه حساسیت به وقوع سیل در حوزه آبخیز هراز در استان مازندران از روشهای شبکه عصبی مصنوعی (ANN)، نسبت فراوانی (FR) و تابع شواهد قطعی (EBF) استفاده شده است و برای دستیابی به هدف پژوهش از ده پارامتر موثر در وقوع سیلاب از قبیل شیب، انحنای زمین، فاصله از رودخانه، طبقات ارتفاعی، بارش، شاخص توان رودخانه (SPI)، شاخص رطوبت توپوگرافی (TWI)، لیتولوژی، کاربری اراضی و شاخص تفرق پوشش گیاهی (NDVI) استفاده گردید. همچنین، موقعیت جغرافیایی 211 نقطه سیلگیر در منطقه تهیه شده و نقاط به صورت تصادفی به گروههایی متشکل از 151 نقطه (70%) و 60 نقطه (30%) بهترتیب برای واسنجی و اعتبارسنجی تقسیم شدهاند. سپس احتمال رخداد سیل برای هر کلاس از هر پارامتر محاسبه گردید. وزنهای محاسبه شده برای هر کلاس در سیستم اطلاعات جغرافیایی در لایههای مربوطه اعمالگردیده و نقشههای حساسیت به وقوع سیل منطقه مورد مطالعه بهدست آمد. براساس نقشه پتانسیل سیلخیزی، منطقه به 5 کلاس با حساسیت خیلی زیاد، زیاد، متوسط، کم و خیلی کم تقسیم گردید. روشهای مذکور توسط روش منحنی مشخصه عملکرد سیستم (AUC) ارزیابی شدند. نتایج حاکی از آن است که طبقات ارتفاعی پایین و نزدیک رودخانه دارای احتمال و حساسیت بالایی نسبت به وقوع سیل میباشند. همچنین نتایج نشان داد که تکنیک نسبت فراوانی (AUC=0.97)، تابع شواهد قطعی (AUC=0.94) و شبکه عصبی مصنوعی (AUC=0.87) بهترتیب اولویت، دارای بیشترین دقت در پیشبینی وقوع سیل بودهاند. از اینرو مدلهای مذکور به منظور پیشبینی پتانسیل خطر سیل بهویژه در نواحی مختلف از جمله فضاهای شهری به دلیل کارایی بالا، میتواند مفید و قابل اعتماد باشند.
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