دوره 8، شماره 15 - ( بهار و تابستان 1396 )                   جلد 8 شماره 15 صفحات 235-249 | برگشت به فهرست نسخه ها


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Uncertainty Estimation of HEC-HMS Flood Simulation Model using Markov Chain Monte Carlo Algorithm. jwmr. 2017; 8 (15) :235-249
URL: http://jwmr.sanru.ac.ir/article-1-859-fa.html
نورعلی مه روز، قهرمان بیژن، پوررضا بیلندی محسن، داوری کامران. تخمین عدم قطعیت مدل شبیه سازی سیلاب HEC-HMS با استفاده از الگوریتم مونت کارلو زنجیره مارکوف. پ‍‍ژوهشنامه مديريت حوزه آبخيز. 1396; 8 (15) :235-249

URL: http://jwmr.sanru.ac.ir/article-1-859-fa.html


چکیده:   (2595 مشاهده)
مدل­های هیدرولوژیکی اغلب شامل پارامترهایی هستند که به­طور مستقیم نمی­توانند اندازه­گیری شوند. تخمین پارامترها توسط روش­ها و الگوریتم­های مختلف بهینه­سازی هم با خطا همراه است. بنابراین تجزیه و تحلیل عدم قطعیت امری ضروری به­شمار
می­آید. در تحقیق حاضر از الگوریتم
DREAM-ZS (از الگوریتم­های مبتنی بر مونت کارلو زنجیره مارکوف) به­منظور بررسی عدم قطعیت پارامترهای مدل­هیدرولوژیکی HEC-HMS در حوزه­ آبخیز تمر به مساحت 1530 کیلومتر­مربع واقع در استان گلستان استفاده شد. به منظور ارزیابی عدم قطعیت 24 پارامتر بکار رفته درمدل HEC-HMS، سه رویداد سیل برای واسنجی و یک رویداد سیل در اعتباریابی استفاده گردید. نتایج حاصل از واسنجی نشان داد که بازه­های 95 درصد عدم قطعیت کل، بیشتر داده­های مشاهده­ای بویژه دبی اوج را در برگرفتند. همچنین علاوه بر عدم قطعیت ناشی از پارامترهای مدل بارش رواناب، منابع دیگر عدم قطعیت مانند ساختار مدل و داده­های ورودی هم سهم مهمی در خطای شبیه­سازی دارند. با مشاهده مقادیر پایین ضریب تغییرات برای پارامتر CN (شماره منحنی) در تمامی سیلاب­ها، این پارامتر به­عنوان حساس­ترین پارامتر به­حساب آمد. هیستوگرام­های پسین پارامترها نشان داد که بیشتر پارامترها به­خوبی تعیین شده­اند و ناحیه کوچکی از توزیع­های یکنواخت پیشین را اشغال می­کنند. همچنین بهترین شبیه­سازی حاصل از اجرای الگوریتم عدم قطعیت DREAM-ZS آشکارا بر شبیه سازی حاصل از الگوریتم جستجوی خودکار نلدر و مید  برتری داشت.
متن کامل [PDF 6329 kb]   (2462 دریافت)    
نوع مطالعه: پژوهشي | موضوع مقاله: تخصصي
دریافت: 1396/6/28 | ویرایش نهایی: 1396/7/3 | پذیرش: 1396/6/28 | انتشار: 1396/6/28

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