نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشجوی دکتری آبخیزداری، دانشگاه علوم کشاورزی و منابع طبیعی ساری، ایران

2 استاد گروه احیای مناطق خشک و کوهستانی، دانشکدة منابع طبیعی، دانشگاه تهران، ایران

3 استادیار گروه مهندسی آبخیزداری، دانشکدة منابع طبیعی دانشگاه تربیت مدرس، نور، ایران

4 دانشیار گروه احیای مناطق خشک و کوهستانی، دانشکدة منابع طبیعی، دانشگاه تهران، ایران

چکیده

به دلیل ناکافی‌بودن امکانات، بودجه، نیروی انسانی، زمان، و ... عملیات آبخیزداری در کل سطح حوضة آبخیز قابل اجرا نیست. به همین دلیل، عملیات آبخیزداری باید در زیرحوضه‌هایی اجرا شود که اثرگذارتر است و از نظر تخریب، فرسایش، خسارات جانی و مالی، سیلاب، و ... بیشتر در معرض خطر باشد. همچنین، نقص ایستگاه‌های هیدرومتری یا فقدان ایستگاه‌ها در برخی مناطق متخصصان را بر آن داشته تا برای اولویت‌بندی زیرحوضه‌ها به دنبال روش‌هایی باشند که با استفاده از خصوصیات در دسترس زیرحوضه‌‌ها، در مناطق مختلف جغرافیایی، به‌درستی عمل کند. در تحقیق حاضر امکان استفاده از روش‌های نروفازی و SCS در مدل HEC-HMS، که محدودة وسیعی از مزایا و معایب را می‌توانند در تصمیم‌گیری‌ها لحاظ نمایند، بررسی شد. برای تعیین صحت نتایج روش‌های مختلف، میزان دبی خروجی از زیرحوضه‌های طالقان طی یک سال آماری برداشت شد. نتایج به‌دست‌آمده از این دو روش با حداکثر دبی با دورة بازگشت دوسالة مشاهداتی زیرحوضه‌ها مقایسه شد. نتایج نشان داد بهترین اولویت‌بندی مربوط به روش نروفازی است و در مقایسه با SCS، بر اساس ضرایب خطا و تبیین مربوط به مقایسة داده‌‌های مشاهداتی و برآوردشده، بهترین برآوردها را داشته است.

کلیدواژه‌ها

عنوان مقاله [English]

Comparison of Neuro-fuzzy and SCS methods in sub-watersheds prioritization for watershed measures (Case study: Taleghan watershed)

نویسندگان [English]

  • Sadegh Tali-Khoshk 1
  • Mohsen Mohseni Saravi 2
  • Mahadi Vatakhah 3
  • Shahram Khalighi-Sigarodi 4

1 Ph. D. student in Watershed Management, Sari Agricultural and Natural Resources University, I.R. Iran

2 Professors, Faculty of Natural Resources, University of Tehran, I.R. Iran

3 Assistant professor, Faculty of Natural Resources, Tarbiat Modares University, I.R. Iran

4 Associate professor, Faculty of Natural Resources, University of Tehran, I.R. Iran

چکیده [English]

Because of insufficient factors including facilities, budget, human resources as well as time watershed operation is not applicable throughout the basin. As a result, watershed operation should be performed in the sub-basins in which is more affectionate and the risk frequency of some events such as destruction, degradation; physical and financial damage and also flooding are considerably high. In addition, due to hydrometric stations, defects or the lack of stations in some areas, some efforts have been made experts recently to assess and consequently introduce some novel and reliable methods for prioritizing on the basis of current data obtained from sub-basins features of different geographical regions. In current study, the utilization possibilities of neuro-fuzzy technique and SCS in HEC-HMS model that have different potential to examine a wide range of advantageous and disadvantageous in making various decisions were studied. To determine the prediction accuracy of these methods, the rate of flow and sediment output of Taleghan sub-basins were taken over one year. The results of these methods were then compared with the maximum two-year return period flow observations. Our results revealed that in making prioritization, neuro-fuzzy as compared with the SCS method can produce the best prediction as long as the coefficients of errors, efficiency compared to the observational data and predictions are taken into account.
 

کلیدواژه‌ها [English]

  • neuro-fuzzy
  • SCS
  • Prioritization
  • Flooding
  • Taleghan watershed

 

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