مدل شبکه های بیزین برای بررسی تأثیر بارش پیشین بر پیش بینی وقوع سیلاب واریزه‌ای در ناحیه البرز ایران

نوع مقاله: مقاله پژوهشی

نویسندگان

1 دانشجوی کارشناسی ارشد /سازه های آبی، پردیس ابوریحان، دانشگاه تهران

2 دانشیار /گروه مهندسی آبیاری زهکشی، دانشگاه تهران، پردیس ابوریحان

3 استادیار/گروه مهندسی آبیاری زهکشی، دانشگاه تهران، پردیس ابوریحان

چکیده

تحلیل خطر سیلاب واریزه‌ای، به علت پیچیدگی و عدم قطعیت عوامل مختلف مربوط به آن، یک موضوع چالش برانگیز است. در تحقیق حاضر، اثر بارش پیشین بر رخداد سیلاب واریزه‌ای با استفاده از مدل بیزین در ناحیه البرز ایران ارزیابی شده است. در این مدل از متوسط ارتفاع، شیب حوضه، مساحت، بارش فعلی، بارش پیشین (به مدت 3 روز قبل از وقوع سیلاب واریزه‌ای) و دبی جریان 1 روز قبل، استفاده شده است. 6 سناریو شامل مقدار بارش پیشین 3 روز قبل به صورت مجزا، بارش پیشین 2 روز قبل به صورت مجزا، بارش پیشین 1 روز قبل، مقدار تجمعی بارش پیشین 3 روز قبل، مقدار تجمعی بارش پیشین 2 روز قبل و حذف اثر بارش پیشین در نظر گرفته شد. نتایج نشان داد، دقت مدل در حالت بارش پیشین مجزا، 13 درصد نسبت به حالت بارش پیشین تجمعی بیشتر است و بالاترین دقت مدل به ازای سناریو بارش پیشین 3 روز قبل به صورت مجزا، معادل 91 درصد برآورد شد. هم‌چنین، حذف اثر هر یک از بارش پیشین از ورودی مدل باعث افت عملکرد آن می‌شود. مدل پیشنهادی این تحقیق، قادر به ارائه نتایج قابل اعتماد برای سیستم‌های هشدار خطر سیلاب واریزه‌ای در حوضه های آبریز می‌باشد.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Bayesian Network Model for the Assessment of the Effect of Antecedent Rainfall on Debris Flow Forecasting In Alborz Zone of Iran

نویسندگان [English]

  • M. Tanhapour 1
  • M. E. Banihabib 2
  • A. Roozbahany 3
1 M.Sc. Student, Hydraulic Structures, College of Abouraihan, University of Tehran, Tehran, Iran
2 Associate Professor, Department of Irrigation and Drainage Engineering, College of Abouraihan, University of Tehran, Tehran, Iran.
3 Assistant Professor, Department of Irrigation and Drainage Engineering, College of Abouraihan, University of Tehran, Tehran, Iran
چکیده [English]

Comprehensive assessment of debris flow hazards is a challenging issue due to the complexity and uncertainty of its factors. In this paper, the effect of antecedent rainfall (AR) on the debris flow occurrence was assessed by using of Bayesian networks (BN) in Alborz Zone, Iran. In this model, the effect of factors such as average basin height, average basin slope, watershed area, the current rainfall, AR (three days ago) and discharge one-day ago have been used as the model’s input. Six scenarios including the amounts of AR three days ago separately, AR two days ago separately, AR one day ago, cumulative rainfall of AR three days ago, cumulative rainfall of AR two days ago and the effect of excluding AR were considered. The results indicated the performance of BN model in the first case, 13% more than the second, and highest accuracy of the model was computed by the scenario of AR 3 days ago separately with a forecasting accuracy of 91%. Furthermore, excluding the effect of any of the events AR from the model causes reduction of its performance. The proposed model is able to provide reliable results in warning systems of debris flow hazards in watersheds.

کلیدواژه‌ها [English]

  • Antecedent rainfall
  • debris Bayesian network
  • flow
  • Uncertainty
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