نوع مقاله: مقاله پژوهشی

نویسنده

استادیار گروه اکولوژی، پژوهشکده علوم محیطی، پژوهشگاه علوم و تکنولوژی پیشرفته و علوم محیطی، دانشگاه تحصیلات تکمیلی صنعتی و فناوری پیشرفته

چکیده

پیش­بینی جریان ورودی به مخزن سد، ابزاری اساسی در مدیریت بهینه منابع آب محسوب می­شود. ضرورت ارتقاء دقت و بازه زمانی پیش­بینی جریان، برای بخش کشاورزی که بزرگ­ترین مصرف­کننده آب محسوب می­شود، بارزتر می­باشد. در این راستا استفاده از رویکردهای احتمالاتی برای پیش­بینی­های بلند­مدت جریان و احتساب عدم قطعیت پیش­بینی، توصیه شده است. هدف تحقیق حاضر ارائه مدلی برای پیش­بینی احتمالاتی جریان ورودی به مخزن سد جیرفت می­باشد. در این راستا با استفاده از رویکرد پیش­بینی­های گروهی جریان (ESP) و نیز به­کارگیری مدل­های شبکه عصبی مصنوعی (ANNs)، سناریوهای احتمالاتی جریان یک تا دوازده ماه آینده رودخانه هلیل پیش­بینی گردید. بدین منظور با استفاده از داده­های هواشناسی و هیدرولوژیکی حوضه رودخانه هلیل­رود، پیش­بینی­های تجمعی جریان با مدل­های ANN صورت گرفت و در ادامه از این پیش­بینی­ها برای ساخت سناریوهای احتمالاتی جریان با رویکرد ESP مصنوعی استفاده شد. نتایج نشان داد، با افزایش بازه زمانی پیش­بینی، از مقیاس ماهانه تا سالانه، دقت نتایج، مقداری کاهش می­یابد. همچنین از ترکیب مدل­های ANN با رویکرد ESP مصنوعی، می­توان سناریوهای احتمالاتی جریان را بخوبی پیش­بینی نمود.

کلیدواژه‌ها

موضوعات

عنوان مقاله [English]

Probabilistic Forecasts of Streamflow Scenarios Using ESP Approach (Case study: Halil River)

نویسنده [English]

  • Sedigheh Anvari

Assistant Professor, Department of Ecology, Environmental Research Center, Institute of Science and High Technology and Environmental Science, Graduate University of Advanced Technology

چکیده [English]

Stream flow forecast is a fundamental tool that could be utilized for appropriate water resource management. The enhancement of accuracy as well as the increase of time horizon for stream flow forecasts is essential especially for agricultural sector which is the most vulnerable sector during water shortages. In this regard, the application of stochastic approaches like Ensemble Streamflow Prediction (ESP) procedure for long-term forecast with respect to streamflow uncertainty can be proposed. The ESP procedure produces streamflow forecasts in the form of multiple hydrographs, each a possible realization of seasonal streamflow (Day, 1985). One example of ensemble streamflow forecasts is the National Weather Service’s ESP procedure. Faber and Stedinger (2001) successfully combined reservoir operation models with updated information from ESP of the National Weather Service (Faber and Stedinger, 2001). Using ESP forecasts, Eum et al. (2011) also developed a procedure to calculate optimal water release curtailments during droughts using a future value function derived with a sampling stochastic dynamic programming model.
The main objective of this paper is to present a probabilistic approach and forecast the inflows to Jiroft dam reservoir. In this regards, using ESP approach as well as Artificial Neural Networks (ANNs) the 1- to 12- month ahead probabilistic scenarios of Halil river were forecasted.

کلیدواژه‌ها [English]

  • Stream flow Forecast
  • ANN
  • ESP
  • Halil River

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