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مدل‌سازی بارش – رواناب حوضه آجی‌چای با استفاده از مدل‌های جنگل تصادفی و شبکه عصبی مصنوعی

نوع مقاله : مقاله پژوهشی

نویسندگان

1 مهندسی آب، دانشکده کشاورزی، دانشگاه تبریز.

2 گروه مهندسی آب- دانشکده کشاورزی- دانشگاه تبریز - تبریز- ایران

3 گروه مهندسی آب- دانشکده کشاورزی- دانشگاه تبریز- تبریز

4 مهندسی آب ،دانشکده کشاورزی ، دانشگاه تبریز

10.22103/nrswe.2023.20278.1013

چکیده

برآورد رواناب ناشی از وقوع بارندگی، گامی بسیار مهم در برنامه‌ریزی منابع آب به ویژه در آبخیزهای فاقد ایستگاه‌های هیدرومتری است. در این مطالعه به شبیه‌سازی بارش- رواناب ایستگاه آخولا واقع در حوضه آجی‌چای پرداخته شد و با استفاده از روش‌های داده‌کاوی و مقایسه عملکرد آنها، مناسب‌ترین مدل بارش-رواناب ارائه گردید. برای این منظور داده‌های مورد نظر (بارش، دبی، دما) بصورت ماهانه از سازمان‌های آب و هواشناسی استان‌های آذربایجان شرقی و غربی دریافت گردید. جهت شبیه‌سازی از مدل‌های داده‌کاوی جنگل تصادفی و شبکه عصبی مصنوعی استفاده گردید. مقایسه مقادیر رواناب ماهانه مشاهداتی با رواناب ماهانه تخمین زده شده توسط مدل‌ها با استفاده از معیارهای ارزیابی انجام شد. در این مطالعه مقادیر CC (ضریب همبستگی) برای مجموعه‌های تست در مدل جنگل تصادفی و شبکه عصبی مصنوعی به ترتیب برابر با 82/0و 86/0 تعیین گردید. تحلیل‌ نتایج نشان داد که برای ایستگاه آخولا مدل ANN عملکرد و کارایی بالاتری نسبت به مدل RF دارد. از نتایج دیگر این پژوهش می‌توان به سری زمانی بارش و رواناب ایستگاه طی 20 سال اخیر اشاره کرد. با توجه به تحلیل روند من-کندال، در طی این 20 سال روند مشخصی برای بارش بر روی حوضه آجی‌چای دیده نشد و نمودارهای سری زمانی نشان داد که بارش در این مناطق بصورت نوسانی بوده است. اما سری زمانی برای دبی آجی‌چای در ایستگاه آخولا، نشان داد که روند کاملاً نزولی برای جریان آب رودخانه ثبت شده است که در واقع دلیل کاهش دبی ورودی به دریاچه ارومیه و پایین آمدن تراز آب دریاچه می‌باشد.

کلیدواژه‌ها

عنوان مقاله [English]

Rainfall-Runoff Modeling of Aji Chai Basin Using Random Forest and Artificial Neural Network Models

نویسندگان [English]

  • Zeinab Bigdeli 1
  • Abolfazl Majnooni Heris 2
  • Reza Delirhasannia 3
  • Sepide Karimi 4

1 Water department, Agriculture college Tabriz University

2 Water department - Agriculture College - Tabriz University- Tabriz

3 Water department- Agriculture College- Tabriz University - Tabriz.

4 Water department, Agriculture college , Tabriz University.

چکیده [English]

Estimating runoff due to rainfall is a very important step in planning water resources, especially in watersheds without hydrometric stations. In this study, the rainfall-runoff simulation of Akhola station located in the Ajichai basin was discussed and the most suitable rainfall-runoff model was presented by using data mining methods and comparing their performance. For this purpose, the desired data (rainfall, discharge, temperature) for this study were received monthly from the water and meteorological organizations of the East and West Azerbaijan provinces. Random Forest and Artificial Neural Network data mining models were used for simulation. The comparison of observed monthly runoff values with monthly runoff estimated by models was done using evaluation criteria. In this study, CC values ​​(correlation coefficient) for test sets in the random forest model and artificial neural network were determined as 0.77 and 0.86, respectively. The analysis of the results showed that the ANN model has a higher performance and efficiency than the RF model for the Akhola station. Among other results of this research, we can mention the time series of rainfall and runoff of the station during the last 20 years. According to the obtained graphs, during these 20 years, there was no clear trend for precipitation in the Ajichai basin, and the time series graphs showed that the precipitation in these areas was fluctuating. But the time series for Ajichai discharge at Akhula station showed that a completely downward trend was recorded for the river water flow, which is the reason for the decrease of the discharge entering Lake Urmia and the lowering of the lake water level.

کلیدواژه‌ها [English]

  • Rainfall-Runoff
  • Random Forest
  • Aji Chai Basin
  • Modeling
  • Machine Learning
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پژوهش های نوین در مهندسی آب پایدار
دوره 1، شماره 2 - شماره پیاپی 2
اسفند 1401
صفحه 27-42
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  • تاریخ دریافت: 31 شهریور 1401
  • تاریخ بازنگری: 26 دی 1401
  • تاریخ پذیرش: 24 اسفند 1401
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