مدل‌سازی بارش- رواناب آبخیزهای مناطق ساحلی در نزدیکی تنگه هرمز با استفاده از روش‌های داده‌کاوی

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشجوی دکتری علوم و مهندسی آبخیزداری-آب، دانشکده کشاورزی و منابع طبیعی، دانشگاه هرمزگان، بندرعباس، ایران

2 دانشیار بازنشسته گروه مهندسی منابع طبیعی، دانشکده کشاورزی و منابع طبیعی، دانشگاه هرمزگان،بندرعباس،

3 دانشیار گروه مهندسی منابع طبیعی، دانشکده کشاورزی و منابع طبیعی، دانشگاه هرمزگان،بندرعباس، ایران

4 دانشیار گروه علوم و مهندسی آب، دانشکده کشاورزی و منابع طبیعی، دانشگاه بین المللی امام خمینی( ره )، قزوین، ایران

5 استاد بخش مهندسی آب، دانشکده کشاورزی، دانشگاه شیراز، شیراز، ایران

چکیده

برآورد رواناب ناشی از وقوع بارندگی، گامی بسیار مهم در برنامه‌ریزی منابع آب به­ویژه در آبخیزهای فاقد ایستگاه­های هیدرومتری است. بنابراین پژوهش در ارتباط با مدل‌هایی که بتواند در این حوضه‌ها و با کمترین خطا، جریان رودخانه را شبیه‌سازی نمایند یک ضرورت اجتناب‌ناپذیر است. در این مطالعه به شبیه‌سازی بارش- رواناب آبخیز سد استقلال میناب با استفاده از روش‌های داده‌کاوی و مقایسه عملکرد آنها و ارائه مناسب‌ترین مدل بارش- رواناب برای این منطقه پرداخته شد. برای این منظور از هشت مدل داده­کاوی شامل الگوریتم جنگل تصادفی، ماشین بردار پشتیبان، شبکه عصبی مصنوعی، مدل الگوریتم‌های ارتقای شدید گرادیان، مدل درختی M5، مدل اسپلاین چند متغیره رگرسیون انطباقی، مدل فرایند گوسی، مدل بیزی جمعی رگرسیون درختی استفاده گردید. به‌منظور ارزیابی مدل‌های مورداستفاده در این تحقیق از معیارهای ارزیابی ضریب تعیین، ریشه میانگین مربعات خطا و میانگین خطای مطلق و همچنین نمودار تیلور استفاده شده است . نتایج  نشان داد که  مدل اسپلاین چند متغیره رگرسیون انطباقی، بهترین عملکرد را در بین مدل‌ها برای شبیه‌سازی دبی ماهانه آبخیز مورد مطالعه داشته است. مدل ماشین بردار پشتیبان نیز با مقدار خطای جذر میانگین مربعات (RSME) برابر 73/7 مترمکعب در ثانیه عملکرد مناسبی داشته است. بقیه مدل‌ها نیز عملکرد نسبتاً نزدیک به هم داشته‌اند، به‌طوری‌که مدل الگوریتم‌های ارتقای شدید گرادیان با مقدار 98/9 مترمکعب در ثانیه بالاترین و مدل اسپلاین چند متغیره رگرسیون انطباقی با مقدار 7/7 مترمکعب در ثانیه کمترین مقدار RMSE را داشته‌اند. در ادامه با وارد نمودن مقادیر دمای سطح دریا خلیج فارس (PGSST) به فرایند شبیه‌سازی به بررسی اثر این پارامتر بر نتایج شبیه‌سازی پرداخته شد. نتایج نشان داد که مقادیر PGSST موجب بهبود نتایج شبیه‌سازی رواناب در منطقه مورد مطالعه نگردید.

کلیدواژه‌ها


عنوان مقاله [English]

Rainfall-runoff Modelling of Coastal Watersheds near Hormuz Strait Using Data Mining

نویسندگان [English]

  • Mojtaba Mohammadi 1
  • Hassan Vagharfard 2
  • Rasool Mahdavi Najafabadi 3
  • Peyman Daneshkar Arasteh 4
  • Mohammad Jafar Nazemosadat 5
1 PhD Student, Department of Natural Resources Engineering, University of Hormozgan, Bandar-Abbas, Hormozgan, Iran
2 - Associate Professor, Department of Natural Resources Engineering, University of Hormozgan, Bandar-Abbas, Hormozgan, Iran
3 Associate Professor, Department of Natural Resources Engineering, University of Hormozgan, Bandar-Abbas, Hormozgan, Iran
4 Associate Professor, Water Sciences and Engineering Department, Faculty of Agriculture and Natural Resources, Imam Khomeini International University, Qazvin, Iran
5 Professor, Water Engineering Department, College of Agriculture, Shiraz University, Shiraz, Iran
چکیده [English]

Estimating runoff created by rainfall is a very important step in water resources planning, especially in ungauged River Basins. Therefore, research on models simulating the river flow with minimum error in the river basins is necessary. In this study, rainfall-runoff simulation of Minab watershed was done using data mining methods and their performance was compared to present the proper one. For this purpose, eight data mining algorithms including Model Tree (MT), Random Forest (RF), Support Vector Machines (SVM), Bayesian Ridge Regression (BRR), Gaussian Process (GP), Extreme Gradient Boosting (XGB), Artificial Neural Network (ANN), and Multivariate Adaptive Regression Splines (MARS) were used. Coefficient of determination (R2), root mean square error (RMSE), mean absolute error (MAE) and Taylor diagram were used to evaluate the model performance. The results indicated that the MARS model had the best performance among the all models to simulate the monthly discharge of the Minab watershed. Also, the SVM model with (RSME =7.73) has a good performance. The other models also performed relatively close to each other (The XGB model with 9.98 had the highest and the MARS model with 7.7 had the lowest RMSE). Then, by entering the values of sea level temperature (PGSST) in the simulation process, the effect of this parameter on the simulation results was investigated. The results showed that PGSST values did not improve the runoff simulation results in the study area.

کلیدواژه‌ها [English]

  • Rainfall-Runoff
  • Data mining
  • Minab watershed
  • Sea Surface Temperature
  • Persian Gulf
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