کاهش خطای شبیه سازی فرآیند بارش-رواناب با بکارگیری تکنیک داده گواری در مدل هیدرولوژیکی SWAT

نوع مقاله: مقاله پژوهشی

نویسندگان

1 کاندیدای دکتری /دانشکده مهندسی عمران، دانشگاه صنعتی اصفهان.

2 دانشیار / دانشکده مهندسی عمران، دانشگاه صنعتی اصفهان

3 استادیار / دانشکده مهندسی عمران، دانشگاه صنعتی اصفهان

چکیده

مدلسازی فرآیند بارش-رواناب با انبوهی از پارامترها و داده های اقلیمی همراه است که ارائه یک مدل شبیه ساز مناسب با حداقل خطا از چالش های مطالعات گذشته بوده است. عدم اطمینان و قطعیت بر صحت داده ها و پارامترهای ورودی مدل های شبیه سازی منجر به تولید خطا می شود که تاثیر قابل توجهی بر پیش بینی های بلند مدت و سیاست های مدیریتی می گذارد. در این مطالعه از مدل مفهومی آب و خاک SWAT به منظور شبیه سازی فرآیند بارش-رواناب در زیر حوضه آبریز چلگرد استفاده می شود. به منظور ارائه یک مدل مناسب، تکنیک داده گواری فیلتر کالمن مجموعه ای (EnKF) جهت به روزرسانی و اصلاح منابع تولید خطا در مدلسازی به کار برده می شود که این منابع شامل پارامترها و داده های ورودی مدل می باشد. نتایج بدست آمده از مدل اصلاحی ارائه شده با معیار ارزیابی Nash-Sutcliff سنجیده شده که مدل اصلاحی با ضریب 0.86 عملکرد بهتری نسبت به مدل توسعه یافته بدون تکنیک EnKF از خود نشان می دهد و همچنین ضریب Nash-Sutcliff برای دوره صحت سنجی به 0.82 ارتقاء می یابد.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Reducing Error of Rainfall-Runoff Simulation Using Coupled Hydrological SWAT Model and Data Assimilation Technique

نویسندگان [English]

  • M. Mehrparvar 1
  • K. Asghari 2
  • M.H. Golmohammadi 3
1 Ph.D. Candidate, Department of Civil Engineering, Isfahan University of Technology, Isfahan, Iran.
2 Associate Professor, Department of Civil Engineering, Isfahan University of Technology, Isfahan, Iran.
3 Assistant Professor, Department of Civil Engineering, Isfahan University of Technology, Isfahan, Iran.
چکیده [English]

Modeling conceptual rainfall-runoff procedure involves large number of parameters and climate data. Uncertainty in these input parameters are very likely which lead to output errors as well as impractical prediction of long-term impact of management policies. In this study Soil and Water Assessment Tool (SWAT) is implemented to simulate rainfall-runoff process in Chelgerd sub-basin. To develop appropriate model with acceptable and reliable performance, Ensemble Kalman filter (EnKF) as data assimilation technique is used to assimilate the variables of model which are known as sources of error product; these sources include model parameters and input data. The paper in concluded that EnKF as a data assimilation technique is capable of reducing the computational error inherited in the simulation model. Results of proposed model is evaluated by Nash-Sutcliff (NS) factor with value of 0.86 which have better performance than modeling without EnKF technique. Also developed model performance is improved with NS value of 0.82 for validation period.

کلیدواژه‌ها [English]

  • Rainfall-Runoff
  • Ensemble Kalman filter
  • Soil and Water Assessment tool
  • Error reduction
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