بررسی عدم قطعیت ناشی از پیچیدگی مدل‌های ستون تجربی انتقال آلاینده از دیدگاه محلی و منطقه‌ای

نوع مقاله: مقاله پژوهشی

نویسندگان

1 دانشجوی دکتری هیدروژئولوژی/گروه علوم زمین دانشگاه تبریز. تبریز. ایران

2 دکتری هیدروژئولوژی/ استاد /گروه علوم زمین دانشگاه تبریز. تبریز. ایران

چکیده

شناسایی پیچیدگی در مدل‌های جایگزین ستون تجربی انتقال آلاینده منجر به انتخاب مدل بهینه و بهترین برآورد از پارامتر می‌گردد و از عدم قطعیت ناشی از پیچیدگی و نتایج غیر صحیح جلوگیری می‌نماید. در این مطالعه جهت بررسی عدم قطعیت ناشی از پیچیدگی در مدل‌های ستون تجربی چهار مدل مفهومی مختلف با درجه های پیچیدگی متفاوت شامل: مدل‌های تعادلی کانوکشن-دیسپرژن، CDE1 (ساده‌ترین مدل با یک پارامتر) و CDE2 ، مدل‌های غیر تعادلی متحرک- غیر متحرک، MIM1 و MIM2(پیچیده‌ترین مدل با چهار پارامتر)، با دو وضعیت سرعت جریان بالا q36.7 و سرعت جریان پایین q2.71 از منابع استفاده گردیده است. آنالیز مدل‌های جایگزین ستون تجربی از طریق چهار روش: 1- امتیازدهی به مدل ها بر اساس RMSE . 2- ارزیابی احتمال مدل‌های جایگزین از طریق روش معیارهای انتخاب مدل( AIC، AICC، BIC و KIC) 3- ارزیابی احتمالات مدل از طریق میانگین حسابی یا AME با روش مونت کارلو و 4- روش برآورد احتمالات مدل از طریق میانگین هارمونیک یا HME از طریق زنجیره مارکوف مونت کارلو ( MCMC) دارای یک توسعه تدریجی از دیدگاه محلی به سمت دیدگاه منطقه‌ای می‌باشد. نتایج نهایی در ارزیابی مدل‌ها نشان می‌دهد که امتیاز بندی مدل‌ها در روش‌های محلی با روش‌های منطقه‌ای متفاوت هستند. در یک نتیجه گیری کلی پیچیدگی در وضعیت سرعت جریان بالا تا حد مدل MIM1 و در وضعیت سرعت جریان پایین تا حد مدل CDE2 کافی می‌باشد و پیچیده کردن مدل‌های انتقال بیشتر از این حد منجر به افزایش عدم قطعیت مدل می‌گردد.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Exploring Uncertainty Caused by Model Complexity in Column Experiments from Local and Global Perspectives

نویسندگان [English]

  • S Samani 1
  • A Asghari Moghaddam 2
1 Ph.D Student of Hydrogeology, Geology Department, University of Tabriz , Tabriz, Iran
2 Ph.D in Hydrogeology, Professor, Geology Department, University of Tabriz, Tabriz, Iran
چکیده [English]

Considering the complexity of contaminant transport models in column experiments, can aid selection of an optimal model and best estimation of model parameters, avoid over parameterization, model uncertainty and incorrect conclusions. We consider tow experiment with high flow velocity (q36.7) and low flow velocity (q2.71) with four models of different levels of complexity, including the equilibrium and non-equilibrium convection dispersion models. Consists of the convection-dispersion models CDE1 (The simplest model with one parameter) and CDE2, and mobile-immobile models MIM1 and MIM2 (the most complex model with four parameters). Through analysis of column experiments, we can view the four approaches: 1- ranking the models based on the RMSE, 2- Evaluate model probability through model selection criteria (AIC, AICc, BIC, and KIC statistics). 3- Evaluate model probability using the arithmetic mean estimated using the Monte Carlo method, and 4- Evaluate model probability using the harmonic mean estimated using the Markov chain Monte Carlo method as a gradual expansion from the local to the global scale of model parameters. The final result is showing that, evaluation of model probability change from local to global scale of model parameters. In a general conclusion, degree of complexity for high flow case to the extent MIM1 and for low flow case to the CDE2 model is enough to avoid uncertainty from over parameterization.

کلیدواژه‌ها [English]

  • 'Model complexity'
  • 'Model uncertainty'
  • 'Column experiment'
  • 'Contaminant transport model'
  • 'Local and global Perspectives'
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