بررسی عدم قطعیت زنجیره مارکوف برای پیش بینی وضعیت هیدرولوژیک بر اساس وضعیت هواشناسی

نوع مقاله : مقاله پژوهشی

نویسندگان

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

2 استاد، گروه مهندسی آب، دانشگاه بین المللی امام خمینی (ره)، قزوین، ایران

10.22059/ijswr.2021.319712.668905

چکیده

بررسی و به کمیّت درآوردن میزان عدم قطعیت در نتایج پیش­بینی مدل­ها، مهم­ترین گام، قبل از استفاده از نتایج مدل­ها در تصمیم­گیری­های مربوط به پروژه‌های منابع آب است. در این پژوهش برای پیش­بینی وضعیت هیدرولوژیکی حوضه با توجه به میزان بارش در گام زمانی قبل، از روش زنجیره مارکوف استفاده شد. هدف مطالعه حاضر تعیین میزان عدم قطعیت پیش بینی با استفاده از باند اعتماد احتمال رخ داد وقایع در حالت‌های مختلف هواشناسی و هیدرولوژیکی می­باشد. برای ارزیابی عدم قطعیت حاصله در پیش‌بینی انجام شده به کمک ماتریس احتمال انتقال دوبعدی مارکوف، 20 دوره با وضعیت مشابه با شرایط تاریخی به روش مونت کارلو شبیه‌سازی شد. برای تعیین عدم­قطعیت در برآورد ماتریس احتمال انتقال هیدروکلیماتولوژی به­دست آمده با روش زنجیره مارکوف، روش ناپارامتریک نسبت­ها برای نمونه‌های بزرگ و روش دقیق مبتنی بر آزمون نشانه برای میانه درایه‌های ماتریس پیش بینی مورد استفاده قرار گرفت. نتایج ماتریس هیدروکلیماتولوژی برای طولانی­مدت نشان داد که شرایط هیدرولوژیک تمایل به ماندن در حالت نرمال را دارد. نتایج تحلیل عدم قطعیت نیز حاکی از آن بود که آزمون نشانه  به عنوان یک روش ناپارامتریک در ارزیابی عدم قطعیت زنجیره مارکوف بهتر عمل می‌نماید و چون محدوده احتمالات انتقال از حالات مختلف هواشناسی به هیدرولوژی برای همه ایستگاه­ها تقریباً یکسان می­باشد حوضه مورد مطالعه از نظر هواشناسی و هیدرولوژیکی حوضه­ای همگن محسوب می‌گردد.

کلیدواژه‌ها


عنوان مقاله [English]

Investigation of Markov Chain Uncertainty for Forecasting Hydrological Status Based on Meteorological Status

نویسندگان [English]

  • Fahime Razei 1
  • Alireza Shokoohi 2
1 Water Engineering Department, Faculty of Agriculture and Natural Resources, Imam Khomeini International University, Qazvin, Iran
2 Professor, Water Engineering Department, Imam Khomeini International University, Qazvin, Iran
چکیده [English]

Examining and quantifying the degree of uncertainty in the prediction results of the models is the most important step before using the results of the models in water resources decisions making. In this research, the Markov chain technique was used to predict the hydrological status of the basin according to the amount of precipitation in the previous time step. The present study aims to determine the degree of uncertainty of prediction using the confidence interval of the probability of occurrence of events in different meteorological and hydrological conditions. To assess the uncertainty of the predictions by the 2D Markov chain transfer probability matrix, 20 periods with similar characteristics to historical conditions were simulated by the Monte Carlo method. To determine the uncertainty in estimating the hydroclimatology transfer matrix components, the nonparametric method of ratios for large samples and the exact method based on the sign test for the median of the predicted matrix components were used. The results of the long-term hydroclimatology matrix showed that the hydrological conditions tended to remain normal. The results of uncertainty analysis also indicated that the sign test, as a non-parametric method, in assessing the uncertainty of the Markov Chain acts better, and because the range of probabilities of transfer from different meteorological states to hydrological states is almost the same for all stations, the study basin is considered meteorologically and hydrologically homogeneous.

کلیدواژه‌ها [English]

  • Uncertainty
  • Two-Dimensional Markov Chain
  • Monte Carlo simulation
  • Anzali wetland watershed
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