بررسی احتمال وقوع و تداوم روزهای بارانی با استفاده از مدل زنجیره ی مارکوف (مطالعه ی موردی شهر لامرد)

نوع مقاله: مقاله پژوهشی

نویسندگان

1 دانشجوی دکتری علوم و مهندسی آب دانشگاه شیراز

2 دانشیار بخش مهندسی آب، دانشکدة کشاورزی، دانشگاه شیراز

چکیده

در پژوهش حاضر، با استفاده از آمار موجود بارش روزانه مربوط به 22 سال (1995-2016) ایستگاه هواشناسی شهر لامرد (واقع در استان فارس)، تواتر و تداوم روزهای بارانی در این شهر با استفاده از مدل زنجیرة مارکوف مورد مطالعه قرار گرفت. در این مطالعه، به دلیل ناچیز بودن تعداد بارش روزانه در ماه های مه تا اکتبر، از این ماه‌ها صرفنظر شد. داده‌های بارش روزانه براساس ماتریس فراوانی تغییر حالات رخداد روزهای خشک و بارانی مرتب شده و ماتریس انتقال بر اساس روش حداکثر درستنمایی محاسبه گردید. در تحقیقاتی که در ایران جهت پیش‌بینی بارش با استفاده از زنجیرة مارکوف صورت گرفته، تنها از زنجیرة مارکوف مرتبة اول استفاده شده که چه بسا همخوانی مناسبی با داده‌ها نداشته و نتایج نادرستی را ارائه داده است. اما در تحقیق حاضر، با روش‌های آماری دقیق، مرتبة مناسب زنجیرة مارکوف، تشخیص داده شده و به کار گرفته شد. ماتریس‌های احتمال ایستا و دورة بازگشت تداوم روزهای بارانی 2 تا 5 روزه برای ماه‌های مذکور محاسبه گردید. نتایج نشان داد که احتمال وقوع بارش در هر روز 126/0 و احتمال عدم وقوع بارش 874/0 است. جهت اعتبارسنجی نتایج، پیش‌بینی‌های کوتاه‌مدت و بلندمدت بدست آمده را با نتایج واقعی ماه‌های ژانویه، فوریه و مارس سال 2017 میلادی با استفاده از آزمون‌های متداول برابری درصدها مورد مقایسه قرار گرفت که این نتایج آزمون‌ها نشان می دهد که پیش‌بینی‌ها قویا مورد تایید قرار می‌گیرند.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Investigation of Probability of Occurrence and Persistence of Rainy Days by Using Markov Chain Model (Case Study: Lamerd City)

نویسندگان [English]

  • Nima Tavanpour 1
  • Ali Asghar Ghaemi 2
  • Tooraj Honar 2
  • Amin Shirvani 2
1 Ph.D. Candidate in Water Engineering Department, Faculty of Agriculture, Shiraz University
2 Associate Professor, Department of Water Engineering, Faculty of Agriculture, Shiraz University
چکیده [English]

In the present study, using available records of daily rainfall of 22 years (1995-2016) of the Lamerd (Fars Province) weather station, frequencies and durations of rainy days were studied by using the Markov chain model. In this study, the months of May to October were disregarded due to the insignificant number of daily precipitations. The daily rainfall data were arranged based on the transition matrix of occurrence of dry and wet days, while the transition matrix was calculated based on the maximum likelihood method. In all studies done in Iran, in order to forecast precipitation by using the Markov chain, only the first order of the Markov chain was used which may not be in good agreement with data and resulted to incorrect results. But in this study, by using an accurate statistical method, the appropriate order of the Markov chain was diagnosed to be used. Matrices of stationary probability and the return periods of rainy days for 2 to 5-day precipitations were determined for the studied months in this research. The results showed that the probability of precipitation per day is 0.126, and the probability of absence of precipitation is 0.874.

کلیدواژه‌ها [English]

  • Markov chain
  • Rainy day
  • Dry day
  • Persistence
  • Return period

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