INVESTIGATION THE OCCURRENCE PROBABILITY AND PERSISTENCE OF RAINY DAYS BY USING MARKOV CHAIN MODEL (CASE STUDY: LAMERD CITY)

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TAVANPOUR N.; GHAEMI A.A.; HONAR T.; SHIRVANI A.

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Journal: IRAN-WATER RESOURCES RESEARCH Year:2018 | Volume:14 | Issue:2 Page(s): 89-99

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Title

INVESTIGATION THE OCCURRENCE PROBABILITY AND PERSISTENCE OF RAINY DAYS BY USING MARKOV CHAIN MODEL (CASE STUDY: LAMERD CITY)

Author(s)

TAVANPOUR N. | GHAEMI A.A. | HONAR T. | SHIRVANI A. | Issue Writer Certificate

Keywords

MARKOV CHAINQ2

RAINY DAYQ2

DRY DAYQ1

PERSISTENCEQ1

RETURN PERIODQ1

Abstract

One of the primary needs of planning for the management of water resources is to predict the amount of water necessary for agricultural practices, industrial usage and municipal consumption. Accordingly, it is necessary to determine the potential of water supply in different time scales for efficient plans by appropriate and reliable methods. The probability analysis is useful methods for prediction of components such as precipitation. The MARKOV CHAIN is among these methods. MARKOV CHAIN models are a special case of models in which the current state of a system depends on its previous state. In the present study, using available records of daily rainfall for 22 years (1995-2016) of the Lamerd weather station (in Fars Province), frequencies and durations of RAINY DAYs were studied by using MARKOV CHAIN model. In this study, the period of May to October was disregarded due to the insignificant number of daily precipitation events. 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 previous studies done in Iran, only the first order of the MARKOV CHAIN was used to forecast precipitation by using the MARKOV CHAIN, which may not be in good agreement with the data and may resulted in incorrect results. But in this study, by using an accurate statistical method, the appropriate order of the MARKOV CHAIN was diagnosed to be used. Matrixes 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. It was also found that the highest probability of having RAINY DAYs occur in the months of January and March, and that precipitation in Lamerd city does not exhibit temporally homogenous distribution.

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APA: Copy

TAVANPOUR, N., GHAEMI, A.A., HONAR, T., & SHIRVANI, A.. (2018). INVESTIGATION THE OCCURRENCE PROBABILITY AND PERSISTENCE OF RAINY DAYS BY USING MARKOV CHAIN MODEL (CASE STUDY: LAMERD CITY). IRAN-WATER RESOURCES RESEARCH, 14(2 ), 89-99. SID. https://sid.ir/paper/100356/en

Vancouver: Copy

TAVANPOUR N., GHAEMI A.A., HONAR T., SHIRVANI A.. INVESTIGATION THE OCCURRENCE PROBABILITY AND PERSISTENCE OF RAINY DAYS BY USING MARKOV CHAIN MODEL (CASE STUDY: LAMERD CITY). IRAN-WATER RESOURCES RESEARCH[Internet]. 2018;14(2 ):89-99. Available from: https://sid.ir/paper/100356/en

IEEE: Copy

N. TAVANPOUR, A.A. GHAEMI, T. HONAR, and A. SHIRVANI, “INVESTIGATION THE OCCURRENCE PROBABILITY AND PERSISTENCE OF RAINY DAYS BY USING MARKOV CHAIN MODEL (CASE STUDY: LAMERD CITY),” IRAN-WATER RESOURCES RESEARCH, vol. 14, no. 2 , pp. 89–99, 2018, [Online]. Available: https://sid.ir/paper/100356/en

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