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Information Journal Paper

Title

ESTIMATING PROBABILITIES OF DROUGHT AND WETPERIODS USING THE MARKOV CHAIN AND NORMAL DISTRIBUTION METHODS: CASESTUDY - GHAZVIN

Pages

  121-128

Abstract

 An increase or decrease in the precipitation intensity compared to the normal conditions may lead to a higher risk of floods or a higher probability of incidence of DROUGHT. Knowledge of the probability distribution of precipitation is essential to the management of water resources. Such knowledge can be achieved using dynamical or statistical approaches. In the present article the probabilities of different DROUGHT states (very dry, dry, semidry, normal, semi wet, wet, and very wet) are calculated based on the annual and seasonal precipitation amounts in Ghazvin using the normal distribution and MARKOV CHAIN methods. The results indicate that the probabilities of DROUGHT/wet states based on annual and seasonal precipitation data as calculated using the two methods are comparable. The statistical evaluation of the results using X2, however, reveals that the MARKOV CHAIN method is superior to the normal distribution.

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  • Cite

    APA: Copy

    YOUSEFI, NOSRAT ELAH, HAJAM, S., & IRANNEZHAD, P.. (2007). ESTIMATING PROBABILITIES OF DROUGHT AND WETPERIODS USING THE MARKOV CHAIN AND NORMAL DISTRIBUTION METHODS: CASESTUDY - GHAZVIN. GEOGRAPHICAL RESEARCH QUARTERLY, 39(60), 121-128. SID. https://sid.ir/paper/5494/en

    Vancouver: Copy

    YOUSEFI NOSRAT ELAH, HAJAM S., IRANNEZHAD P.. ESTIMATING PROBABILITIES OF DROUGHT AND WETPERIODS USING THE MARKOV CHAIN AND NORMAL DISTRIBUTION METHODS: CASESTUDY - GHAZVIN. GEOGRAPHICAL RESEARCH QUARTERLY[Internet]. 2007;39(60):121-128. Available from: https://sid.ir/paper/5494/en

    IEEE: Copy

    NOSRAT ELAH YOUSEFI, S. HAJAM, and P. IRANNEZHAD, “ESTIMATING PROBABILITIES OF DROUGHT AND WETPERIODS USING THE MARKOV CHAIN AND NORMAL DISTRIBUTION METHODS: CASESTUDY - GHAZVIN,” GEOGRAPHICAL RESEARCH QUARTERLY, vol. 39, no. 60, pp. 121–128, 2007, [Online]. Available: https://sid.ir/paper/5494/en

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