Analysis of Frost-Free and Freeze days based on First-Order Markov Chain Probability Model (Case Study: of Hamedan and Malayer Synoptic Stations)

Document Type : Research Paper

Authors

1 Ph.D. Student, Water Res. Engr., Dept. of Science and Water Engr., Faculty of Agric., Bu-Ali Sina University, Hamedan, Iran

2 Prof., Water Res. Engr., Dept. of Science and Water Engr., Faculty of Agric., Bu-Ali Sina University, Hamedan,Iran

Abstract

This study tries to analyze the consecutive frost-free and freeze day’s occurance probabilities, in Hamedan and Malayer Synoptic stations using first-order two-state Markov Chain method. The analysis was performed for the minimum daily temperature data during the October to March in the period of 2000-2014. The data were arranged according to frequency matrix of the freeze and frost-free days mode change and the elements of probability matrix were calculated by the maximum likelihood method. In addition, the initial and consecutive probabilities of the frost-free and freeze periods were also calculated. Based on the results, the number of observed periods with 2 consecutive frost-free days at Hamedan and Malayer synoptic stations were 860 and 1199, respectively. In the same order the occurrences numbers of frost-free days after freezing days at the same stations were also 235 and 246, respectively. Accordingly, 235 and 246 freezing days were occurred after frost-free event and also, 1400 and 1039 periods of 2 consecutive freeze days were detected at Hamedan and Malayer stations, respectively. The average probability percentages of the consecutive freeze periods were 81.06 and 76.73 for the Hamedan and Malayer stations, respectively. The average probability percent of freeze days were 60.11 and 46.99 in the studied stations, respectively. Also, probability percentages for freezing duration of 2-5 days showed that the average probability percentages of the consecutive days were equal to 50.9, 43.73, 37.67 and 32.78 in Hamadan station and 37.82, 30.72, 25.25 and 20.99 in Malayer station, respectively. So the results can be used to predict and prevent potential damage, since the low temperatures have a detrimental effect on agricultural production.

Keywords

References

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Water and Soil Science
Volume 29, Issue 2
September 2019
Pages 213-224

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