Study of the use of Markov model in studying changes in the length of dry periods in Semnan province

Document Type : Original Article

Author

ASSISTANT PROFESSOR- SEMNAN UNIVERSITY-IRAN

10.22075/ceasr.2025.37148.1042

Abstract

Knowledge of the distribution of the probability of precipitation provides a suitable basis for planning water and soil resources, as well as flood control and erosion management..

competence of the Markov chain model for estimating changes in dry days and probabilistic zoning (classification of land based on land use) has been studied and evaluated in many provinces such as Kohgiluyeh and Boyer-Ahmad provinces. In this article, the behavioral pattern of the length of dry periods was investigated using daily precipitation data for all synoptic stations in Semnan province and a number of selected climatological and rain gauge stations (1985 to 2017) using the Markov chain empirical distribution algorithm model.

The results showed that the highest frequency of long-term dry periods (30 days and more) in Semnan province was related to the Hosseinian station in the south of Damghan city. And of course, the lowest frequency was related to the stations on the border of Semnan province with Mazandaran and Golestan provinces, such as Rezvan and Mojen stations in the northwest of the province.

Based on the fact that in recent decades, the climate of Semnan province, following the climate of Iran, has been reported to be increasing in temperature, decreasing in precipitation, and increasing in drought.

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