Analysis of drought and wet season in Guilan province using SPI relationship and Markov chain model

Abstract

Drought is an urgent environmental issue. Therefore, recognizing its characteristics is of great importance. The most common drought monitoring tool is the Drought Index. The SPI index is a well-known indicator of drought monitoring because of its simplicity, versatility and applicability in any type of climate. In order to investigate the dry matter and estimate its occurrence probability in Rasht city, which is located in the most rainy part of Iran, the time series of SPI were used in combination with Markov chain and the continuity, severity and frequency of dry and wet periods for the period 12.6.3 and 24 months old. The probability of equilibrium in each of the dry and wet conditions and the normal and the expected average expected drought and mildew were predicted, together with the average duration of its duration for different periods. The results showed that the drought share of mild droughts in all periods and droughts Severe is more than 6 months longer. Drought is the highest in the 3rd and 6th month period and is the lowest in the 24-month period. The continuation of drought is greater in the 12 and 24-month intervals, and the probability of transition from one state to another is increased in a longer time series. The probability of equilibrium is more than drought. The SPI profile matches the results of the Markov chain, so combining these two, while improving our ability to evaluate drought monitoring, increases the efficiency of the management system and resource planning.