Application of ARIMA time series models for forecasting meteorological drought in Tehran province

Today, water resources have become one of the major concerns in arid and semi-arid regions of the world. Low rainfall and its irregular distribution in Iran, along with rapid population growth and increased agricultural activities, have caused recent droughts. The present study was conducted with the aim of investigating and forecasting meteorological drought in Tehran province using the ARIMA model. Data from seven rainfall stations for the period 2000-2020 were used to evaluate the Standardized Precipitation Index (SPI). Then, the ARIMA model for drought prediction was implemented based on SPI, and the best model for drought prediction was extracted for each station. The results showed that ARIMA time series models can correctly evaluate climate change. Also, according to the results of the SPI drought index for the forecasted period, it was found that the situation was close to normal in all the studied stations, and from 2022 to 2024, the conditions have progressed towards improving the rainfall situation, which according to the recent rainfall in Iran, this model It has been able to model climate changes well. According to the SPI index, the drought in the target area is close to normal, it can be a suitable tool for managing water resources, preserving natural ecosystems, and improving the future climate.