Davood Darvishi Salookolaei - Assistant Professor, Department of Mathematics, Payame Noor University, Tehran, Iran.
Sifeng Liu - College of Economics and Management, Nanjing University of Aeronautics and Astronautics, Nanjing, China
Parvin Babaei - Master of Science, Department of Mathematics, Payame Noor University, Tehran, Iran.

Considering the fact that Iran is situated in an arid and semi-arid region, rainfall prediction for the management of water resources is very important and necessary. Researchers have proposed various prediction methods that have been utilized in such areas as water and meteorology, especially water resources management. The present study aimed at predicting rainfall amounts using Grey Prediction Method. It is a novel approach in confrontation with uncertainties in the aquiferous region of Babolrud to serve for the water resources management purposes. Therefore, expressing the concepts of Grey Prediction Methods using the collected data, at a ۱۲-year timeframe of ۲۰۰۶ and ۲۰۱۷, rainfall prediction in ۲۰۱۸ and ۲۰۲۲ were also implemented with three methods GM(۱,۱), DGM(۲,۱) and Verhulest models. According to the calculated error and the predictive power, GM(۱,۱) method is better than other models and was placed within the set of good predictions. Also, we predict that in ۲۰۲۷, there might be a drought. According to the small samples and calculations required in this approach, the method is suggested for rainfall prediction in inexact environments. The authors can use fuzzy grey systems to predict the amount of rainfall in uncertaint environments.

prediction, Grey system, Water resources management, Rainfall amount, Absolute prediction error