Using ARIMA Time Series Model to Predict Groundwater Quality Parameters for use in agriculture (Case Study: Chaharmahal & Bakhtiari Plain)

Groundwater is an important water resource especially in arid and semi-arid regions. Therefore, according to the conditions, it is necessary to study and predict the qualitative changes of water in the future. In this study two quality parameters Including electrical conductivity (EC) and sodium adsorption ratio (SAR) taken from 18 groundwater wells in Chaharmahal and Bakhtiari Province during the years 1991 to 2016 were used. First, the primary zoning map was drawn from the parameters at the beginning and the end of the data range, then the suitable model for each parameter in each well was choiced and by drawing a map of groundwater quality zoning in 2021, the changes between these years was studied and groundwater quality was determined by Wilcox. Based on the results, selected ARIMA models have good performance. Also, according to these models, the average amount of predicted SAR (absorption rate) in all wells will decrease in 2021 compared to 2016, while the average amount of EC (electrical conductivity) is increasing in all wells. Therefore, according to the reviewed qualitative parameters, the majority of the region can be classified in the C2S1 and C3S1 classes, that will be salt and harmful water for agriculture.