Forecasting of Shatt al-Arab water levels using autoregressive models and Seasonal Moving Average (SARIMA)

Abstract

The research aims to provide an analytical study of the monthly platforms of Shatt al-Arab waters in Basra governorate by adopting seasonal time chain models. Water tables are directly influencing the levels of salt concentrations by pushing the saline tongue from the Shatt al-Arab waters. This will result in reducing environmental and economic adverse effects, Thus, one of the integration of SARIMA time series integrated regression models and seasonal moving circles to predict future levels of Arabian shatters using the Box-Jenkins methodology, using the data of the desks for the period from January 2009 to December 2021, Accordingly, the study was able to identify the appropriate template for time-series data in the SARIMA (1.1.1) (1.1.1)12 model based on the criteria of good conformity (LogL, AIC, BIC, HQ) and diagnostic tests, where predictive values showed an increasing frequency in the Arab Shatt water levels for the duration (Jan. /2022 - Dec. /2030).