Comparison between SARIMA and SARIMAX time series Models with application on Groundwater in Sulaymaniyah

Bakhan Hoshyar  Qadir; Monem Aziz  Mohammed

doi:10.25098/5.2.17

Authors

Bakhan Hoshyar Qadir 2Department of statistic and informatics, College of Administration and Economics, University of Sulaimani, Sulaymaniyah, Iraq.
Monem Aziz Mohammed Department of statistic and informatics, College of Administration and Economics, University of Sulaimani, Sulaymaniyah, Iraq.

DOI:

https://doi.org/10.25098/5.2.17

Keywords:

SARIMA, SARIMAX, groundwater level, climate variability

Abstract

Groundwater is one of the common essential water resources for billions of people, especially for many developing countries in Asia. Indeed, climate variation is one factor in the quantity and quality of groundwater resources in the world. The study used time-series data, it can be used to understand the past as well as predict the future.

Additionally, were taken climate index (Rainfall) to show and understand ground water level is affected by external factors and show the relationship between them. For this purpose, using groundwater level data during (7) years period contained 89 observation of data; beginning from (Jan 2013) through (May 2020) in the center of Sulaymaniyah city. Additionally, the climate variability data and groundwater data are monthly through a duration time.

The objective of this study Fitting the suitable Seasonal Autoregressive Integrated Moving Average (SARIMA) and Seasonal Autoregressive Integrated Moving Average with Explanatory variable (SARIMAX) model to studies the relationship between the climate variation and groundwater level. Finally, after added climate variability (Rainfall) to the SARIMA model, study showed the ground water level is affected by external factors. while, coefficient of external factor is positive and significant at %5 level of significant. This showed ARIMAX (0,1,0) x (1,0,1)12 with AIC (456.744) is a best model.

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