Comparison of Fourteen Methods of Time Series to Analyze and PredictGround Water Changes in Marand Plain (North of Urmia Lake)

Marand plain is one of the most important regions for agricultural production in East Azarbaijan province, Iran. In this plain groundwater resources were applied to compensate more than 80% the water requirements of agricultural productions. Continuous consumption of groundwater caused a significant decline since 1982. Therefore, optimal and sustainable utilization of groundwater resources is a management necessity in Marand plain. Consequently, modeling and predicting the exploitation process could be accomplished by the appropriate techniques. This study was conducted with the aim of analyzing the groundwater level variations in Marand plain with time series models. Because of the ability of time series techniques to model and predict the behavior of temporal variation in water engineering phenomenon. Moreover, the groundwater level decline was modeled for 45-year with 14 methods of time series analysis in this study. An Autoregressive Integrated Moving Average (ARIMA) model was recognized as the most appropriate pattern. Modeling, testing and prediction were as follows: 25- year of the data for modeling (from 1982 to 2006), 10- year of data for the test (from 2006 to 2017) and future 10 years (from 2017 to 2027) were used for predicting ground water changes. Results showed that the average decline of groundwater from 1982 up to now was 17 m. For optimal management of groundwater application, different saving scenarios including 0, 5, 10, 15, 20, 25 and 30 percent savings starting from 2018 were considered. In the tenth year, about 67 ×106 m3 of groundwater will be saved with savings of only 10% from year of 2018. The land leveling, crop with low water requirements, deficit irrigation and irrigation scheduling could be applied to save groundwater in the north of Urmia Lake.