Forecasting Urmia Lake Water Level by using Linear Time Series Models

Document Type : Complete scientific research article

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Abstract

Modeling and predicting Urmia Lake level have the importance in investigating facilities and related structures risk, lake water storage changes, costal constructions and environmental impacts. The main object of the present research is to model and predict Urmia Lake level using time series model. In the present research, Urmia lake level data from 1964 to 2006 were used and the prediction carried out to 2016. In order to model, time series different components such as trend, periodicity and stochastic component of lake level were separated and then these components were modeled. The results showed that the used model had a high ability to model Urmia Lake water level. Monthly periods and 3, 4, 20, 35 and 47 years periods are considerable periods and considering these periods, Urmia Lake water level is modeled. Because by removing these periods, obtained series do not have periodicity property. The results showed that Urmia Lake water level decrease from 1270 (m) in 2009 until 1270 (m) in 2016. The results of the present research emphasize to select the basic decisions for protecting Urmia Lake.

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