Prediction of Water Level and Salinity of Lakes by Using Artificial Neural Networks, Case Study: Lake Urmia

Urmia Lake is the 20st largest lake in the world and the second salt lake of the World according to its high salinity. This lake is considered as an evacuation place and final destination of some important rivers of northwest of Iran. This lake is also very important because of its effects on economic and environment of region. In recent years because of decrease of rainfall and drought, unessential use of agricultural water, evaporation on water surface of lake, bracing of water surface flows by dams in upstream of rivers and digging of wells near the lake, water surface level of lake has decreased and salinity of water of the lake has increased very much. Considering the importance of water surface level and salinity of lake, study on these items through environmental approachplay important role for decision making. It is necessary to predict water level and salinity of Urmia Lake for future programming to prevent, continue of this critical situation. In this research water level and salinity of Urmia Lake have been analyzed and predicted by using artificial neural networks and statistical software. Obtained results from this research showed that water level of Urmia Lake is predicted very well. Also prediction of salinity has shown acceptable results. Calculation of water level and salinity of this lake in a same time prediction mode is another research that has been investigated in this study.