Climate change, Groundwater depth, HadCM3, LARS-WG

In the present research, the climate change effect on groundwater resources of Miandoab plain in West Azerbaijan province was investigated. In this direction, the scenarios including A1B, A2 and B1 via LARS-WG downscaling model and with applying the HadCM3 general circulation model and artificial neural network model in two different periods (2046-2065, 2080 -2099) were studied. For this purpose, monthly groundwater depths data of 25 piezometric wells in the Miandoab plain with a 10-year statistical period (2005-2014) and daily and monthly data of rainfall, minimum and maximum temperatures and sunshine hours of the Miandoab synoptic station in a 20-year statistical period (1995-2014) were used. The evaluation results of the observed and simulated data by the LARS-WG model, using different statistical indices indicates that there is no significant differences between simulated and observed values. The performance analysis of the artificial neural network model shows that the mentioned model has good and suitable accuracy in simulating the changes in groundwater depth in the studied plain. The results showed that the average depth of groundwater level in the first period (2046-2065) and the second period (2080-2099) increases 2.87% and 9.3%, respectively. In fact, considerable augmentation of temperature and consequently increasing the groundwater consumption cause to deeper depth of the groundwater.