Influence of teleconnection patterns on prediction of groundwater level fluctuations(Case Study: Garmsar Plain)

External source of weather signals is also called teleconnections that can change weather conditions and thus affect groundwater resources. The purpose of this study is to predict the effect of teleconnection patterns on groundwater level fluctuations in Garmsar plain. Data of groundwater level, climatic parameters of the study area, as well as 16 teleconnection indices from 1993 to 2016 were used for this study. Gamma test was used to analyze inputs sensitivity and so determine the optimal combination of inputs. Modeling was performed with multiple regression as well as multilayer perceptron artificial neural network (MLP) with two learning algorithms of Levenberg-Marquardt and Bayesian.Sensitivity analysis of model inputs with gamma test showed that among the climate parameters of the region, maximum temperature of Firoozkooh station and also teleconnection indices of SOI, EA, NP and WP had the most influence among the selected inputs. The results of the modeling using the most effective inputs showed that the best model is the neural network method with Bayesian learning algorithm, that in the model testing stage in Sardareh well, the MSE and the R2 were 0.36 and 0.93 respectively. In well 26, these values were 0.038 and 0.85, respectively. Also, rsults indicated that the use of teleconnections indices to predict groundwater level fluctuations in Sardareh well and in well 26 reduced the error rate by 5.6% and by 24% respectively.