Nowadays, Nitrate contamination of groundwater resources is one of the most important environmental issues. Nitrate is both soluble and mobile, so it is prone to leaching through soil with infiltrating such as rainfall or irrigation water. On the other hand discharge of wastewaters from industrial and agricultural activities has resulted in degradation of water resources. Elevated nitrate concentrations in drinking water can cause Methemoglobinemia in infants and stomach cancer in adults. As such, the US Environmental Protection Agency (US EPA) has established a maximum contaminant level (MCL) of 10 mg/l NO3-N. Therefore, access to reliable water resources will be a real challenge for many communities, especially in semi arid and arid regions. Considering the above, assessment and prediction of water quality will be a first step in planning and management of water resources. Mathematical modeling and simulation is one of the tools used by researchers for this purpose. Groundwater provides one third of the world’s drinking water. Importance of identifying groundwater pollution and increasing demand for water quality, demonstrate the need for creating powerful, reliable and predictive models. In this field, intelligent and data-driven models are new methods that are rapidly expanding in various fields of science. These models are able to train and generalized, they could be used for estimation, prediction and management in various aspects of water resources. Support Vector Machine is a method for ). Keywords: Data Driven Model, Support Vector Machines, Nitrate Concentration, Groundwater Resource
