Sensitivity analysis is the basic process of modeling that determines how the variation in the output of the model can be attributed to variations of its input factors. In recent decades with the increase in simulation models and the complexity of these models due to increased variables, sensitivity analysis is an essential tool for understanding the role and significance of variables in the modeling process. There are different categorizations for a variety of sensitivity analysis methods, Depending on whether output variability is obtained by varying the inputs around reference (nominal) values, or across their entire feasible space, Sensitivity analysis is either referred to as local or global. Quantitative and qualitative sensitivity analysis and One-At-a-Time (OAT) and All-At-a-Time (AAT) methods are other divisions for a variety of sensitivity analysis methods. In this study, sensitivity analysis methods in simulation models were investigated and capability of GLUE method, a common method for uncertainty analysis based on the Monte Carlo simulations, was presented to analyze the sensitivity of groundwater model in a case study.