The study of many scientific and natural phenomena in laboratory condition is sometimes impossible, therefore theire expresed by mathemathical models and simulated by complex computer models (codes). Running a computer model with different inputs is called a computer expriment.
Statistical issues allocated a wide range of applications for computer expriment to itself. In this paper, the structure of computer models is described, and one of statistical applications, that is variance-based sensitivity analysis is expressed. Sensitivity analysis, involves a set of methods that determine the effect on model inputs on the output by using sensitivity indices. The indices are defined based on the concept of condition variance and the since explicit mathematical form of the model is unclear, hence the essues monte carlo based them are proposed.
Due to the inherent complexity of the model, execuation time is problem.Therefore a specifict design of expriment, base on Quasi-random number, is proposed to reduce the runnig costs. As an application, the INCA-N model that simulates amount of Nitrogen in river and underground sources was used. Using the sensitivity indices, we could found the effective variable on this danger pollution that threaten human life and inviromental.