Varinace-Based Sensitivity Analysis of Deterministic Model

‎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.