title: [Comparison of optimum, RSA and GLUE methods in parameter identification of a nonlinear environmental model].
abstract: Parameter identification plays a key role in environmental model application. The optimization method is one of the earliest and most widely used methods. However, as the parameters by optimization may not fully fit the observations, there is a risk that the errors may be enhanced in the decision-make stage. With this deficiency in consideration, the RSA and GLUE algorithms search for the feasible parameters not only to the optimum but also around the neighbors. The difference between RSA and GLUE is that the RSA accepts the estimated parameters equally as the candidates for application; while the GLUE keeps the difference among the parameters as measured by likelihood. In addition for parameter identification, both RSA and GLUE are efficient tools for global sensitivity analysis.
authors.affiliation: Department of Environmental Sciences and Engineering, Tsinghua University, Beijing 100084, China.
authors.forename: Yixiang
authors.initials: Y
authors.lastname: Deng
authors.forename: Qi
authors.initials: Q
authors.lastname: Wang
authors.forename: Siyun
authors.initials: S
authors.lastname: Lai
authors.forename: Jining
authors.initials: J
authors.lastname: Chen
mesh_terms: D004777:Environment; D016013:Likelihood Functions; D017711:Nonlinear Dynamics