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In this paper, we attempted to entend the application of conditional nonlinear optimal perturbation (CNOP) to the optimization of parameters in land surface model. We used the common land model and data of Tongyu station, which is a reference site of the CEOP in the semi-arid regions, and used three key parameters (soil color, soil sand/lay proportion and leaf area index) as parameters to be optimized. Two experiments are designed in our work, namely the single-parameter optimization and the triple-parameter optimization. Notable improvements in simulating sensible heat flux (SH), latent heat flux (LH), soil temperature (TS) and moisture (MS) at shallow layers were achieved by using the optimized parameters. In addition, the latter experiment shows a better performance than the former. All results above illustrate that the application of CNOP method can be extended to parameters optimization of land surface model. And what is more, due to its other advantages, such as the clear mathematical meaning, the simple design structure, and the fast computing speed, it shows a great potential for further applications in parameters optimization of related problems.