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Parameter sensitivity analysis and optimization of Noah land surface model with field measurements from Huaihe River Basin, China

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Abstract

This study aims to identify the parameters that are most important in controlling the Noah land surface model (LSM), the analysis of parameter interactions, and the evaluation of the performance of parameter optimization using the parameter estimation software PEST. We found it necessary to analyze parameter sensitivity in order to properly simulate hydrological variables such as latent heat flux in the Huaihe River Basin, China. The parameters under study in the Noah LSM link thermodynamic and hydrological parts into a complete model. To our knowledge, this parameter interaction in the Noah LSM has never been studied before. There are, however, several studies concerning the influence of vegetation types and climate conditions on parameter sensitivity of the Noah LSM. Three sensitivity analysis methods, the including local sensitivity analysis method SENSAN, regional sensitivity analysis, and Sobol’s method, were tested. Five experimental sites in the Huaihe River Basin were chosen to perform the simulations. The results show that the Noah LSM parameter sensitivities were impacted by the choice of the analysis method. The local method SENSAN often produced significant differences in results compared to the two global methods. The parameter interactions investigated made a significant contribution towards elucidating how one process influences another in the Noah LSM. The results show that parameters were not transferable solely based on vegetation types but also rely on climate conditions. According to the sensitivity analysis results, four sensitive parameters were chosen to be optimized using the PEST method. PEST is a widely used method for estimating parameters in models. Root-mean-square error was used to evaluate the effect of the optimization. Generally in all sites, the optimized parameters values perform better than the original parameter values.

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Acknowledgments

This research was supported by National Basic Research Program of China (2013CBA01806); NNSF (41371049;51190091); The open fund of State Key Laboratory of Desert and Oasis Ecology; Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences and the National Science Foundation for Outstanding Youth (41125002); PAPD. The authors are grateful to the editors and the reviewers; the comments and suggestions of the editors and reviewers have contributed significantly to the improvement of the manuscript.

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Authors and Affiliations

  1. State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, College of Hydrology and Water Resources, Hohai University, Nanjing, 210098, China

    Ting Hou, Yonghua Zhu, Haishen Lü, Zhongbo Yu & Fen Ouyang

  2. Department of Earth and Environmental Sciences, University of Waterloo, 200 University Avenue West, Waterloo, ON, N2L 3G1, Canada

    Edward Sudicky

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  1. Ting Hou
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  2. Yonghua Zhu
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  3. Haishen Lü
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  5. Zhongbo Yu
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Correspondence to Haishen Lü.

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Hou, T., Zhu, Y., Lü, H. et al. Parameter sensitivity analysis and optimization of Noah land surface model with field measurements from Huaihe River Basin, China. Stoch Environ Res Risk Assess 29, 1383–1401 (2015). https://doi.org/10.1007/s00477-015-1033-5

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