| 土壤湿度和土壤温度模拟中的参数敏感性分析和优化 |
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| 引用本文： | 李得勤,段云霞,张述文,文小航.土壤湿度和土壤温度模拟中的参数敏感性分析和优化[J].大气科学,2015,39(5):991-1010. |
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| 作者姓名： | 李得勤 段云霞 张述文 文小航 |
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| 作者单位： | 1.中国气象局沈阳大气环境研究所, 沈阳 110166;兰州大学半干旱气候变化教育部重点实验室, 兰州 730000 |
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| 基金项目： | 国家自然科学基金项目41105064、41305058,半干旱气候变化教育部重点实验室(兰州大学)开放课题 |
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| 摘 要： | 使用一种复杂洗牌算法 (SCE-UA, Shuffled Complex Evolution Algorithm) 对Noah陆面模式中的参数进行敏感性分析和优化,其中水文参数采取直接优化和优化土壤成份的形式,侧重于研究两种水文参数给出方法对土壤湿度和土壤温度模拟的敏感性。结果表明:将土壤湿度和土壤温度作为判据,模式中水文参数敏感性最高,水文参数对土壤湿度的敏感性要高于对土壤温度的敏感性。表层土壤湿度作为判据对土壤水文参数优化后,可以改善土壤湿度和土壤温度的模拟,加入深层土壤湿度同时作为判据后,优化使土壤温度的模拟变差。当土壤成份作为优化的参数,表层和深层土壤湿度作为判据,优化能够同时改善土壤湿度和土壤温度的模拟。单独使用土壤温度作为判据不能达到优化水文参数的目的。将土壤成份作为优化的参数后,土壤湿度和土壤温度的多判据优化效果最好,且减少不敏感参数的个数后对优化结果的影响总体不大。基于以上结果,将土壤成份作为优化水文参数的方法能够更好的考虑不同水文参数之间的约束关系,优化后的水文参数具有很好的一致性,优化效果较直接优化水文参数更好。
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| 关 键 词： | 土壤湿度 参数优化 敏感性分析 陆面过程 |
| 收稿时间： | 2014/9/30 0:00:00 |
| 修稿时间： | 2015/3/11 0:00:00 |
Quantifying Parameter Sensitivity and Calibration in Simulating Soil Temperature and Moisture |
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| Deqin,DUAN Yunxi,ZHANG Shuwen and WEN Xiaohang.Quantifying Parameter Sensitivity and Calibration in Simulating Soil Temperature and Moisture[J].Chinese Journal of Atmospheric Sciences,2015,39(5):991-1010. |
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| Authors: | Deqin DUAN Yunxi ZHANG Shuwen and WEN Xiaohang |
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| Institution: | 1.Institute of Atmospheric Environment, China Meteorological Administration, Shenyang 110016;Key Laboratory for Semi-Arid Climate Change of the Ministry of Education, Lanzhou University, Lanzhou 7300002.Shenyang Meteorological Service, Shenyang 1100163.Key Laboratory for Semi-Arid Climate Change of the Ministry of Education, Lanzhou University, Lanzhou 7300004.Chendu University of Information Technology, Chendu 610225 |
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| Abstract: | The Shuffled Complex Evolution Algorithm is used to estimate the parameters in the Noah model, and soil hydraulic parameters are also estimated by soil texture components to evaluate the sensitivity of model hydraulic parameters in simulating soil moisture and soil temperature. The results show that soil hydraulic parameters are more sensitive than parameters related to vegetation, and more sensitive to soil moisture than soil temperature. When surface soil moisture is used to calculate the objective function, the estimated hydraulic parameters can not only improve the soil moisture, but also soil temperature. However, when deep soil moisture is used to calculate the objective function, the soil temperature simulation is even worse than with default parameters. Soil texture components are also used to calculate soil hydraulic parameters; and when they are used as estimated parameters, the results can improve both soil moisture and soil temperature simulation. Parameter estimation experiments in which soil temperature is used to calculate the objective function cannot improve the simulation of soil moisture. When soil texture components are used as estimated parameters and soil moisture and soil temperature are used to calculate the objective function, the estimated hydraulic parameters can improve both soil moisture and soil temperature simulation. Decreasing the number of parameters has little impact on the results. Accordingly, when soil texture components are used as estimating parameters in this land surface model, the estimated hydraulic parameters show good consistency-more so than when estimating hydraulic parameters directly. |
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| Keywords: | Soil moisture Parameter calibration Sensitivity Land surface model |
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