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吴龙刚, 王爱慧, 盛炎平. 土壤质地对中国区域陆面过程模拟的影响[J]. 气候与环境研究, 2014, 19(5): 559-571. DOI: 10.3878/j.issn.1006-9585.2013.13055
引用本文: 吴龙刚, 王爱慧, 盛炎平. 土壤质地对中国区域陆面过程模拟的影响[J]. 气候与环境研究, 2014, 19(5): 559-571. DOI: 10.3878/j.issn.1006-9585.2013.13055
WU Longgang, WANG Aihui, SHENG Yanping. Impact of Soil Texture on the Simulation of Land Surface Processes in China[J]. Climatic and Environmental Research, 2014, 19(5): 559-571. DOI: 10.3878/j.issn.1006-9585.2013.13055
Citation: WU Longgang, WANG Aihui, SHENG Yanping. Impact of Soil Texture on the Simulation of Land Surface Processes in China[J]. Climatic and Environmental Research, 2014, 19(5): 559-571. DOI: 10.3878/j.issn.1006-9585.2013.13055

土壤质地对中国区域陆面过程模拟的影响

Impact of Soil Texture on the Simulation of Land Surface Processes in China

  • 摘要: 利用陆面过程模式(CLM3.5)和中国区域两种土壤质地数据(分别来自第二次中国土壤调查SNSS和联合国粮食农业组织FAO),研究了土壤质地变化对于模式模拟的陆表水热变量的影响。结果显示,土壤质地对土壤水文学变量的影响远大于对土壤热力学变量的影响,尤其是对于饱和土壤含水量和饱和水力传导率的影响。对于模式的输出,土壤质地影响比较明显的有土壤湿度、总径流和土壤渗透等水文学变量以及地表潜热、地表感热和土壤热通量等热力学变量,而影响相对较小的有地面吸收的太阳辐射和地表反照率。同时,发现基于SNSS模拟的土壤湿度与站点观测值更加接近。因此,本研究认为基于SNSS土壤质地数据可以有效地改进模式模拟结果,建议以后在陆面模式试验中尽可能使用以观测为基础的SNSS土壤质地数据。

     

    Abstract: On the basis of Community Land Model version 3.5 (CLM3.5) and two soil texture datasets such as the Second National Soil Survey of China (SNSS) and the Food and Agriculture Organization of the United Nations (FAO), this study investigates the impacts of soil texture on the simulation of land surface processes in China. By analyzing soil hydrological and thermal properties derived from soil texture, it is determined that soil texture plays a more important role on the soil hydrological characteristics, such as saturated soil moisture and saturated hydraulic conductivity, than that on its thermal properties. Model outputs show that soil texture has a significant impact on soil moisture, runoff, infiltration, surface latent heat, sensible heat, and heat flux, while little impact on absorbed solar radiation and albedo. Moreover, it is shown that soil moisture values are closer to the observations when simulated by CLM3.5 with SNSS than those simulated with FAO. Therefore, to improve the performance of the land surface model, particularly for soil hydrology, this study suggests the use of observation-based soil texture datasets, such as those of SNSS, in the future.

     

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