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Comparative Study of Computing Methods of Soil Temperature on Different Underlying Surfaces

ZHANG Haihong1, LIU Shuhua1, WEI Zhigang2, Lv Shihua2, HOU Xuhong2,WEN Jun2, GAO Xiaoqing2   

  1. 1. Department of Atmospheric and Oceanic Sciences, School of Physics, Peking University, Beijing 100871; 2. Cold and Arid Regions Environmental Engineering Research Institute, Chinese Academy of Science, Lanzhou 730000;
  • Received:2010-12-22 Online:2011-11-20 Published:2011-11-20



  1. 1. 北京大学物理学院大气与海洋科学系, 北京 100871; 2. 中国科学院寒区旱区环境与工程研究所, 兰州 730000;

Abstract: Using soil temperature data observed at Dunhuang, Badanjilin Desert center, Badanjilin Desert edge and Pingliang from July to Aug. 2009, the soil thermal diffusivity and soil water flux density are calculated with thermal conduction algorithm and thermal conduction-convection algorithm. Based on these results and taking the soil layer at the depth of 5 cm as the upper boundary, the soil temperatures at the depth of 10 cm in the 4 areas are modeled using the two algorithms. The results show that both of the two methods could correctly model the soil temperature, and the soil temperature modeled at daytime is more exact. The soil thermal diffusivities of Dunhuang, Badanjilin Desert center, Badanjilin Desert edge and Pingliang are 1.62 × 10-7, 6.92 × 10-7, 8.01 × 10-7and 16.10 × 10-7m2/s, and the soil water flux densities of Badanjilin Desert center, Badanjilin Desert edge and Pingliang are 4.72, 9.22 and 7.06 m2/s. The standard error of soil temperature modeled by thermal conduction algorithm is less at Dunhuang Gobi, where the soil moisture is low. The standard errors of soil temperature modeled by thermal conduction-convection algorithm are less at Badanjilin Desert center, Badanjilin Desert edge and Pingliang, where the soil moistures are high.

Key words: arid and semi-arid region, underlying surface, soil temperature, thermal conduction algorithm, thermal conduction-convection algorithm, minimum variance fitting method

摘要: 利用2009年7-8月敦煌、巴丹吉林沙漠边缘、巴丹吉林沙漠腹地和平凉的土壤温度观测资料, 采用热传导方法和热传导?对流方法分别计算了4个地区的土壤热扩散率及水通量密度, 并以5 cm深处土壤为上边界, 利用两种方法模拟了4个地区10 cm深处的土壤温度值。结果表明: 两种方法模拟出不同下垫面的土壤温度值及其日变化特征与实际观测基本一致, 白天的温度模拟值更加准确。敦煌、巴丹吉林沙漠边缘、巴丹吉林沙漠腹地和平凉4个地区的土壤热扩散率分别为1.62 × 10-7, 6.92 × 10-7, 8.01 × 10-7和16.10 × 10-7m2/s, 巴丹吉林沙漠边缘、巴丹吉林沙漠腹地和平凉黄土区的水通量密度分别为4.72, 9.22和7.06 m/s。在敦煌戈壁下垫面地区, 土壤含水量低, 热传导方法模拟的土壤温度的标准差较小。在巴丹吉林沙漠边缘、巴丹吉林沙漠腹地和平凉黄土下垫面地区, 由于考虑了水分的垂直运动对能量的输送, 热传导?对流方法模拟的土壤温度的标准差较小。

关键词: 干旱半干旱区, 下垫面, 土壤温度, 热传导方法, 热传导?对流方法, 最小方差拟合法

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