Journal of Geographical Sciences ›› 2019, Vol. 29 ›› Issue (9): 1475-1490.doi: 10.1007/s11442-019-1672-4

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Spatial-temporal variability of the fluctuation of soil temperature in the Babao River Basin, Northwest China

NING Lixin1,2,3, CHENG Changxiu1,2,3,*(), SHEN Shi1,2,3   

  1. 1 State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing 100875, China
    2 Key Laboratory of Environmental Change and Natural Disaster, Beijing Normal University, Beijing 100875, China
    3 Center for Geodata and Analysis, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
  • Received:2018-10-23 Accepted:2019-02-28 Online:2019-09-25 Published:2019-12-11
  • Contact: CHENG Changxiu E-mail:chengcx@bnu.edu.cn
  • About author:Ning Lixin (1991-), specialized in disaster risk analysis. E-mail: ninglixin123@163.com
  • Supported by:
    National Key R&D Program of China(No.2017YFB0504102);National Natural Science Foundation of China(No.41771537)

Abstract:

The Babao River Basin is the “water tower” of the Heihe River Basin. The combination of vulnerable ecosystems and inhospitable natural environments substantially restricts the existence of humans and the sustainable development of society and environment in the Heihe River Basin. Soil temperature (ST) is a critical soil variable that could affect a series of physical, chemical and biological soil processes, which is the guarantee of water conservation and vegetation growth in this region. To measure the temporal variation and spatial pattern of ST fluctuation in the Babao River Basin, fluctuation of ST at various depths were analyzed with ST data at depths of 4, 10 and 20 cm using classical statistical methods and permutation entropy. The study results show the following: 1) There are variations of ST at different depths, although ST followed an obvious seasonal law. ST at shallower depths is higher than at deeper depths in summer, and vice versa in winter. The difference of ST between different depths is close to zero when ST is near 5℃ in March or -5℃ in September. 2) In spring, ST at the shallower depths becomes higher than at deeper depths as soon as ST is above -5℃; this is reversed in autumn when ST is below 5℃. ST at a soil depth of 4 cm is the first to change, followed by ST at 10 and 20 cm, and the time that ST reaches the same level is delayed for 10-15 days. In chilling and warming seasons, September and February are, respectively, the months when ST at various depths are similar. 3) The average PE values of ST for 17 sites at 4 cm are 0.765 in spring > 0.764 in summer > 0.735 in autumn > 0.723 in winter, which implies the complicated degree of fluctuations of ST. 4) For the variation of ST at different depths, it appears that Max, Ranges, Average and the Standard Deviation of ST decrease by depth increments in soil. Surface soil is more complicated because ST fluctuation at shallower depths is more pronounced and random. The average PE value of ST for 17 sites are 0.863 at a depth of 4 cm > 0.818 at 10 cm > 0.744 at 20 cm. 5) For the variation of ST at different elevations, it appears that Max, Ranges, Average, Standard Deviation and ST fluctuation decrease with increasing elevation at the same soil depth. And with the increase of elevation, the decrease rates of Max, Range, Average, Standard Deviation at 4 cm are -0.89℃/100 m, -0.94℃/100 m, -0.43℃/100 m, and -0.25℃/100 m, respectively. In addition, this correlation decreased with the increase of soil depth. 6) Significant correlation between PE values of ST at depths of 4, 10 and 20 cm can easily be found. This finding implies that temperature can easily be transmitted within soil at depths between 4 and 20 cm. 7) For the variation of ST on shady slope and sunny slope sides, it appears that the PE values of ST at 4, 10 and 20 cm for 8 sites located on shady slope side are 0.868, 0.824 and 0.776, respectively, whereas they are 0.858, 0.810 and 0.716 for 9 sites located on sunny slope side.

Key words: soil temperature, spatial-temporal fluctuation, classical statistical methods, permutation entropy, Babao River Basin