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Research on Variation Rule of Sensible Heat Flux in Field Under Different Soil Moisture Content and Underlying Surface by Large Aperture Scintillometer

  • Xin Han
  • Qingyun Zhou
  • Baozhong Zhang
  • Di Xu
Conference paper
Part of the IFIP Advances in Information and Communication Technology book series (IFIPAICT, volume 509)

Abstract

The surface sensible heat flux has a profound impact on regional energy balance of payments and regional water cycle, which is an important part of composition of the surface energy balance. This research was based on the large aperture scintillometer (LAS), combined with eddy covariance system. Sensible heat fluxes in field in September 2015 - April 2016 were observed continuously on Daxing district experimental base in Beijing. The original data was processed by BLS software and the data process cycle of large aperture scintillometer was established.The analysis of sensible heat fluxes in field under different soil moisture content and different underlying surface could provide theoretical basis for variability of sensible heat fluxes in field.

Keywords

Sensible heat flux Large aperture scintillameter Eddy covariance system Soil moisture content Underlying surface 

Notes

Acknowledgment

This work was financially supported by Governmental Public Industry Research Special Funds for Projects (201501016), the Chinese National Natural Science Fund (51609170).

References

  1. 1.
    Meijninger, W.M.L., De Bruin, H.A.R.: The sensible heat fluxes over irrigated areas in western Turkey determined with a large aperture scintillometer. J. Hydrol. 229(1), 42–49 (2000)CrossRefGoogle Scholar
  2. 2.
    Von Randow, C., Kruijt, B., Hobbslag, A.A.M., et al.: Exploring eddy-covariance and large-aperture scintillameter measurements in an Amazonian rain forest. Agric. Forest Meteor. 148(4), 680–690 (2008)CrossRefGoogle Scholar
  3. 3.
    De Bruin, H.A.R., Kohsiek, W., VanDenhurk, B.J.J.M.: A verification of some methods to determine the fluxes of momentum sensible heat and water vapor using standard deviation and structure parameter of scalar meteorological quantities. Bound.-Layer Meteorol. 63, 231–257 (1993)CrossRefGoogle Scholar
  4. 4.
    Cain, J.D., Rosier, P.T.W., Meijninger, W.: Spatially averaged sensible heat fluxes measured over barley. Agric. Forest Meteorol. 107, 307–322 (2001)CrossRefGoogle Scholar
  5. 5.
    Ezzahar, J., Chehbouni, A., Hoedjes, J.C.B.: The use of the scintillation technique for estimating and monitoring water consumption of olive orchards in a semiarid region. Agric. Water Manag. 89, 173–184 (2007)CrossRefGoogle Scholar
  6. 6.
    Jie, B., Shaomin, L., Li, L.: Methods of dealing with, the observational data of large aperture flashing research. Progress Earth Sci. 11(25), 1187–1196 (2010)Google Scholar
  7. 7.
    Ziwei, X., Yongbin, H., Shaomin, L.: Study of large aperture flicker meter observation method. Progress Earth Sci. 25(11), 1140–1146 (2010)Google Scholar
  8. 8.
    Li, L., Shaomin, L., Ziwei, X., Jiemin, W., Xiaowen, Li: Different underlying surface observational date processing analysis of large aperture flicker. Progress Earth Sci. 20(2), 172–176 (2009)Google Scholar

Copyright information

© IFIP International Federation for Information Processing 2019

Authors and Affiliations

  • Xin Han
    • 1
    • 2
  • Qingyun Zhou
    • 1
    • 2
  • Baozhong Zhang
    • 2
  • Di Xu
    • 2
  1. 1.College of Water Conservancy EngineeringTianjin Agricultural UniversityTianjinChina
  2. 2.State Key Laboratory of Simulation of Water Cycle in River BasinChina Institute of Water Resources and Hydropower ResearchBeijingChina

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