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Journal of Arid Land  2020, Vol. 12 Issue (3): 423-435    DOI: 10.1007/s40333-020-0103-9
Research article     
Application of a new wind driving force model in soil wind erosion area of northern China
ZOU Xueyong1,*(), LI Huiru1, LIU Wei2, WANG Jingpu3, CHENG Hong1, WU Xiaoxu4, ZHANG Chunlai1, KANG Liqiang1
1 State Key Laboratory of Earth Surface Processes and Resource Ecology/MOE Engineering Research Center of Desertification and Blown-sand Control, Beijing Normal University, Beijing 100875, China
2 School of Geographic and Environmental Sciences, Tianjin Normal University, Tianjin 300387, China
3 School of Resources and Environmental Engineering, Ludong University, Yantai 264025, China
4 College of Global Change and Earth System Science, Beijing Normal University, Beijing 100875, China
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The shear stress generated by the wind on the land surface is the driving force that results in the wind erosion of the soil. It is an independent factor influencing soil wind erosion. The factors related to wind erosivity, known as submodels, mainly include the weather factor (WF) in revised wind erosion equation (RWEQ), the erosion submodel (ES) in wind erosion prediction system (WEPS), as well as the drift potential (DP) in wind energy environmental assessment. However, the essential factors of WF and ES contain wind, soil characteristics and surface coverings, which therefore results in the interdependence between WF or ES and other factors (e.g., soil erodible factor) in soil erosion models. Considering that DP is a relative indicator of the wind energy environment and does not have the value of expressing wind to induce shear stress on the surface. Therefore, a new factor is needed to express accurately wind erosivity. Based on the theoretical basis that the soil loss by wind erosion (Q) is proportional to the shear stress of the wind on the soil surface, a new model of wind driving force (WDF) was established, which expresses the potential capacity of wind to drive soil mass in per unit area and a period of time. Through the calculations in the typical area, the WDF, WF and DP are compared and analyzed from the theoretical basis, construction goal, problem-solving ability and typical area application; the spatial distribution of soil wind erosion intensity was concurrently compared with the spatial distributions of the WDF, WF and DP values in the typical area. The results indicate that the WDF is better to reflect the potential capacity of wind erosivity than WF and DP, and that the WDF model is a good model with universal applicability and can be logically incorporated into the soil wind erosion models.

Key wordssoil wind erosion      wind driving force      weather factor      drift potential      WDF (wind driving force) model     
Received: 28 October 2019      Published: 10 May 2020
Corresponding Authors: Xueyong ZOU     E-mail:
About author: *Corresponding author: ZOU Xueyong (E-mail:
Cite this article:

ZOU Xueyong, LI Huiru, LIU Wei, WANG Jingpu, CHENG Hong, WU Xiaoxu, ZHANG Chunlai, KANG Liqiang. Application of a new wind driving force model in soil wind erosion area of northern China. Journal of Arid Land, 2020, 12(3): 423-435.

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Fig. 1 Application area of the WDF model and the spatial distributions of meteorological stations and annual average wind velocity
Fig. 2 Annual variation of the WDF values and the Mann-Kendall trend test (in the upper-right corner) in the application area during 1980-2016
Fig. 3 Seasonal variation of the WDF values in the application area during 1980-2016
Fig. 4 Spatial distribution of annual mean WDF value (a) and Mann-Kendall trend test (b) in the application area during 1980-2016
Fig. 5 Spatial distribution of seasonal mean WDF value in the application area in spring (a), summer (b), autumn (c) and winter (d) during 1980-2016
Fig. 6 Spatial distribution comparison of soil wind erosion intensity with the WDF, WF (weather factor) and DP (drift potential) in the typical area (Taklimakan Desert and its surrounding areas). (a), spatial distribution of soil wind erosion intensity modified from the literature (Niu, 2017); (b), a scale enlarged view of the typical area; (c), (d) and (e), the spatial distributions of the WDF, WF and DP in the typical area, respectively.
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