TY  - JOUR
A1  - Zhang, Zhuodong
A1  - Wieland, Ralf
A1  - Reiche, Matthias
A1  - Funk, Roger
A1  - Hoffmann, Carsten
A1  - Li, Yong
A1  - Sommer, Michael
T1  - Identifying sensitive areas to wind erosion in the xilingele grassland by computational fluid dynamics modelling
JF  - Ecological informatics : an international journal on ecoinformatics and computational ecolog
N2  - In order to identify the areas in the Xilingele grassland which are sensitive to wind erosion, a computational fluid dynamics model (CFD-WEM) was used to simulate the wind fields over a region of 37 km(2) which contains different topography and land use types. Previous studies revealed the important influences of topography and land use on wind erosion in the Xilingele grassland. Topography influences wind fields at large scale, and land use influences wind fields near the ground. Two steps were designed to implement the CFD wind simulation, and they were respectively to simulate the influence of topography and surface roughness on the wind. Digital elevation model (DEM) and surface roughness length were the key inputs for the CFD simulation. The wind simulation by CFD-WEM was validated by a wind data set which was measured simultaneously at six positions in the field. Three scenarios with different wind velocities were designed based on observed dust storm events, and wind fields were simulated according to these scenarios to predict the sensitive areas to wind erosion. General assumptions that cropland is the most sensitive area to wind erosion and heavily and moderately grazed grasslands are both sensitive etc. can be refined by the modelling of CFD-WEM. Aided by the results of this study, the land use planning and protection measures against wind erosion can be more efficient. Based on the case study in the Xilingele grassland, a method of regional wind erosion assessment aided by CFD wind simulation is summarized. The essence of this method is a combination of CFD wind simulation and determination of threshold wind velocity for wind erosion. Because of the physically-based simulation and the flexibility of the method, it can be generalised to other regions.
KW  - Sensitive areas
KW  - Wind erosion
KW  - Computational fluid dynamics
KW  - Grassland
KW  - Surface roughness
Y1  - 2012
U6  - https://doi.org/10.1016/j.ecoinf.2011.12.002
SN  - 1574-9541
VL  - 8
IS  - 5
SP  - 37
EP  - 47
PB  - Elsevier
CY  - Amsterdam
ER  -