Wind modelling for wind erosion research by open source computational fluid dynamics

The open source computational fluid dynamics (CFD) wind model (CFD-WEM) for wind erosion research in the Xilingele grassland in Inner Mongolia (autonomous region, China) is compared with two open source CFD models Gerris and OpenFOAM. The evaluation of these models was made according to software technology, implemented methods, handling, accuracy and calculation speed. All models were applied to the same wind tunnel data set. Results show that the simplest CFD-WEM has the highest calculation speed with acceptable accuracy, and the most powerful OpenFOAM produces the simulation with highest accuracy and the lowest calculation speed. Gerris is between CFD-WEM and OpenFOAM. It calculates faster than OpenFOAM, and it is capable to solve different CFD problems. CFD-WEM is the optimal model to be further developed for wind erosion research in Inner Mongolia grassland considering its efficiency and the uncertainties of other input data. However, for other applications using CFD technology, Gerris and OpenFOAM can be good choices. This paper shows the powerful capability of open source CFD software in wind erosion study, and advocates more involvement of open source technology in wind erosion and related ecological researches.

[1]  Michael Sommer,et al.  Temporal variations in PM10 and particle size distribution during Asian dust storms in Inner Mongolia , 2008 .

[2]  Shi Feng,et al.  Computational simulations of blown sand fluxes over the surfaces of complex microtopography , 2010, Environ. Model. Softw..

[3]  E. L. Skidmore,et al.  Soil erosion by wind: an overview , 1986 .

[4]  Ralf Wieland,et al.  Spatial Analysis and Modeling Tool (SAMT): 2. Applications , 2006, Ecol. Informatics.

[5]  Michael Sommer,et al.  Effect of grazing on wind driven carbon and nitrogen ratios in the grasslands of Inner Mongolia , 2008 .

[6]  Ralf Wieland,et al.  Spatial Analysis and Modeling Tool (SAMT): 1. Structure and possibilities , 2006, Ecol. Informatics.

[7]  G. Arfken Mathematical Methods for Physicists , 1967 .

[8]  Yan Yang,et al.  Numerical simulations of flow and pollution dispersion in urban atmospheric boundary layers , 2008, Environ. Model. Softw..

[9]  Ralf Wieland,et al.  Effects of grazing and topography on dust flux and deposition in the Xilingele grassland, Inner Mongolia , 2008 .

[10]  Ralf Wieland,et al.  Multi-Scale Landscape Analysis (MSLA) - A method to identify correlation of relief with ecological point data , 2011, Ecol. Informatics.

[11]  Rainer Horn,et al.  Spatial variability of soil properties affected by grazing intensity in Inner Mongolia grassland , 2007 .

[12]  S. Popinet Gerris: a tree-based adaptive solver for the incompressible Euler equations in complex geometries , 2003 .

[13]  Geoffrey J. Hay,et al.  Free and open source geographic information tools for landscape ecology , 2009, Ecol. Informatics.

[14]  William Gropp,et al.  High-performance parallel implicit CFD , 2001, Parallel Comput..

[15]  Efisio Solazzo,et al.  Improved parameterisation for the numerical modelling of air pollution within an urban street canyon , 2009, Environ. Model. Softw..

[16]  Sarah J. Wakes,et al.  Numerical modelling of wind flow over a complex topography , 2010, Environ. Model. Softw..

[17]  Jean-Luc Harion,et al.  Numerical modelling of flow over stockpiles: Implications on dust emissions , 2005 .

[18]  Hisham El-Shishiny,et al.  Influences of wind flow over heritage sites: A case study of the wind environment over the Giza Plateau in Egypt , 2009, Environ. Model. Softw..

[19]  Ralf Wieland,et al.  Detecting landscape forms using Fourier transformation and singular value decomposition (SVD) , 2009, Comput. Geosci..