Improvement and application of wind factor in RWEQ model
GONG Guoli1, LIU Xin2, YAO Ling1, REN Lixia1, WANG Min3
1. Shanxi Institute of Energy, 030600, Yuci, Shanxi, China; 2. Information Center of Ministry of Ecology and Environment, 100029, Beijing, China; 3. Vision World Technology Co., Ltd, 100029, Beijing, China
Abstract：[Background] Wind is the most important driver of soil wind erosion and the most important input parameter in the RWEQ (revised wind erosion equation) model for quantitatively estimating wind erosion. The actual wind speed changes all the time. Substituting the average wind speed into the model will make the calculated wind erosion less. Therefore, the model requires no less than 500 wind speed values to estimate the wind factor. However, wind speed data with high temporary resolution is difficult to acquire. For all this, how to select downscaling techniques for wind speed data is worth studying.[Methods] Two-parameter Weibull distribution model, as well as the fitting method of daily average and maximum wind speed were used to fit wind speed respectively. The fitting results of the two methods were compared with the measured results respectively. The measured data were the observed values of national meteorological stations, including daily four periodic wind speed values, daily mean and daily maximum wind speed values. According to the comparison results, the wind speed downscaling method was modified, and the revised wind speed values were substituted into the RWEQ model to obtain the spatial distribution of wind factors in North China.[Results] 1) There was an error in the wind erosion force between by the two-parameter Weibull distribution model and by the measured wind speed, the relative error value was in 0.19 to 0.95, the mean relative one reached 0.52. Regression analysis results showed that the correlation coefficient between two of them reached 0.97, and the significance level P<0.01. 2) For the wind speed value >5 m/s, the relative error value between the fitting results and the measured results were 0.01-0.18, and the mean one was 0.09, correlation coefficient reached 0.82, and the significance level P<0.01. The fitting result in the high wind speed area (>5 m/s) was small with a slope of 0.74. 3) The fitting method of daily average and daily maximum wind speed also couldn't be directly applied to estimate wind erosion in North China. However, the wind erosion force fitted by this method had a strong correlation with the results calculated by the measured wind speed (R2=0.96). According to the spatial distribution of wind erosion force in March from 2000 to 2010 calculated by this correlations, areas of high wind factor value were distributed mostly around the Inner Mongolia Plateau, also in the Northeast China and the Qinghai-Tibet Plateau.[Conclusions] Two-parameter Weibull distribution model underestimated the value of wind speed (especially for wind speeds >5 m/s). The wind erosion force calculated by the fitting method of daily average and daily maximum wind speed is correlated with the one from the measured wind speed, thus this correlation can be used to estimate the wind erosion force. Based on comparing the common methods, this paper improved RWEQ model in the calculation of wind factor, revealed climate driver in wind erosion area, and provided a theoretical instruction for control the wind erosion in North China.
巩国丽, 刘鑫, 要玲, 任丽霞, 王敏. RWEQ模型中风因子的改进及应用[J]. 中国水土保持科学, 2021, 19(4): 143-148.
GONG Guoli, LIU Xin, YAO Ling, REN Lixia, WANG Min. Improvement and application of wind factor in RWEQ model. SSWC, 2021, 19(4): 143-148.
FRYREAR D W, SALEH A, BILBRO J D, et al. Revised Wind Erosion Equation (RWEQ)[M].Wind Erosion and Water Conservation Research Unit, Technical Bulletin 1, Southern Plains Area Cropping Systems Research Laboratory, USDA-ARS. 1998:33.
[2]
张俊伟,李春,李倩倩,等.基于风速时间序列分形与传统插值对比研究[J].热能动力工程, 2018, 33(7):122. ZHANG Junwei, LI Chun, LI Qianqian, et al. The contrastive study of fractal and traditional interpolation based on wind speed time series[J].Journal of Engineering for Thermal Enegey and Power, 2018, 33(7):122.
[3]
朱韶峰. 韦伯(Weibull)分布参数估算风能的讨论[J].浙江气象科技, 1985, 6(3):41. ZHU Shaofeng. Discussion on Weibull distribution parameter estimation of wind energy[J]. Journal of Zhejiang Meteorology, 1985, 6(3):41.
[4]
杨维军, 王斌. 二参数Weibull分布函数对近地层风速的拟合及应用[J].应用气象学报, 1999, 10(1):118. YANG Weijun, WANG Bin. Fitting to wind velocity of surface layer using two parameter Weibull distribution function and its application[J].Journal of Applied Meteorological Science, 1999, 10(1):118.
[5]
DONK S J V, WAGNER L E, SKIDMORE E L, et al. Comparison of the Weibull model with measured wind speed distributions for stochastic wind generation[J]. Transactions of ASAE, 2005, 48(2):503.
[6]
郭中领. RWEQ模型参数修订及其在中国北方应用研究[D].北京:北京师范大学, 2012:59. GUO Zhongling. Improvement and application of RWEQ model in North China[D].Beijing:Beijing Normal University, 2012:59.
[7]
梅凡民, 江姗姗, 王涛. 粗糙床面风廓线的转折特征及其物理意义[J].中国沙漠, 2010, 30(2):217. MEI Fanmin, JIANG Shanshan, WANG Tao. The inflected feature of wind profiles over several roughness beds and its implications[J].Journal of Desert Research, 2010, 30(2):217.
[8]
ELLIOT D L. Adjustment and analysis of data for regional wind energy assessments[C].North Carolina:Workshop on Wind Climate, 1979:121.
[9]
BAGNOLD R A. The physics of blown sand and desert dunes[M]. London, UK:Methuen, 1941:64.
[10]
ZINGG A W. Some characteristics of Aeolian sand movement by saltation process[M]. Quai Anatole France, Paris:Editions du centre National de la Recherche Scientifique,1953,7ed:197.
[11]
GREELEY R, IVERSON J D. Wind as a geological process on Earth, Mars, Venus, and Titan[M]. Cambrige:Cambridge Univ. Press, 1985:77.
[12]
SAILOR D J, SMITH M, HART M. Climate change implications for wind power resources in the Northwest United States[J]. Renewable Energy, 2008, 33(11):2393.
[13]
PAVLIK D, SOHL D, PLUNTKE T, et al. Dynamic downscaling of global climate projections for Eastern Europe with a horizontal resolution of 7km[J]. Environmental Earth Science, 2011, 65(5):1475.
[14]
KUROSAKI Y, MIKAMI M. Threshold wind speed for dust emission in east Asia and its seasonal variations[J]. Journal of Geophysical Research, 2007,112(D17):D17202.
[15]
杨兴华, 何清,丁国锋, 等. 塔克拉玛干沙漠腹地风蚀起沙观测试验[J]. 沙漠与绿洲气象, 2000, 6(5):67. YANG Xinghua,HE Qing, DING Guofeng,et al.The study on observation experiment of wind erosion over the Hinterland of Taklimakan Desert[J].Desert and Oasis Meteorology, 2000, 6(5):67.
[16]
周成龙,买买提艾力·买买提依明,杨兴华,等.基于野外试验对临界起沙风速的计算解析[J].干旱气象,2018,36(1):90. ZHOU Chenglong, ALI Mamtimin, YANG Xinghua, et al. Critical threshold velocity of dust emission in Tazhong area based on the parameterization schemes[J]. Journal of Arid Meteorology, 2018,36(1):90.
2021, Vol. 19 
