FRYBERGER输沙势计算方法及其估算值偏差分析——以塔克拉玛干沙漠为例

Magnitude deviations of sand drift potential calculation in the‘FRYBERGER'model:a case of the Taklimakan Desert

以塔克拉玛干沙漠地区2007年5个观测站及策勒站2007-2013年逐时观测数据为例,详细介绍了FRYBERGER输沙势计算方法和步骤,并对输沙势含义和易混淆的问题进行了解释说明。基于输沙势公式定义输沙势基准值,通过比较FRYBERGER输沙势估算值与基准值之间的差异,分析了不同观测点之间年均输沙势及其各风级输沙势分量的估算偏差。结果表明:(1)风速观测值的平均时距愈短,风速脉动性作用愈显著,导致输沙势计算值偏大。(2)输沙势的贡献率主要集中于I、II风级,其分布形态不同于起沙风频数分布。(3)FRYBERGER方法估算各测站年均输沙势时,采用FRYBERGER风速中间值产生的估算偏差最小。(4)输沙势估算偏差具有区域和年际性变化(策勒站为例)。(5)各风级风速代表值对输沙势分量的估算偏差产生影响,其最佳组合随观测点和年份而变化;采用最佳组合可有效减小输沙势估算偏差。

Sand drift potential is a useful index for assessing the wind-energy of blown sand,which plays an important role in the formation of aeolian landforms. The FRYBERGER method provides a simple and practical model to evaluate the value of drift potential（DP）from measurements of wind velocity. That is,without the actual measurements or even the wind records in different types,using the statistical wind data,such as the representative velocity value corresponding to each wind class and the time wind blew expressed as percentage,also can calculate the DP values. Another is that the model offers a standard for assessing the wind-energy of blown sand,which is widely used in various regions. Unfortunately,there is still some doubt about the process of DP calculation,and it would influence the accuracy of DP. Thus,on the basis of the varied wind data recorded hourly from five sites in Taklimakan Desert in 2007 and Cele site at Qira County,Xinjiang,China in 2007-2013,the clarification of some confusion about DP is given with the example calculations of using FRYBERGER method. Whereas the accuracy of the DP values and its differences between wind velocity-type calculated in FRYBERGER model are required for each site.Then,the most precise values of DP calculated from the definition-based method are expressed as the reference values（DP＊）,the annual DPs at the five sites and their components corresponding to each wind class are estimated to compare the different deviations of DP from the DP＊ distinguished by local sites and wind velocity classes. The results show as follows：（1）For the types of wind velocity recorded as different time-averaged mean values,it appears that the shorter of the time-interval is,the higher of the wind mean velocity becomes. Because the impact of wind impulse on sand drift has been improved,by which the evaluated DPs are enlarged relatively. Such as in Cele site,compare the DP＊ calculation of two minutes-averaged mean values to ten minutes,the former has increased by 4.7%.（2）The distribution of annual DP values with respect to each wind-class is different from the wind events distribution,the major components of annual DPs are provided by the low-energy winds,which is classified as the grade I and II with FRYBERGER＇s scale.（3）In FRYBERGER model,the representative velocity value corresponding to each wind class is an important factor that directly influences the accuracy of DP calculations. For the annual DPs in the region,it is only the type of FRYBERGER＇s mid-point values that approach to the smallest deviations among the three types of representative velocities,i.e. mid-point values,modified mid-point values,and arithmetical mean values,and it is selected as the best-fit representative values. While for the annual DPs in different years in Cele,using the FRYBERGER＇s mid-point values as the best-fit representative velocities can reduce the deviations of DP values except for 2013. Additionally,the best-fit representative velocity to calculate the annual DP values corresponding to each wind-class is different both in various sites and years.（4）The best-fit values of the representative velocity not only vary with wind classes,also vary with locations. Here,with the aggregation of best-fit values for each wind class corresponding to each site,the DP calculations have been improved obviously.