江苏省水土流失动态监测降雨侵蚀力因子站点密度优化研究

Study on optimization of site density of rainfall erosivity factor for dynamic monitoring of soil erosion in Jiangsu Province

为进一步提高水土流失动态监测精度,基于江苏省水土流失动态监测现设的74个站点和江苏省水文站网399个降雨监测站点的降雨参数计算降雨侵蚀力,采用克里金插值法获取其空间分布特征,并通过分层抽样、误差对比等方法分析不同站点密度对降雨侵蚀力计算结果的影响,进而探讨研究区的最优站点密度。结果表明:①基于现用水土流失动态监测站点数据计算的降雨侵蚀力(R动)与基于全省总站点数据计算的降雨侵蚀力(R真)在空间分布上大体一致,总体呈从南到北的递减趋势,主要在极值区域存在较大差异;②随着站点密度增加,R_(动)与R_(真)的结果差异减小,降雨侵蚀力计算精度增加,在站点数从200增加为300时,差异显著减小;③基于优化站点(287个)计算的降雨侵蚀力(R_(287))与基于全省总站点数据计算的降雨侵蚀力(R_(真))的空间分布趋势基本一致,差异较小。根据研究区降雨量数理特征,采用样本量公式计算得到最优站点数量为287个。

In order to further improve the dynamic monitoring accuracy of soil erosion,the rainfall erosivity was calculated based on the rainfall parameters of 74 existing sites of dynamic monitoring in Jiangsu Province and 399 monitoring stations in Jiangsu hydrology network,kriging interpolation method was used to obtain its spatial distribution characteristics,the influence of different site densities of rainfall erosivity was analyzed by the methods of stratified sampling and error comparison,then the optimal site density in the study area is discussed.The result shows that:①Rainfall erosivity calculated based on the data of current soil erosion dynamic monitoring station(R_(dynamic))and rainfall erosivity calculated based on total site data of the whole province(R_(real)),their spatial distributions are generally consistent,there is a decreasing trend from south to north,and there are great differences mainly in the extreme value region.②As site density increases,the difference between Rdynamic and Rreal decreases,the computational accuracy of rainfall erosivity increases,and the difference decreases significantly when the number of stations increases from 200 to 300.③The spatial distribution trend of rainfall erosivity calculated based on the(287)optimized sites(R_(287))is basically the same as that of rainfall erosivity calculated based on the total sites of the whole province(Rreal),with little difference.According to the mathematical characteristics of rainfall in the study area,the optimal number of stations is calculated as 287 by using the sample size formula.