洞庭湖平原区土壤全磷含量地统计学和GIS分析

Geostatistical and GIS Analyses on Soil Total P in the Typical Area of Dongting Lake Plain

以洞庭湖平原区典型景观单元为试点,利用GPS定位共取得651个耕层(0～20cm)土壤样品。通过对数转化、稳健统计、域法处理和Box-Cox转化4种数据处理方法对土壤全磷进行了正态分布性检验。结果表明,Box-Cox转化成功地使数据集服从正态分布并消弱了异常值的影响,应用地统计学分析方法进行了实验变异函数的计算和最适合模型的拟合,得出土壤全磷最好的理论模型为球状模型,随后用普通克立格估值方法绘制了土壤全磷的空间分布图。在经过不同趋势阶数土壤全磷克立格(Kriging)插值误差的综合比较的基础上,结果表明趋势效应参数宜选取二阶。Kriging估值标准差(KSD)被认为是内插象素值的标准差,并为提高全磷的制图精度提供了有用的信息。应用地统计学和地理信息系统(GIS)的概率克立格法研究了洞庭湖平原典型区的土壤全磷的空间分布并进行了风险性评价。结果表明,土壤全磷不同含量水平下的概率分布图对风险性评价、合理施肥和控制磷素的面源污染的管理实践将是十分有益的。

A typical landscape unit of Dongting Lake plain was selected as an experimental site. Approximate grid approaches were employed for the sampling scenario in 2004 with 651 Global Position System (GPS) established spots sampled in topsoil (0-20 cm). The purpose of this study is to evaluate various data processing methods, including logarithmic transformation, robust statistics, excluding outliers and Box-Cox transformation for evaluating soil total P content with normal distribution. The result showed that Box-Cox transformation was applied in order to achieve normality in the data set and to dampen the effect of outliers. Geostatistical analyses were carried out, including calculation of experimental variograms and model fitting. The best theoretical model for semivariogram of soil total P were spherical model. The ordinary kriging estimates of soil total P concentration were mapped. The integrative comparisons of semivariogram parameters with different trends of the kriging prediction errors of soil total P indicated that the 2-order trend effect was preferable. Kriging standard deviations (KSD) were regarded as the standard deviations of the interpolated pixel values and provided valuable information for which will increase the accuracy of the total P mapping. Spatial distribution and hazard assesment of soil total P in the typical area of Dongting Lake plain were investigated using geostatistics and geographic information system (GIS) techniques such as probability kriging on the basis of the software ArcGIS Desktop. Probability distribution of soil total P at different levels will be helpful to conduct hazard assessment, optimal fertilization and develop manage ment practices to control the non-point sources of P pollution.