| 广东省土壤Cd含量空间分布预测 |
| 摘要点击 2679 全文点击 1150 投稿时间：2016-11-01 修订日期：2016-12-02 |
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| 中文关键词 空间分布 土壤Cd含量 广东 Cubist 驱动因子 |
| 英文关键词 spatial distribution soil Cd concentrations Guangdong cubist driving factors |
| 作者 | 单位 | E-mail | | 孙慧 | 山西农业大学资源环境学院, 晋中 030800
广东省生态环境技术研究所, 广东省农业环境综合治理重点实验室, 广州 510650 | 2824414813@qq.com | | 郭治兴 | 广东省生态环境技术研究所, 广东省农业环境综合治理重点实验室, 广州 510650 | | | 郭颖 | 山西农业大学资源环境学院, 晋中 030800
广东省生态环境技术研究所, 广东省农业环境综合治理重点实验室, 广州 510650 | | | 袁宇志 | 广东省生态环境技术研究所, 广东省农业环境综合治理重点实验室, 广州 510650 | | | 柴敏 | 广东省生态环境技术研究所, 广东省农业环境综合治理重点实验室, 广州 510650 | | | 毕如田 | 山西农业大学资源环境学院, 晋中 030800 | birutian@163.com | | 杨静 | 山西农业大学资源环境学院, 晋中 030800 | |
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| 中文摘要 |
| 土壤重金属的空间格局对土壤重金属污染防治具有重要的指导意义.本文以广东省土壤Cd含量为研究对象，基于"规则"模型——Cubist以及样条插值法、反距离加权法、自然邻域法、普通克里金插值法、局部多项式插值法和径向基函数插值法等6种GIS空间插值方法，选取2000、1500、1000、800、500、300、200、150及90 m这9个不同的格网尺度，构建Cd含量空间格局模型.选择不同方法的最佳预测尺度和最优模型参数，预测广东省土壤Cd含量分布.结果表明：1在相同尺度时Cubist方法预测结果都比传统的空间插值结果精度高，格网大小为300 m×300 m时预测精度最高.其次是样条插值法，其在1500 m插值尺度上精度最高；2Cubist模型同时可以识别土壤Cd含量空间分布的驱动因子.结果表明在37个影响Cd含量的自然和人为因子中，地质类型是驱动广东省土壤Cd含量分布差异的主要因子；3Cd含量高值主要分布在珠三角地区及粤北少部分地区.广东省土壤Cd含量超过GB 15618-1995中3级和2级标准，即大于1.0 mg·kg-1和0.3 mg·kg-1的面积分别约为160 km2和2140 km2，约占广东省总面积的0.09%和1.18%. |
| 英文摘要 |
| Heavy metals are one of the principal soil pollution sources. Contaminated soils affect the quality of agricultural products, and then threaten human health. Prediction of the contaminants distribution in the soil is the foundation of pollution evaluation and risk control. A total of 1000 soil profiles were collected to investigate the spatial variation of soil cadmium (Cd) concentration in Guangdong province. These datasets were divided into two groups, about 900 samples for model training and the other 100 for model validation. Six frequently used GIS spatial interpolation methods including Spline, Natural Neighbor, Ordinary Kriging, Inverse Distance Weighted, Local Polynomial Interpolation and Radial Basis Function, and Cubist which is a type of rule-based model were compared to determine their suitability parameters for estimating soil Cd concentration. Nine different resolutions including 2000, 1500, 1000, 800, 500, 300, 200, 150, and 90 m were selected to calculate, evaluate and compare their accuracy. The results showed that, 1 Quantitative assessment of the continuous surfaces showed that there was a large difference in the accuracy of the seven methods. Cubist was superior to GIS-based spatial interpolation methods at all resolutions. Cubist was the best tool for mapping the spatial distribution of Cd in soils with thirty-seven specific predictors relevant to the source and behavior of Cd (parent material, land use, soil type, soil properties, population density, gross domestic product per capita, and the lengths and classes of the roads surrounding the sampling sites, climatic factors, etc.) at 300 m×300 m resolution. The second was Spline, its accuracy was optimal at the 1500 m×1500 m resolution. 2 Results of Cubist suggested that the soil Cd spatial distribution was primarily dependent on the properties of soil regional parent materials. And soil samples with higher Cd concentration mainly located in Carboniferous and Quaternary areas. 3 Spatially, Cd concentrations were higher in the Pearl River Delta region and north of Guangdong Province. Many hotspots existed throughout the Pearl River Delta region due to transportation and pollution of the river. The major anthropogenic inputs of heavy metals to soils and the environment were metalliferous mining and smelting in the north of Guangdong Province. The soil Cd geometric mean concentration of 0.147 mg·kg-1 was lower than that of China, however it varied from zero to 6.056 mg·kg-1. The areas with soil Cd concentrations greater than 1.0 and 3.0 mg·kg-1 were 160 km2 and 2140 km2 respectively, accounting for 0.09% and 1.18% of the total area of Guangdong Province. |
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