基于地理探测器的农田土壤重金属影响因子分析

发布时间：2018-04-30 23:40

本文选题：地理探测器 + 土壤重金属　；参考：《中国农业科学》2017年21期

【摘要】：【目的】研究土壤重金属与影响因子以及不同土壤重金属之间相关关系,为土壤重金属空间预测模型提供更加全面的辅助变量。【方法】利用地理探测器模型,结合空间插值技术对2014年湖南省湘潭县5个乡镇农田中5种土壤重金属Pb、Cd、As、Cr和Hg的空间分布变化与6种影响因子以及5种土壤重金属之间的相关性和交互作用进行研究。【结果】研究结果表明,GDP、平均温度和相对湿度对5种土壤重金属解释力较大(PD,H值均在0.5以上),土壤pH、土壤类型与高程对土壤重金属的解释力较小(PD,H值均在0.3以下),其中土壤类型对于5种土壤重金属的解释力最低(PD,H值均在0.1以下)。5种土壤重金属中,Cr对Cd的解释力最强(PD,H值达到0.95),As对Cd的解释力最小(PD,H值仅为0.20)。平均温度、相对湿度、GDP对土壤重金属的影响显著高于其他影响因子,而其他影响因子之间的解释力差异并不显著。各影响因子之间和5种重金属元素之间均具有相互增强或非线性增强作用。【结论】土壤重金属的空间分布是由多种影响因子共同作用的结果。通过地理探测器模型发现,GDP、平均温度和相对湿度等影响因子对研究区域内的土壤重金属的空间分布具有较强的解释力,这些影响因子可作为研究区土壤重金属空间预测模型的辅助变量。地理探测器模型可以对多种影响因子进行更加全面的分析,为土壤重金属空间预测模型的建立提供有效的依据。
[Abstract]:[objective] to study the correlation between soil heavy metals and influencing factors and different soil heavy metals, so as to provide a more comprehensive auxiliary variable for spatial prediction model of soil heavy metals. [methods] Geo-detector model was used. Combined with spatial interpolation technique, the spatial distribution of five soil heavy metals, PbcCdCdAsC, Cr and Hg, and the correlation and interaction among the five heavy metals in five villages and towns in Xiangtan County, Hunan Province in 2014 were studied. [results] the results showed that GDP, mean temperature and relative humidity had greater interpretive power on 5 kinds of soil heavy metals than 0.5, pH of soil, soil type and height were lower than that of soil. Among the 5 kinds of heavy metals in soil, soil type has the lowest explanatory power (PDH) and the lowest PDH value (P < 0. 5). Among all the heavy metals below 0. 1, Cr has the strongest interpretive power to CD, the PDN H value is 0. 95%, and the lowest PDN H value is only 0. 20% (P < 0. 05). The effects of average temperature and relative humidity GDP on soil heavy metals were significantly higher than those of other factors, but there was no significant difference in the explanatory power among other factors. The spatial distribution of heavy metals in soils is the result of the interaction of various factors. [conclusion] the spatial distribution of heavy metals in soils is the result of the interaction of many factors. [conclusion] the spatial distribution of heavy metals in soils is the result of the interaction of many factors. It is found that the GDP, average temperature and relative humidity have a strong explanatory power on the spatial distribution of heavy metals in the soil of the study area. These factors can be used as auxiliary variables of spatial prediction model of heavy metals in soil. The geo-detector model can be used to analyze the influence factors more comprehensively and provide an effective basis for the establishment of spatial prediction model of soil heavy metals.
【作者单位】：三峡大学计算机与信息学院;北京市农林科学院北京农业质量标准与检测技术研究中心;
【基金】：国家公益性行业(农业)科研专项(201403014-04) 国家高技术研究发展计划项目(2013AA102302)
【分类号】：S153

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