| 基于地理探测器和多源数据的耕地土壤重金属来源驱动因子及其交互作用识别 |
| 摘要点击 1558 全文点击 465 投稿时间：2022-05-17 修订日期：2022-07-05 |
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| 中文关键词 耕地土壤 重金属 多源数据 地理探测器 驱动因子 可塑性面积单元问题 |
| 英文关键词 farmland soil heavy metals multi-source data geodetector driving factor modifiable areal unit problem |
| 作者 | 单位 | E-mail | | 张宏泽 | 贵州师范大学地理与环境科学学院, 贵阳 550025
贵州省山地资源与环境遥感应用重点实验室, 贵阳 550001 | 193972589@qq.com | | 崔文刚 | 贵州师范大学地理与环境科学学院, 贵阳 550025
贵州省山地资源与环境遥感应用重点实验室, 贵阳 550001 | 849028074@qq.com | | 刘绥华 | 贵州师范大学地理与环境科学学院, 贵阳 550025
贵州省山地资源与环境遥感应用重点实验室, 贵阳 550001 | | | 崔瀚文 | 贵州师范大学地理与环境科学学院, 贵阳 550025
贵州省山地资源与环境遥感应用重点实验室, 贵阳 550001 | | | 黄月美 | 贵州师范大学地理与环境科学学院, 贵阳 550025
贵州省山地资源与环境遥感应用重点实验室, 贵阳 550001 | |
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| 中文摘要 |
| 明确耕地土壤重金属来源对土壤健康合理管护及其可持续发展至关重要.利用正定矩阵因子分解（PMF）模型源解析结果（源成分谱和源贡献）、历史调查数据和时序遥感数据，整合地理探测器（GD）、最佳参数地理探测器（OPGD）、空间关联探测器（SPADE）和空间关联交互探测器（IDSA）模型，探讨了土壤重金属来源空间分层异质性研究中可塑性面积单元问题（MAUP），分别识别了分类变量和连续变量中控制土壤重金属来源空间分异的驱动因子及其交互作用.结果表明，中小尺度下土壤重金属来源的空间分异性研究受空间尺度影响，0.08 km2能够作为区域土壤重金属来源空间分异性探测的可选空间单元.连续变量受空间相关性与离散化水平影响，分位数法和中断数为10的离散化参数组合能够减少连续变量在土壤重金属来源空间分异性探测中所受分区效应的影响.分类变量中地层（PD 0.12~0.48）控制土壤重金属来源空间分异，地层和流域的交互作用对各来源解释力为27.28%~60.61%，各来源的高风险区域分别分布在地层中的下震旦系、上白垩系、土地利用中采矿用地和土壤种类中典型强淋溶土区域.连续变量中人口（PSD 0.40~0.82）控制土壤重金属来源空间分异，连续变量的空间组合对各来源解释力为61.77%~78.46%，各来源的高风险区域分别分布在蒸腾量（41.2~43 kg ·m-2）、距河流距离（315~398 m）、增强型植被指数（0.796~0.995）和距河流距离（499~605 m）区域.研究结果为耕地土壤重金属来源驱动因子及其交互作用的相关研究提供参考，为喀斯特地区耕地土壤健康合理管护及其可持续发展提供重要的科学依据. |
| 英文摘要 |
| The identification of heavy metal sources in farmland soils is essential for the rational health condition management and sustainable development of soil. Using source resolution results(source component spectrum and source contribution)of a positive matrix factorization(PMF)model, historical survey data, and time-series remote sensing data, integrating a geodetector(GD), an optimal parameters-based geographical detector(OPGD), a spatial association detector(SPADE), and an interactive detector for spatial associations(IDSA)model, this study explored the modifiable areal unit problem(MAUP) of spatial heterogeneity of soil heavy metal sources and identified the driving factors and their interacting effects on the spatial heterogeneity of soil heavy metal sources in categorical and continuous variables, respectively. The results showed that the spatial heterogeneity of soil heavy metal sources at small and medium scales was affected by the spatial scale, and the optional spatial unit was 0.08 km2 for detecting spatial heterogeneity of soil heavy metal sources in the study region. Considering spatial correlation and discretization level, the combination of the quantile method and discretization parameters with an interruption number of 10 could be implied to reduce the partitioning effects on continuous variables in the detection of spatial heterogeneity of soil heavy metal sources. Within categorical variables, strata(PD 0.12-0.48) controlled the spatial heterogeneity of soil heavy metal sources, the interaction between strata and watersheds explained 27.28%-60.61% of each source, and the high-risk areas of each source were distributed in the lower sinian system, upper cretaceous in strata, mining land in land use, and haplic acrisols in soil types. Within continuous variables, population (PSD 0.40-0.82) controlled the spatial variation in soil heavy metal sources, and the explanatory power of spatial combinations of continuous variables for each source ranged from 61.77% to 78.46%. The high-risk areas of each source were distributed in evapotranspiration (41.2-43 kg·m-2), distance from the river (315-398 m), enhanced vegetation index (0.796-0.995), and distance from the river (499-605 m). The results of this study provide a reference for the research of the drivers of heavy metal sources and their interactions in arable soils and provide an important scientific basis for the management of arable soil and its sustainable development in karst areas. |
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