Purpose

Establishing the spatial distribution of soil properties in agro-ecosystems is critical to increasing the productivity of intensive tillage soils and reducing environmental pressure. Thus, a comprehensive understanding of soil’s heavy metal distribution characteristics is important for optimal management. The goal of this study was to determine the most accurate soil Cd interpolation method for the study area and analyze the variation and spatial distribution of Cd content with depth.

Materials and methods

In this work, we employed two common spatial interpolation methods—inverse distance weighting (IDW) and radial basis function (RBF)—in conjunction with a geographic information system (GIS) to interpolate sampling data of the heavy metal cadmium (Cd) throughout Santai County; a locale in the lower part of Fujiang River, Mianyang, in the northeast of Sichuan Province.

Results and discussion

The results of our investigation are as follows. (1) At depths of 0–50 cm, the Cd content decreased with depth while the coefficient of variation (Cv) increased with depth. The exponential model and the Gauss model adequately described the Cd content’s spatial autocorrelation and the determination coefficient (R²) varied within 0.747–0.962, indicating that the model had high precision. (2) With respect to the accuracy of the IDW and RBF methods, IDW was more accurate than the RBF in the 0–20 cm soil layer, yet the reverse was found in the 20–50 cm soil layer. (3) Three-dimensional spatial distribution maps—constructed using the RBF and IDW methods at different soil depths—showed that the RBF method provided a greater smoothing effect than the IDW method.

Conclusions

The spatial variability of soil Cd content shows that: (1) the Cd content’s spatial autocorrelation was strong in the 0–50 cm soil layer. (2) The IDW method is suitable for areas that are greatly influenced by human or farming activities while the RBF method is appropriate for areas that are greatly influenced by internal soil factors. The RBF is superior for evaluating the spatial distribution of soil Cd content in this area.

中文翻译：

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基于IDW和RBF的绵阳Fujian江土壤镉含量的空间变异性

目的

在农业生态系统中建立土壤特性的空间分布对于提高集约耕作土壤的生产力和降低环境压力至关重要。因此，全面了解土壤的重金属分布特征对于优化管理很重要。这项研究的目的是确定研究区域最准确的土壤Cd插值方法，并分析Cd含量随深度的变化和空间分布。

材料和方法

在这项工作中，我们采用了两种常见的空间插值方法-反距离权重（IDW）和径向基函数（RBF）-结合地理信息系统（GIS）来插值整个三台市重金属镉（Cd）的采样数据县; 位于四川省东北部绵阳市Fujian江下游的一个地区。

结果和讨论

我们的调查结果如下。（1）在0–50 cm深度处，Cd含量随深度而降低，而变异系数（Cv）随深度而增加。指数模型和高斯模型充分描述了Cd含量的空间自相关，其测定系数（R ²）在0.747-0.962之间变化，表明该模型具有较高的精度。（2）关于IDW和RBF方法的准确性，IDW​​在0–20 cm土层中比RBF更准确，但在20–50 cm土层中却相反。（3）使用RBF和IDW方法在不同土壤深度下构建的三维空间分布图表明，RBF方法比IDW方法具有更大的平滑效果。

结论

土壤Cd含量的空间变异性表明：（1）0-50 cm土层中Cd含量的空间自相关性强。（2）IDW方法适用于受人类或农业活动影响较大的区域，而RBF方法适用于受内部土壤因素影响较大的区域。RBF在评估该地区土壤Cd含量的空间分布方面具有优势。