Spatial Zoning Based on Spatial and Temporal Soil Heavy Metal Changes in Geological High Background Areas

Zhiheng Qin, Li Li and Xiuqin Wu ()
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Zhiheng Qin: School of Soil and Water Conservation, Beijing Forestry University, Beijing 100091, China
Li Li: Department of Agricultural Land Ecological Environment Supervision Technology, Technical Centre for Soil, Agriculture and RuraI Ecology and Environment, Ministry of Ecology and Environment, Beijing 100012, China
Xiuqin Wu: School of Soil and Water Conservation, Beijing Forestry University, Beijing 100091, China

Land, 2025, vol. 14, issue 4, 1-17

Abstract: Soil heavy metal content varies greatly in areas with high geological background, and the commonly used spatial interpolation analysis methods have low accuracy. In order to improve the accuracy of simulation, we selected a typical karst area in Southwestern China as the study area, where 290 soil sampling points were collected, including historical points, surface samples, deep samples, and bedrock samples. Compared to 30 years ago, the average cadmium content at the same location has increased by 326%, while mercury content has decreased by 29%, arsenic content has decreased by 24%, and the changes in lead and chromium content are relatively low. Through comparison of multiple spatial interpolation methods, Inverse distance weighting model (IDW) was used for mercury, while Kriging was used for other metals. The surface cadmium content was relatively high, with mild accumulation accounting for 42.5% or above, and cadmium content is influenced by both parent material and human activities. The mild accumulation rate of arsenic is 5%, concentrated in the central part of the study area. The spatial distribution pattern of lead and chromium in the surface layer is consistent, but chromium content is higher in the deep layer. Mercury content is very low in soil layers, and consistent conclusions were obtained from the longitudinal profile analysis of rock sampling points. The coefficient of variation in each sub-region based on Mean of Surface with Nonhomogeneity model (MSN) partitioning is significantly lower than that of the entire study area, which is related to the differences in dominant factors of soil heavy metal content in each region. The research results can provide a new method for precise risk assessment of soil heavy metal content in areas with abnormal heavy metal content such as karst soils.

Keywords: soil heavy metals; spatial interpolation analysis; MSN; karst area (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2025
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