Influence factor analysis of farmland soil heavy metal based on the geographical detector

Abstract

[Objective]To study the correlation between soil heavy metals and influencing factors and heavy metals in different soils, as well as to provide a more comprehensive auxiliary variable for soil heavy metal spatial prediction model.[Method]The spatial distributions of heavy metals Pb, Cd, As, Cr and Hg in five soils in five towns of Xiangtan County, Hunan Province were analyzed by using the geophysical model and the spatial interpolation technique. The correlation and interaction of spatial distributions of heavy metals and 6 factors, as well as that of five heavy metals, were studied.[Result]The results showed that Gross Domestic Product (GDP), the average temperature and relative humidity had a greater explanatory power to the five kinds of soil heavy metals to (PD,H values are above 0.5). Soil pH, soil type, elevation and soil heavy metals were less explanatory (PD,H values below 0.3). The soil type had the lowest explanatory power to five kinds of soil heavy metals (PD,H values were below 0.1). Among the five soil heavy metals, Cr has the strongest explanatory effect on Cd (PD,H = 0.95), and As is the least (PD,H = 0.20). The effects of average temperature, relative humidity and GDP on soil heavy metals were significantly higher than those of other Influence factors, while the difference of explanatory power between other influence factors was not significant. There are mutually reinforcing or non-linear enhancement effects between the Influence factors and between the five heavy metal elements. [Conclusion]The spatial distribution of heavy metals in soil is the result of the interaction of multiple influence factors. Based on the geographical exploration model, the Influence factors, such as GDP, average precipitation, average temperature and relative humidity, have strong explanatory power for the spatial distribution of heavy metals of research area in soils. These influence factors can be used as the soil heavy metal space in the study area predictive model of the auxiliary variable. Geographic detector model can provide a more comprehensive analysis of various influence factors, and provide an effective basis for the establishment of soil heavy metal spatial prediction model.