In order to ascertain the distribution characteristics of soil heavy metal pollution and main pollution sources in a small watershed in the southern mountainous area of Ningxia and to ensure the quality of the soil environment, the contents of heavy metals Pb, Ni, Zn, Mn, Cu, Cr, and Cd in 260 surface soil samples (0-20 cm) were collected and determined. Based on the soil background value in Ningxia, the soil heavy metal pollution status and potential ecological risk were evaluated through the single factor index, Nemera composite index, and potential ecological risk index, and the method of combining positive definite matrix factor analysis (PMF) and Kriging interpolation was used to analyze the soil heavy metal spatial distribution and source. The results showed that the average contents of ω(Pb), ω(Ni), ω(Zn), ω(Mn), ω(Cu), ω(Cr), and ω(Cd) were 31.42, 36.22, 62.89, 546.18, 22.26, 61.90, and 0.18 mg·kg-1, respectively. Except for Ni, the other elements were higher than the background value of Ningxia but lower than the background value of agricultural soil pollution risk selection criteria and green food environmental quality standards. The Nemera composite index showed that the proportions of mild, moderate, and severe heavy metal pollution were 71.92%, 19.23%, and 1.54%, respectively. The potential ecological risks were mainly minor risks, accounting for 98.85%. In addition, there were a very small number of samples with medium potential ecological risk levels, accounting for 1.15% of the total number of samples. Source analysis showed that the main sources of soil heavy metals in the small watershed in the mountainous area of southern Ningxia were mixed sources of fertilization and industrial emissions (12.6%), agricultural activity sources (23.5%), natural parent material sources (27.6%), mixed sources of pesticide use and mining development emissions (17.7%), and atmospheric deposition sources (18.6%).
Keywords: Ningxia; heavy metals in soil; positive matrix factorization (PMF); potential ecological risk; spatial distribution.