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Soil erosion is a main problem in sloping vineyards, which can dramatically affect soil quality and fertility. The present study aimed to evaluate the spatial patterns of selected physico-chemical soil characteristics and the soil’s potentially toxic element (PTE) contents in the context of erosion. The study was conducted in a 0.4 ha vineyard plot on a steep slope in Tállya, part of the wine-growing region of Tokaj-Hegyalja (Hungary). A total of 20 topsoil samples (0-10 cm) were collected and analysed for PTEs (B, Co, Ba, Sr, Mn, Ni, Cr, Pb, Zn, and Cu), soil pH (deionized water and KCl solution), particle-size distribution, soil organic matter (SOM), (nitrate+nitrite)-N, P2O5, and carbonate content. Among the selected PTEs, only Cu (125±27 mg/kg) exceeds the Hungarian standards set for soils and sediments (75 mg/kg) due to the long-term use of Cu-based pesticides in the vineyard. Examined PTEs are negatively correlated with the sand content of the topsoil, except for Mn, while the significant positive relationship with the clay content shows the role of clay in retaining PTEs in soil. SOM seems to play a minor role in binding PTEs, as Cu is the only element for which a significant correlation with the SOM content can be detected. The spatial distribution maps prepared by inverse distance weighting (IDW) and lognormal kriging (LK) methods show higher PTE contents at the summit and the shoulder of the hillslope and lower contents at the backslope and the footslope zones. The low slope gradients (0-5 degree) and the high contents of the coarse fraction (> 35%) likely protect the soil at the summit and the hillslope’s shoulder from excessive erosion-induced losses. While the reraising PTE contents at the toeslope are likely due to the deposition of fine soil particles (silt and clay). The highest SOM contents at the summit and the toeslope areas, and increased contents of the coarse fraction at the backslope, confirm the effects of soil erosion on the spatial distribution patterns of main soil quality indicators. Overall, the LK outperformed the IDW method in predicting the soil parameters in unsampled areas.