The mapping of heavy metal distribution is usually associated with certain uncertainty that needs to be considered in decision making for heavy metal pollution management.The uncertainty in prediction of heavy metal contents at unsampled lo cations is part icularly important because such uncertainty can be propagated into subsequent modelling or decision making process and has fundamental impacts on ultimate results.Based on the Cu content data of a total of 547 topsoil (0~15 cm) samples in Zhangjiagang City,the sequential indicator simulation (SIS) were applied to perform a conditional stochast ic simulation in this study to quantitatively assess the uncertainty of mapping total Cu content.Results show that prediction of the spatial pattern of soil Cu fluctuated the most in the eastern and central northern parts of the study area,where intensive agriculture and metallurgic and electronic enterprises dominate and the total Cu contents were high,and the least in the southern part,where the total Cu contents were low.The pattern simulated with SIS did not show any smoothing effect.With a given threshold of Cu content,SIS can quantitatively assess both local uncertainty and spatial uncertainty of Cu content that is greater the threshold.