Time series prediction of heavy metal contamination in mining areas based on exponential smoothing model

Abstract

Heavy metal contamination in mining areas has the features of time series, so it can be predicted with exponential smoothing model. On the basis of 1995–2007 monitoring data of Copper (Cu) at the surface water monitoring point 500m to the downstream of the sewage outlet in a copper ore, with cubic exponential smoothing method, the predicting model of heavy metal Cu is established through selecting different smoothing coefficient a. After applying the predicting model to predicting the content of Cu in the wastewater 500m to the sewage outlet from 2005 to 2007, it is found that the error of comparing the predicted result with correspondent actual monitoring values is less than 5%, which satisfies the requirements after testing. The predicting result shows that the mining area will be still in the contamination of Cu in the future.