Groundwater pollution early warning based on QTR model for regional risk management: A case study in Luoyang city, China

摘要

Groundwater pollution early warning has been regarded as an effective tool for regional groundwater pollution prevention, especially in China. In this study, the systemic model was established to assess the groundwater pollution early warning by integrating the present situation of groundwater quality (Q), groundwater quality trend (T) and groundwater pollution risk (R). The model integrated spatial and temporal variation of groundwater quality, and combined the state and process of the groundwater pollution. Q, T and R were assessed by the methods of fuzzy comprehensive assessment, Spearman or nonparametric Mann-Kendall trend test, and overlay index, respectively. Taking the Luoyang City as an example, the groundwater pollution early warning mapping was generated, and verified by corresponding the groundwater quality classes and the early warning degrees. The results showed that the groundwater was dominated by the levels of no warning and light warning, which accounted for 77% of the study area. The serious and tremendous warning areas were affected by the worse trend and relatively bad/bad present situations of groundwater quality with the typical contaminants of total hardness, nitrate, Hg and COD. In summary, the present situation of groundwater quality was the most important factor of groundwater pollution early warning mapping in the study area. The worse trend of groundwater quality played equally a key role in the local regions, as well as the high pollution risk, which was mainly affected by the pollution source loading. Targeted measures for groundwater pollution prevention were proposed in the corresponding degrees of groundwater pollution early warning. The QTR model was proved to be effective for assessing the regional groundwater pollution early warning. The accuracy of the model could be improved if there is further data acquisition of groundwater quality in longer time series and in larger number, and further investigation of pollution sources.The QTR model is proposed and proved to be effective for assessing regional groundwater pollution early warning. (C) 2020 Elsevier Ltd. All rights reserved.