Drinking Water Source Contamination Early Warning System and Modelling in China: A Review

Abstract

– China's fast pace industrialization and growing population has led to several accidental surface water pollution events in the last decades. This has severely affected the safety of large populations downstream whom are dependent of these waters for drinking. In other countries such as the USA, several accidental pollution events have forced these to develop early warning systems (EWSs) for the protection of their drinking water sources. The government of China, in its 11 th Five Year plan, after the 2005 Songhua River incident, has pushed for similar actions. Despite recent government efforts, there are still many weaknesses and gaps in EWS in China such as the lack of pollution monitoring and advanced mathematical models to predict and forecast pollution events. The application of existing physical models for water quality prediction in China can be challenging due to information availability issues. Data Driven Models (DDMs) such as Artificial Neural Networks (ANNs) have acquired recent attention as an alternative to physical models which require large amounts of data, do not take into account nonlinear hydrological properties, are computationally demanding and not always flexible.