Visual platform for water quality prediction and pre-warning of drinking water source area in the Three Gorges Reservoir Area

Abstract Water, an essential resource in the ecosystem, is the basis for the survival of life on earth and determines the destiny of mankind. To deal with water resources problems, water quality prediction models and pre-warning platforms have become important means of water resources safety monitoring and essential guarantee for sustainable development in the world today. Since the Three Gorges Reservoir Area has many drinking water source areas, the water quality prediction and early warning platform should be developed, through this way the drinking water safety of the reservoir area can be guaranteed. In this study, a new two-dimensional water quality prediction sub-model was developed by processing and integrating two-dimensional water quality and quantity control equation and digital elevation model (DEM) through Geographic Information System (GIS) platform and FORTRAN language. Meanwhile, the Three Gorges Reservoir Area water quality warning sub-model was constructed, on the basis of the current situation of hydrology and water quality in the Three Gorges Reservoir Area (TGRA), then it combined with the water quality prediction sub-model (after processing by TecPlot 360), a visual platform was developed for the prediction and warning of drinking water quality in the reservoir area. To verify the accuracy and applicability of the platform, the predicted values of various pollutants were compared with the measured values and it was applied to predict and warn hexavalent chromium pollution accident. Under the assumed accident conditions, the pollutants were mainly concentrated on the side of the pollution source for diffusion, and that the migration rate of pollutants was positively correlated with the water level and quantity. The duration of pollution accidents in the four water periods was 31 min in drought period, 28 min in decline period, 25 min in storage period and 24 min in flood period. The results showed that the platform was feasible in operation, and the prediction and pre-warning of pollution accidents were scientific. This research provided a new tool for drinking water management, guaranteed water quality safety and people's health in the reservoir region and achieved sustainable development.