Development of interval transient pollution distribution model and its application in the Fenghuangshan drinking water source

Abstract

For the purpose of studying the spreading regularity of metal pollution accident and resolving problem of parameters being difficult to obtain in the drinking water source, interval transient pollution distribution model was developed and applied to the Fenghuangshan drinking water source, Three Gorges Reservoir. After parameter calibration and model validation, the mean absolute deviation between the calculated value (data obtained by the model simulation) and the measured value (the real measured data of the Zigui drinking water source area) was less than 7%. Thence, the promoted model can be used in practical accident pollution. Relying on MATLAB 2014a, this research presented the cadmium pollution-spreading pattern in the drinking water source based on the proposed model. Under the premise of different hydrological periods and different initial pollutant quality, this study focused on forecasting and analyzing the spatial distribution of pollution accident within one hour, concentration diffusion of pollution source change with time and concentration diffusion in the drinking water source with time. The results showed that the variation of cadmium concentration was influenced by the distance between the accidental emission source and shore. Specifically, the distance increases, and the appearance of the second pollution peak is subsequently delayed. Moreover, the dilution rate of pollutant was directly proportional to water depth and flow velocity, and the flow velocity has more important influence on the diffusion of pollutants than others do. The purpose of this study is to develop an effective model to forecast and solve the metal pollution accident in drinking water sources under the condition of incomplete or uncertain parameters in order to solve the problem of difficult hydrological data acquisition. The results provide some new insights and references for researchers and decision makers to predict and respond to emergency accident pollution in drinking water sources.