Stochastic modeling of river water quality and risk analysis

In practice, caused by external environmental factors influence in the process of river water movement, the river hydrology and water quality characteristics show uncertainty to a large extent. Aiming at the periodicity and randomness feature of hydrological processes, a stochastic water quality model of river is established taking hydrological monthly runoff as random variables and considering three parameters impact including river hydraulics, hydrology and water quality at the same time. This paper explores a formulated stochastic method for river water quality simulation in Huainan reach of Huai River, China, under various hydrological processes and indefinite input of point source pollution conditions. The Gaussian distribution model and stochastic water quality simulation are used to predict spatial and temporal distribution of pollutant concentration with uncertain hydrological process in mind, three discharge scenarios are investigated. The study indicates two results: (1) the impact degree on BOD is proportional to the input BOD strength. (2) The river with higher initial BOD concentration is more sensitive to the input BOD change. Finally, we focus on the case in which the input BOD concentration has been increased. Water pollution risk of the river downstream in different period is calculated and predicted so as to provide a theoretical basis for river pollution prevention and environmental protection. It was helpful to assess pollution risk or its probability of river under uncertain exoteric influences.