Abstract: The river water environment system is a system with many uncertainties. The risk assessment quantifying the influence of uncertainties on river water quality have been paid attention to widely. However, the most of research on risk assessment for river water quality confined to quantify stochastic uncertainty of the river water environmental system using the method of statistics. The research on quantifying the risk due to grey uncertainty of the river water environmental system is done less. Based on the theory of probability and grey system approach, the concepts of grey probability, grey probability distribution, grey probability density, grey expectation and grey variance are defined in this paper. The concept of grey-stochastic risk for water quality concentrations exceeding the standard values is presented to quantify the influence of stochastic uncertainty and grey uncertainty on river water quality. The assessment models of grey-stochastic risk for water quality concentrations exceeding the standard values are established. In the assessment model for the individual parameter, the contaminant concentration is modeled as a random variable with a grey probability distribution and the risk for contaminant concentration exceeding the standard value is expressed with grey probability-the grey-stochastic risk for water quality concentrations exceeding the standard values. In the model of comprehensive assessment for multiple parameters, the river water environmental system is considered as the reliability system to undertake useful function, and the result that the concentration of anyone of water quality parameters exceeds the standard value shows that the useful function of river water environmental system cannot be guaranteed. Lastly, the comprehensive risks for water quality concentrations exceeding the standard values are computed by using the approach of reliability system. An example of application to evaluate the grey-stochastic risks for heavy metals concentrations exceeding the standard values in the Yellow River at the Huayuankou section is given. The results provide more information and are satisfactory.