The invention discloses a support vector regression-based stratified reservoir water intake discharge water temperature prediction model and prediction method, and the method comprises the steps: firstly carrying out principal component analysis of the reservoir water temperature, the reservoir water level, the stoplog gate elevation, the reservoir flow, the outflow flow, the air temperature, the temperature chain vertical water temperature distribution, and the like; and taking the principal component with the total contribution rate greater than 99% as an input feature vector, and predicting the discharged water temperature through the trained support vector regression model. The influence of the reservoir water temperature, the reservoir water temperature distribution, the reservoir flow, the outflow flow, the reservoir water level, the air temperature and the stoplog gate elevation on the discharged water temperature and the interaction of all the influence factors are comprehensively considered, dimensionality reduction is conducted on data, and accurate prediction of the discharged water temperature is achieved on the basis of the support vector regression method. The invention is not limited by regions, can be carried out in the aspects of reservoir water temperature management, reservoir downstream ecological environment protection and the like, provides technical support for a reservoir operation scheduling scheme, can also carry out visual operation, and has a relatively good application prospect.