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Smart water is an important part of smart cities. The rational allocation of water resources is one of the most significant step in smart water systems. How to predict the future index data accurately and quickly is particularly critical in the scheduling process. Through the study of the smart water supply model, the application scheme of the forecasting model is put forward, and the rationality of the forecasting model in the project is verified. In the study of forecasting model, the classical mean GM (1,1) model is used to predict the water flow series firstly. On this basis, Markov chain is introduced to analyze and predict the errors of GM (1,1) model by using single-step and multi-step weighting, and the results are corrected. Finally, MATLAB was used to calculate and simulate the three methods. The comparison results show that the combination of Markov chain and GM (1,1) model has a greater improvement in prediction accuracy than the simple GM (1,1) model. The Markov chain after weighting is also improved in accuracy compared to the single-step prediction state.