The current study presents an efficient method for deriving precise operation rules from all subsystems of a distributed conjunctive use system (CUS), including aquifer, river, and reservoir. Distributed aquifer simulation has been performed using the URM method. Given that the historical flow time series can only represent one of the possible situations in the future and its use to determine the performance of the CUS is certainly not very reliable, in this study, river flow uncertainties are implicitly considered. To develop the operation rules, the time series of river flow were generated using autoregressive model. Then, the operation optimization model of the system was implemented with the objective function of minimizing water shortage for different river flow time series. 70% of the data was used for model training and 30% for model validation. Finally, using the decision tree algorithm (M5Rules), the conditional operation rules were extracted and compared with the single linear regression operation rules. Using five efficiency criteria CC, MAE, RMSE, RAE, and RRSE, the comparison of conditional and single linear regression operating rules has been done. The results showed that the the conditional operation rules reduces relative absolute error by a minimum of 39% and a maximum of 71%. If the system is operated according to the conditional rules, in the worst case, the amount of water shortage imposed will be 16.61 MCM over ten years.