Abstract: Accurate calculation of land surface heat fluxes is scientifically significant and practically valuable for understanding land-atmosphere interaction and improving capabilities of weather forecast. The methods commonly used for calculating land surface heat fluxes in current numerical weather forecast models are based on the Monin-Obukhov Similarity Theory (MOST). These methods have some limitations and it is hard to further improve them. Meanwhile, a method based on maximum entropy production (MEP) model is proposed to calculate land surface heat fluxes in recent years. This method demonstrates great advantages and yields good results and has been increasingly applied in the study of land-atmosphere exchange. This study introduces the MEP model into the operational weather forecast numerical model (CMA-BJ model) in Beijing Meteorological Service to replace the existing MOST-based method in the model for the calculation of land surface sensible heat flux, latent heat flux and ground heat flux. Simulation experiments over the period from June to August 2022 are conducted to evaluate the performance of the operational numerical model system with the MEP model on predicting land surface and atmospheric meteorological elements and precipitation. Results show that the use of MEP model in CMA-BJ model can significantly improve the simulation of surface energy balance and thermodynamic processes of land surface and boundary layer. It also enhances the ability of the model for the simulation of air temperature, humidity and wind in the boundary layer, and ultimately increases the accuracy of precipitation prediction, especially for heavy rainfall prediction. The TS (threat scores) of rainstorm forecasts in North China and Yangtze river basin have increased by 20% and 10%, respectively. The predicted diurnal precipitation variation is also more consistent with observations with higher correlation coefficient. These results show that it is feasible to use MEP model in numerical weather forecast models and operational systems.