We investigated the impacts of vegetation and groundwater dynamics on warm season precipitation by using the Weather Research and Forecasting (WRF) model coupled with a modified Noah land surface model (LSM). The modified Noah LSM was augmented with an interactive canopy model and a simple groundwater model (SIMGM). A series of experiments performed shows that incorporating vegetation and groundwater dynamics into the WRF model can improve the simulation of summer precipitation in the Central United States. The enhanced model produces more precipitation in response to an increase in the latent heat flux. The advantage of incorporating the two components into the model becomes more discernable after 1 month. The model results suggest that the land‐atmosphere feedback is an important mechanism for summer precipitation over the Central United States. Vegetation growth and groundwater dynamics play a significant role in enhancing the persistence of intraseasonal precipitation in regional climate models. Their combined effects act to favor a stronger land‐atmosphere feedback during the summer season. The simulated diurnal cycle of precipitation is improved by the WRF model with the augmented Noah LSM. Moreover, we found that the coupling between the soil moisture and the lifting condensation level (LCL) is enhanced by adding the two components to the WRF model. The impact of groundwater is significant when the soil moisture is relatively dry. This study suggests that incorporating vegetation and groundwater dynamics into a regional climate model would be especially beneficial for seasonal precipitation forecast in the transition zones.