Abstract: Previous studies on parameterizing microphysical processes using the WRF model for the Yangtze River basin have not optimized cumulus convection parameterization schemes for multiple meteorological elements in the middle and lower reaches of the Yangtze River in this specific region. This study focuses on the middle and lower Yangtze River basin, considering it for the first time as the research object. Based on optimal microphysical processes and boundary layer parameterization schemes, we evaluate three cumulus convection parameterization schemes: Kain–Fritsch (KF), Betts–Miller–Janjic (BMJ), and Grell–Freitas (GF). These schemes are analyzed in terms of their ability to simulate precipitation and temperature. We also compare and analyze the reasons behind the performance differences of these schemes, considering factors such as varying altitudes and water vapor sources. The objective is to identify appropriate parameterization schemes for different synoptic types. The results show that (1) the three selected cumulus convective parameterization schemes perform differently in precipitation and air temperature simulations. The KF scheme performs better performance for precipitation, with daily precipitation simulation correlation coefficients ranging from 0.73 to 0.77. The GF scheme performs better in air temperature simulations, with correlation coefficients ranging from 0.71 to 0.77. (2) Significant differences are observed among the three schemes across varying elevations. The KF and BMJ schemes more accurately depict the relationship between precipitation and topography along the Wuling–Dabashan Mountains. In the longitude profile, precipitation simulations in June 2015 and June 2017, the KF scheme shows low simulation errors of 5.96% and 6.06%, respectively. However, the GF scheme exaggerates the effect of topographic uplift, causing greater variability in simulated rainfall along these profiles. (3) The water vapor sources in the simulation results of the three schemes differ. The KF scheme shows that the Indian Ocean monsoon delivers abundant water vapor, resulting in fewer hydromorphic substances and concentrated cloud–water mixing ratios. This makes it more suitable for simulating precipitation in the middle and lower reaches of the Yangtze River. Conversely, the GF scheme highlights stronger warm, humid airflow from the South China Sea, leading to more hydromorphic substances and active cloud development, making it better suited to simulating precipitation in areas with frequent heavy convection. (4) Different water vapor sources weakly affect the accuracy of the simulation results of the three cumulus convective parameterization schemes. For instance, although water vapor from the Western Pacific had a greater influence in June 2017 compared to June 2015, the KF scheme still yielded the best precipitation simulation results.