The middle and lower reaches of the Yangtze River are located in the East Asian monsoon region where part of its summer precipitation water vapor comes from the moisture transport of the Bay of Bengal. In this paper, the atmospheric precipitable water (PW) data collected from the global positioning system (GPS) sites in the Tibetan Plateau and the assimilation module (WRFDA) of WRF (Weather Research and Forecasting Model) are used to assimilate the water vapor transport information into the numerical model. At the same time, WRF is also applied to do batch testing and case analysis of the precipitation forecast in the middle and lower reaches of the Yangtze River region in July. Three schemes are adopted during batch experiments and analysis of individual cases: a control experiment with no data assimilation (NoDA), a cold-start assimilation experiment (Cold) and a cycling assimilation experiment (Cycling). In addition, the experiment of extending the forecast time of the cycling scheme is performed to find out the most obvious time period of active effect. For the purpose of investigating the source of active effect, additional experiments of only assimilating the GPS sites that are mainly covered with the water vapor conveyor belt (Cycling_less_a) and that are not mainly covered the with water vapor conveyor belt (Cycling_less_b) are carried out according to the cycling scheme. The results show that the assimilation of the GPSPW data of the Tibetan Plateau area can improve the forecast of precipitation in the middle and lower reaches of the Yangtze River to a certain extent, especially for the 48-72-h period precipitation forecast. The cycling scheme outperforms the cold scheme on the whole. For the cycling scheme, during the forecast time of 120 h, the active effect is most obvious in the 48-72-h period. When the conveyor belt of water vapor goes through the assimilation area, the TS score of precipitation can be obviously improved, while the improvement will not be so obvious when the water vapor does not go through the assimilation area. If we only assimilate the GPSPW data of the GPS sites covered with the water vapor transportation belt, we can still retain most of the positive effect. Therefore, targeted assimilation of the GPSPW data is feasible.