Abstract: Precipitable water vapor (PWV) plays an important role in small and medium-scale severe weather forecasting and is one of the important parameters for precipitation intensity forecasting. Since the 1980, many scholars have conducted a large number of studies on PWV using GPS. Precise point positioning (PPP) technology is widely used in the PWV inversion due to its advantages of high accuracy, high temporal resolution, and low operating cost for single stations. To improve the accuracy of PWV inversion, the tropospheric gradient parameters are added into the multi-system PPP model to improve the accuracy of GNSS PPP in extracting tropospheric delay under complex atmospheric conditions with precipitation. The experiment use global data from 200 MGEX stations. The results showed that estimating tropospheric gradient parameters can improve the estimation accuracy of GNSS zenith wet delay (ZWD). The mean value, standard deviation (STD), and root mean square (RMS) increased by 36.4%～40.7%, 5.3%～8.7%, and 7.8%～17.9% with tropospheric gradient parameter estimation, respectively. The corresponding PWV obtained is in better comformity with the water vapor radiometer (WVR). In addition, in response to the problem that PWV and ZWD can only reflect the precipitation process and are difficult to determine the precipitation time, a method combined PWV, temperature, and dew point temperature to determine the occurrence of precipitation is proposed, and the Zhengzhou 2021 “7·20” rainstorm event is used to verify the reliability and accuracy of this method.The experimental results show that the combination of local temperature, dew point temperature, and PPP-inferred PWV can accurately determine the occurrence of precipitation.