In the context of the global warming, we experience increasing extreme weather events, in particular extreme precipitation which may cause natural disasters. As monsoon climate is dominant in China bringing frequent and intense convective precipitations, adequate knowledge of monsoon characteristics is necessary for understanding of extreme weather events. Considering that the monsoon is usually accompanied by distinct variations in water vapor between dry and wet seasons and rapid transitions between dry and wet states, understanding of the distribution and variability of water vapor can play a certain role in indicating monsoon characteristics. Compared with other traditional water vapor acquisition methods, ground-based Global Navigation Satellite System (GNSS) observations have big advantages for monsoon studies due to its high accuracy, high temporal availability, and long-term homogeneity. In this work, GNSS data from nearly 1000 stations densely distributed in China were used to obtain Precipitable Water Vapor (PWV) during 2016. We first utilized the bimodality of PWV statistical distribution and selected a suitable metric to quantify the impact of monsoon in different regions. Results indicate that the strongest bimodality occurs in Southwest China with the metrics below 1.75. Eastern China is also part of the monsoon regions with metrics between 1.75 and 2.25. For the less affected regions such as Northwest China, the bimodality is weak with metrics above 2.25. Subsequently, the normalized precipitable water indexes (NPWI) were constructed using temporal variations in PWV to describe the monsoon onset and retreat. The monsoon reached the south-eastern coastal regions in early/mid May (Day of year 120-140) and advanced to the north-eastern regions at the end of July (Day of year 210). In general, the monsoon advances from the south-east to the north-west with an uneven speed over China.