Water vapor plays a vital role in weather variations, making it essential to monitor atmospheric water vapor content for reliable weather forecasts. This study investigates the feasibility of utilizing a low-cost GNSS network to monitor water vapor transport during a heavy precipitation event. The zenith wet delay (ZWD) products are retrieved in GNSS data processing and then transformed to integrated water vapor (IWV). In addition, the impact of various factors, including near real-time products, weighted mean temperature ( \(\:{T}_{m}\) ) estimation models, and the sensitivity of the conversion factor to \(\:{T}_{m}\) variations are investigated in this study. Results demonstrate that: (1) Phase center variation (PCV) corrections, often unavailable for low-cost antennas, are crucial for accurate ZWD estimation, and the absence of these corrections may result in underestimations of the ZWD by several millimeters. (2) Near real-time GNSS products demonstrate comparable accuracy to final products, enabling timely IWV monitoring. (3) ZWD estimated from low-cost stations exhibit strong agreement with those from geodesic-grade stations, demonstrating their reliability. (4) GPT3, GTrop, and GGNTm models could effectively convert ZWD to IWV, with negligible differences despite slight variations in \(\:{T}_{m}\) estimation accuracy. (5) The network effectively captures the spatio-temporal evolution of IWV during the precipitation event, demonstrating its potential for high-resolution water vapor monitoring. These findings highlight the effectiveness of low-cost GNSS networks in providing valuable insights into atmospheric water vapor dynamics, contributing to improved weather forecasting and hydrological modeling.
