With the recent advance of Global Positioning System (GPS) sensing technology, ground-based GPS slant-path wet delay measurements provide an opportunity to observe the small-scale variation of the low-level atmospheric moisture at high temporal resolution. In this study, we performed a series of observing system simulation experiments to assess the potential impact of slant wet delay on the prediction of a prefrontal squall line. The slant wet delay measurements were assimilated through four-dimensional variational data assimilation (4DVAR). We found that the assimilation of slant wet delay data resulted in the enhancement of the three-dimensional gradient of thermodynamic fields in the boundary layer and intensified the surface cold front. As a result, a significant improvement was achieved on the 6-h forecast of the squall line in terms of rainfall prediction and the retrieval of the atmospheric structure.