Wet-snow avalanches are relatively poorly understood and difficult to forecast. By definition, liquid water is required in the snow cover, thus predicting the liquid water content of the snow cover is of paramount importance for wet-snow avalanche forecasting. While assessing wet-snow instability through field measurements is difficult, physically based snow cover models, such as SNOWPACK, can be used to estimate the amount of liquid water within the snow cover using meteorological input. Indeed, an index based on the liquid water content of the snow cover was recently suggested for the onset of wet-snow avalanching (LWCIndex). If snow cover models are forced with data from automated weather stations (AWS), only a now-cast is possible. For this study, we therefore force SNOWPACK with data from the high-resolution numerical weather prediction (NWP) model COSMO and investigate whether forecasting regional patterns of the onset of wet-snow avalanche activity is feasible. To validate the index, we compared simulations performed at the location of numerous AWS in the Swiss Alps with wet-snow avalanche observations from the corresponding region. Results show that the onset of wet-snow avalanche activity can be simulated with the snow cover model SNOWPACK while forced with data from automated weather stations (now-cast). Bias corrections are required prior to forcing SNOWPACK with only NWP data. However, similarly good results compared to simulations with station data only were achieved by first forcing SNOWPACK with data from automated weather stations and then adding the forecasted data. While using this setup the onset of wet-snow avalanching for two different climate regions in Switzerland was reproduced.