Simulation of the water balance in cropping systems is an essential tool, not only to monitor water status and determine drought but also to find ways in which soil water and irrigation water can be used more efficiently. However, besides the requirement that models are physically correct, the spatial representativeness of input data and, in particular, accurate precipitation data remain a challenge. In recent years, satellite-based soil moisture products have become an important data source for soil wetness information at various spatial-temporal scales. Four different study areas in the Czech Republic and Austria were selected representing Central European soil and climatic conditions. The performance of soil water content outputs from two different crop-water balance models and the Metop Advanced SCATterometer (ASCAT) soil moisture product was tested with field measurements from 2007 to 2011. The model output for soil water content shows that the crop model Decision Support System for Agrotechnology Transfer performs well during dry periods (<30% plant available soil moisture (ASM), whereas the soil water-balance model SoilClim presents the best results in humid months (>60% ASM). Moreover, the model performance is best in the early growing season and decreases later in the season due to biases in simulated crop-related above-ground biomass compared with the relatively stable grass canopy of the measurement sites. The Metop ASCAT soil moisture product, which presents a spatial average of soil surface moisture, shows the best performance under medium soil wetness conditions (30–50% ASM), which is related to low variation in precipitation frequency and under conditions of low-surface biomass (early vegetation season).