High soil saturation levels can be considered as a primary indicator for potential river flooding. Therefore it is advisable to visualize real-time soil moisture information in flood forecasting or warning systems. Monitoring of soil moisture, however, is not an easy task due to its variable nature in time, space and depth. This paper presents and compares methods to assess the severity of the soil moisture state of hydrological catchments considered in a typical operational flood forecasting system. The severity of the relative soil moisture state is obtained and mapped by comparing simulation results of a lumped conceptual hydrological model, directly, by making use of the soil moisture component of the model or indirectly considering the baseflow component. The values are compared in real time after with the results of a long term simulation. Another approach uses rainfall, evapotranspiration and the river flow observations. By applying a baseflow filter to the river flow observations and an advanced method for empirical catchment water balance computation, two additional soil moisture indicators can be definied, namely the filtered baseflow and the water balance based relative soil moisture content. It is shown that each of the methods allow to obtain useful estimates of the soil moisture state of a catchment in real time. Secondly, a method has been set up to calculate the exceedance probability of a predefined discharge threshold, e.g. flood threshold, at the outlet or a given location in the catchment. The exceedance probability is calculated by a logit relation with the soil moisture indicator. The different soil moisture indicators are compared in their predicting capabilities by calculating and comparing the probability of detection, the false alarm rate and the critical success index. Interestingly, the application of such logit relation or the use of a simple water balance computation for the catchment, based on real-time rainfall, evapotranspiration and river flow observations, leads to more reliable exceedance probability estimates than the common direct use of total runoff results from a state-of-the art rainfall-runoff model. Mapping the exceedance probability for the different hydrological catchments together with the width of the confidence interval on this probability is proposed as a useful tool to increase the preparedness for potential floods, since this kind of maps provide a quick overview of the catchments in which flood problems can be expected, hence on which flood crisis management bodies have to focus their attention.