A stochastic spatial rainfall generator is developed for use at the small spatial scale of urban and small hydrographic catchments. The generator is based on a spatial rainfall model of the conceptual and hierarchical type. It describes the spatial rainfall field in a macroscopic physically-based way by distinguishing rainfall entities with different scales: rain cells, cell clusters, small and large mesoscale areas (or rain storms). For applications at small spatial scales, the individual rain cells need a detailed description. Data of a dense network of rain gauges at Antwerp, enclosing 5940 rain cells in 807 rain storms are used to derive such description. For separation of the rain cells in the rainfall time series, an algorithm is developed based on the identification of increasing and decreasing rain cell flanks. The rain cells observed at different rain gauges are linked together by applying criteria for testing the similarity in rain cell properties. After separating and linking the rain cells and storms, the spatial rainfall model is calibrated to many storms by two methods (e.g. Kalman filter). The derived model structure and model parameter distributions apply to the stochastic generation of long-term time series of spatial rainfall. The model is tested by comparing intensity–duration–frequency relationships and temporal scaling properties of the generated and historical rainfall series.