A space-time rainfall model is constructed to generate synthetic fields of spacetime rainfall, with a daily time step. The model has two components: a temporal model based on a first-order, four-state discrete Markov chain which generates a daily time series of the regionally averaged rainfall and a spatial model based on a nonhomogeneous random cascade process which disaggregates the above regionally averaged rainfall amounts to produce spatial patterns of daily rainfall across the region. The cascade generators used to disaggregate the rainfall spatially are a product of stochastic and deterministic factors; the latter enable the model to capture systematic spatial gradients exhibited by measured data. The model is applied to a 400 km x 400 km region encompassing the Swan-Avon River Basin in the southwest of Western Australia. The model parameters are estimated on the basis of 11 years of observed daily rainfall data from 490 rain gauges located in the region. A detailed testing of the model is undertaken on the basis of a comparison of the statistical characteristics of the spatial and temporal variability of rainfall between the rainfall fields obtained from the rain gauge network and those generated by the simulation model. It was found that the spatial and temporal characteristics of the simulated rainfall field are in very good agreement with those of observed rainfall. In particular, the model preserves the observed systematic spatial variations of daily, monthly, and annual rainfall across the region and the observed seasonal variations. Statistical characteristics of storm durations and interstorm periods at individual gauge locations are not reproduced that well, which suggests generalizations need to be made to include space-time correlations.