The accuracy of flood forecasts generated using spatially lumped hydrological models can be severely affected by errors in the estimates of mean areal rainfall. The quality of the latter depends both on the size and type of errors in point-based rainfall measurements, and on the density and spatial arrangement of rain gauges in the basin. Here, we use error feedback correction, based on the rainfall system response curve method, to compute updated estimates of the rainfall inputs. The capability of the method to improve the accuracy of real-time flood forecasts is demonstrated using the Xin'anjiang (XAJ) model applied to 16 flood events of the Wangjiaba Basin. The result shows that the forecast improvement is significant. For the Wangjiaba Basin, we also examinethe performance of the method for different rain gauge densities, and find that forecast improvement is more significant when gauge densities are lower. The method is relatively simple to apply and can improve the accuracy of real-time model predictions without increasing either model complexity and/or the number of model parameters.