Conventional raingauge networks have proven to be inadequate to describe the temporal and spatial distribution of rainfall, but raingauge data combined with radar data can provide a very useful technique for monitoring the quantitative distribution of rainfall in time and space. A square grid mean areal rainfall model is developed, which utilizes raingauge measurements and a Kalman filter state-space model of the Z–R relationship from radar measurements. The developed method applies in areas where radar information exists, and it has been tested for only one watershed. Key words: space-time rainfall model, radar, raingauge, Kalman filter.
Correction to “Worth of radar data in the real-time prediction of mean areal rainfall by nonadvective physically based models” by K. P. Georgakakos and W. F. Krajewski