A Kalman filter modelling of space-time rainfall using radar and raingauge observations

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.