Löwe, Roland3; Mikkelsen, Peter Steen3; Rasmussen, Michael Robdrup4; Madsen, Henrik1
1 Department of Applied Mathematics and Computer Science, Technical University of Denmark2 Dynamical Systems, Department of Applied Mathematics and Computer Science, Technical University of Denmark3 Department of Environmental Engineering, Technical University of Denmark4 Aalborg University
Merging of radar rainfall data with rain gauge measurements is a common approach to overcome problems in deriving rain intensities from radar measurements. We extend an existing approach for adjustment of C-band radar data using state-space models and use the resulting rainfall intensities as input for forecasting outflow from two catchments in the Copenhagen area. Stochastic grey-box models are applied to create the runoff forecasts, providing us with not only a point forecast but also a quantification of the forecast uncertainty. Evaluating the results, we can show that using the adjusted radar data improves runoff forecasts compared with using the original radar data and that rain gauge measurements as forecast input are also outperformed. Combining the data merging approach with short-term rainfall forecasting algorithms may result in further improved runoff forecasts that can be used in real time control.
Water Science and Technology, 2013, Vol 68, Issue 3, p. 584-590
Flow Forecast; Greybox Model; Radar Rainfall; State Space Model; Flow forecast; Grey-box model; Radar rainfall; State-space model