Interpolation of spatially varying point precipitation depths introduces uncertainties in the estimated mean areal precipitation (MAP). This paper describes a geostatistical approach – the Kriging method – to calculate the daily MAP on real-time basis. The procedure provides a linear unbiased estimate with minimum estimation variance. The structural analysis of the random precipitation field is automatized by relating the time-varying semivariogram model to the sample variance. This is illustrated on data from a Danish IHD catchment.
The conceptual rainfall-runoff model NAM incorporated into a Kalman-filter algortithm is applied to investigate the effects of uncertainties in MAP on the runoff predictions. Measurement and processing errors are not included in the investigation.
