Missing Rainfall Daily Data: A Comparison Among Gap-Filling Approaches

Abstract Missing data is a frequent problem in meteorological and hydrological temporal observation sets. Finding effective solutions to this essential because complete time series are required conduct reliable analyses. This study used daily rainfall from 60 rain gauges spatially distributed within Portugal's Guadiana River basin over 30-year reference period (1976–2005). Gap-filling approaches using kriging-based interpolation methods (i.e. ordinary kriging simple cokriging) presented compared deterministic approach proposed by the Food Agriculture Organization (FAO method). The suggested procedure consists of fitting monthly semi-variogram models average all available stations for each month period. makes it possible use only 12 semi-variograms instead one day gap Ordinary cokriging estimate missing precipitation interest. method applied considering elevation as secondary variable. One year were removed some assess efficacy approaches, estimated three procedures. validated through cross-validation process different performance metrics. results showed that geostatistical outperformed FAO estimation. In investigated area, did not significantly improve estimates kriging, which was deemed best large majority stations.