Geostatistical regionalization of daily runoff forecasts in Norway

Abstract

The national flood forecasting service in Norway applies the conceptual HBV model in 117 catchments of different scales. Daily runoff forecasts from these 117 catchments are regionalized for nationwide qualitative flood risk regionalization displayed in a map. The regionalization is performed without considering scale dependency in runoff response in different-sized catchments. We developed a simple catchment classification approach that allows the incorporation of catchment scale into qualitative runoff forecasting regionalization by geostatistical methods such as ordinary kriging (OK) and inverse distance weighting (IDW). Slightly improved regionalization results were obtained using this classification approach. We further evaluated the predictive performance of OK as this is the current operational approach for qualitative runoff forecast regionalization used in Norway. The results suggest that OK regularly predicts correct tendencies in runoff development and often with small errors. However, the results further suggest that the runoff normalization procedure (which is necessary to make runoff data comparable) provides another source of errors in flood risk regionalization. We also compare the predictive performance of OK with IDW as a less complex method and top-kriging (TK), which is an approach especially developed for interpolating river network-related data. The validation results show that TK performs best, whereas OK tends to perform only slightly better than IDW.