Use of past precipitation data for regionalisation of hourly rainfall in the low mountain ranges of Saxony, Germany

Abstract

Abstract. Within the context of flood forecasting we deal with the improvement of regionalisation methods for the generation of highly resolved (1 h, 1×1km 2 ) precipitation fields, which can be used as input for rainfall-runoff models or for verification of weather forecasts. Although radar observations of precipitation are available in many regions, it might be necessary to apply regionalisation methods near real-time for the cases that radar is not available or observations are of low quality.The aim of this paper is to investigate whether past precipitation information can be used to improve regionalisation of rainfall. Within a case study we determined typical precipitation Background-Fields (BGF) for the mountainous and hilly regions of Saxony using hourly and daily rain gauge data. Additionally, calibrated radar data served as past information for the BGF generation. For regionalisation of precipitation we used de-trended kriging and compared the results with another kriging based regionalisation method and with Inverse Distance Weighting (IDW). The performance of the methods was assessed by applying crossvalidation, by inspection and by evaluation with rainfallrunoff simulations.The regionalisation of rainfall yielded better results in case of advective events than in case of convective events. The performance of the applied regionalisation methods showed no significant disagreement for different precipitation types. Cross-validation results were rather similar in most cases. Subjectively judged, the BGF-method reproduced best the structures of rain cells. Precipitation input derived from radar or kriging resulted in a better matching between observed and simulated flood hydrographs. Simple techniques likeCorrespondence to: T. Pluntke (thomas.pluntke@tu-dresden.de) IDW also deliver satisfying results in some occasions. Implementation of past radar data into the BGF-method rendered no improvement, because of data shortages. Thus, no method proved to outperform the others generally. The decision, which method is appropriate for an event, should be made objectively using cross-validation, but also subjectively, using the expert knowledge of the forecaster.

The significance of soil moisture in forecasting characteristics of flood events. A statistical analysis in two nested catchments

“…This is consistent with the practice (e.g. Pluntke et al, 2010) that spatial variations of precipitation cannot be neglected in scale transitions. In this respect, upscaling the most important input variable does not seem to be justified.…”

An approach to combine radar and gauge based rainfall data under consideration of their qualities in low mountain ranges of Saxony

“…We think a rainfall-runoff model is a useful tool to check the results of the presented method. A first validation of the final rain product was initiated by Pluntke et al (2010). The results of this study are slightly contrary to the findings of Kneis and Heistermann (2009), where interpolated gauge data performed better than radar data.…”

“…Instead, ordinary kriging is applied. The BGF method is described by Hinterding (2003) and was applied to Saxony (Pluntke et al, 2010). The method reproduces the spatial structure of precipitation cells of hourly rainfall well and works reliably in real-time.…”

“…Statistical methods analyse the variances between two values as well as the distance between them. Hinterding (2003), Haberlandt et al (2005), and Pluntke et al (2010) apply kriging methods to small and large-scale rainfall events with resolutions from one hour to several days. These methods show good results regarding the delineation of precipitation areas, but not for the internal variability within the precipitation fields and the rain intensities.…”

Effects of temporal resolution of input precipitation on the performance of hydrological forecasting

“…Li et al, 2010;Pluntke et al, 2010) or assimilating radar data to create data sets of hourly time resolution or higher for input to hydrological models (e.g. Biggs and Atkinson, 2010).…”