Articles | Volume 10, issue 4
https://doi.org/10.5194/esurf-10-851-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/esurf-10-851-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
15 Aug 2022
Research article |
| 15 Aug 2022
| 15 Aug 2022
Comparison of rainfall generators with regionalisation for the estimation of rainfall erosivity at ungauged sites
Ross Pidoto
Institute of Hydrology and Water Resources Management, Leibniz University Hannover, Hanover, Germany
Nejc Bezak
University of Ljubljana, Faculty of Civil and Geodetic Engineering, Ljubljana, Slovenia
Hannes Müller-Thomy
CORRESPONDING AUTHOR
Leichtweiß Institute for Hydraulic Engineering and Water Resources, Department of Hydrology, Water Management and Water Protection, Technische Universität Braunschweig, Brunswick, Germany
Institute of Hydraulic Engineering and Water Resources Management, Vienna University of Technology, Vienna, Austria
previously published under the name Hannes Müller
Bora Shehu
Institute of Hydrology and Water Resources Management, Leibniz University Hannover, Hanover, Germany
Ana Claudia Callau-Beyer
Institute of Horticultural Production Systems, Leibniz University Hannover, Hanover, Germany
Katarina Zabret
University of Ljubljana, Faculty of Civil and Geodetic Engineering, Ljubljana, Slovenia
Uwe Haberlandt
Institute of Hydrology and Water Resources Management, Leibniz University Hannover, Hanover, Germany
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Rainfall erosivity is the main driver of water-induced soil erosion. A ground radar-based data was used to prepare a rainfall erosivity map of Europe. This study shows that the radar-based data products are a valuable solution for estimating large-scale rainfall erosivity, especially in regions with limited station-based precipitation data. A rainfall erosivity ensemble was derived to give first insights into a future avenue for updatable pan-European rainfall erosivity predictions.
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River flow data are often provided as mean daily flows (MDF), in which a lot of information is lost about the actual maximum flow or instantaneous peak flows (IPF) within a day. We investigate the error of using MDF instead of IPF and identify means to predict IPF when only MDF data are available. We find that the average ratio of daily flood peaks and volumes is a good predictor, which is easily and universally applicable and requires a minimum amount of data.
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Extreme flooding occurred in Slovenia in August 2023. This brief communication examines the main causes, mechanisms and effects of this event. The flood disaster of August 2023 can be described as relatively extreme and was probably the most extreme flood event in Slovenia in recent decades. The economic damage was large and could amount to well over 5 % of Slovenia's annual gross domestic product; the event also claimed three lives.
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Rainfall volumes at varying duration and frequencies are required for many engineering water works. These design volumes have been provided by KOSTRA-DWD in Germany. However, a revision of the KOSTRA-DWD is required, in order to consider the recent state-of-the-art and additional data. For this purpose, in our study, we investigate different methods and data available to achieve the best procedure that will serve as a basis for the development of the new KOSTRA-DWD product.
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Rainfall erosivity is one of the main factors in soil erosion. A satellite-based global map of rainfall erosivity was constructed using data with a 30 min time interval. It was shown that the satellite-based precipitation products are an interesting option for estimating rainfall erosivity, especially in regions with limited ground data. However, ground-based high-frequency precipitation measurements are (still) essential for accurate estimates of rainfall erosivity.
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In this paper we investigate whether similar storms behave similarly and whether the information obtained from past similar storms can improve storm nowcast based on radar data. Here a nearest-neighbour approach is employed to first identify similar storms and later to issue either a single or an ensemble nowcast based on k most similar past storms. The results indicate that the information obtained from similar storms can reduce the errors considerably, especially for convective storm nowcast.
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River flow data is often provided as mean daily flow (MDF), in which a lot of information is lost about the actual maximum flow or instantaneous peak flow (IPF) within a day. We investigate the error of using MDFs instead of IPFs and identify means to predict IPFs when only MDF data is available. We find that the average ratio of daily flood peaks and volumes is a good predictor, which is easily and universally applicable and requires a minimum amount of data.
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Short summary
Erosion is a threat for soils with rainfall as the driving force. The annual rainfall erosivity factor quantifies rainfall impact by analysing high-resolution rainfall time series (~ 5 min). Due to a lack of measuring stations, alternatives for its estimation are analysed in this study. The best results are obtained for regionalisation of the erosivity factor itself. However, the identified minimum of 60-year time series length suggests using rainfall generators as in this study as well.
Erosion is a threat for soils with rainfall as the driving force. The annual rainfall erosivity...
