Articles | Volume 21, issue 10
https://doi.org/10.5194/hess-21-5385-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/hess-21-5385-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
27 Oct 2017
Research article |
| 27 Oct 2017
Regional frequency analysis of extreme rainfall in Belgium based on radar estimates
Edouard Goudenhoofdt
CORRESPONDING AUTHOR
The Royal Meteorological Institute of Belgium, Brussels, Belgium
Laurent Delobbe
The Royal Meteorological Institute of Belgium, Brussels, Belgium
Patrick Willems
Department of Civil Engineering – Hydraulics Division, University of Leuven, Leuven, Belgium
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- Runoff prediction using rainfall data from microwave links: Tabor case study D. Stransky et al. 10.2166/wst.2018.149
- An Effective Algorithm of Outlier Correction in Space–Time Radar Rainfall Data Based on the Iterative Localized Analysis Y. Kim et al. 10.1109/TGRS.2024.3366400
- Identification of Rainfall Events and Heavy Rainfall Events From Radar Measurements in Southeastern Australia A. Bowden et al. 10.1029/2023JD039253
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- Proxy Data of Surface Water Floods in Rural Areas: Application to the Evaluation of the IRIP Intense Runoff Mapping Method Based on Satellite Remote Sensing and Rainfall Radar A. Cerbelaud et al. 10.3390/w14030393
- Intensity–duration–frequency curves exploiting neighbouring extreme precipitation data A. Bárdossy & G. Pegram 10.1080/02626667.2018.1524987
- Regionalization of anthropogenically forced changes in 3 hourly extreme precipitation over Europe P. Hosseinzadehtalaei et al. 10.1088/1748-9326/ab5638
- Spatial Frequency Analysis by Adopting Regional Analysis with Radar Rainfall in Taiwan C. Chang et al. 10.3390/w14172710
- Effect of temporal sampling mismatches between satellite rainfall estimates and rain gauge observations on modelling extreme rainfall in the Upper Awash Basin, Ethiopia K. Mekonnen et al. 10.1016/j.jhydrol.2021.126467
- Decision-Support Tool for Constructing Robust Rainfall IDF Relations in Consideration of Model Uncertainty T. Nguyen & V. Nguyen 10.1061/(ASCE)HE.1943-5584.0001802
- The Impact of Extreme Rainstorms on Escarpment Morphology in Arid Areas: Insights From the Central Negev Desert Y. Shmilovitz et al. 10.1029/2023JF007093
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- Regional Frequency Analysis applied to extreme rainfall events: Evaluating its conceptual assumptions and constructing null distributions G. BLAIN et al. 10.1590/0001-3765202120190406
- Using a regional frequency analysis approach for calculating the Standardized Precipitation Index: an operational approach based on the two-parameter gamma distribution E. dos Santos Junior et al. 10.1007/s00704-022-03989-7
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- Adapting the regional frequency analysis based on L-moments to improve the standardized precipitationevapotranspiration index L. Martins et al. 10.1590/1678-4499.20240029
- Is it possible to apply the regional frequency analysis to daily extreme air temperature data? L. Martins et al. 10.1590/1678-4499.20220061
- Precipitation frequency analyses based on radar estimates: An evaluation over the contiguous United States D. McGraw et al. 10.1016/j.jhydrol.2019.03.032
- Estimating Rainfall Design Values for the City of Oslo, Norway—Comparison of Methods and Quantification of Uncertainty J. Lutz et al. 10.3390/w12061735
- Enhancing the Performance of Quantitative Precipitation Estimation Using Ensemble of Machine Learning Models Applied on Weather Radar Data E. Mihuleţ et al. 10.3390/atmos14010182
- The 3D Neural Network for Improving Radar-Rainfall Estimation in Monsoon Climate N. Roslan et al. 10.3390/atmos12050634
- Survey on the Application of Deep Learning in Extreme Weather Prediction W. Fang et al. 10.3390/atmos12060661
- A process-based flood frequency analysis within a trivariate statistical framework. Application to a semi-arid Mediterranean case study S. Salazar-Galán et al. 10.1016/j.jhydrol.2021.127081
- Frequency analysis of extreme rainfall over the Japanese archipelago by leveraging gauge-adjusted radar and satellite estimates S. Mtibaa 10.1016/j.jhydrol.2024.131425
- Estimation of design precipitation using weather radar in Germany: A comparison of statistical methods K. Lengfeld & F. Marra 10.1016/j.ejrh.2024.101952
- Estimating IDF Curves Consistently over Durations with Spatial Covariates J. Ulrich et al. 10.3390/w12113119
32 citations as recorded by crossref.
- Enhancing the usability of weather radar data for the statistical analysis of extreme precipitation events A. Hänsler & M. Weiler 10.5194/hess-26-5069-2022
- Precipitation frequency analysis from remotely sensed datasets: A focused review F. Marra et al. 10.1016/j.jhydrol.2019.04.081
- Runoff prediction using rainfall data from microwave links: Tabor case study D. Stransky et al. 10.2166/wst.2018.149
- An Effective Algorithm of Outlier Correction in Space–Time Radar Rainfall Data Based on the Iterative Localized Analysis Y. Kim et al. 10.1109/TGRS.2024.3366400
- Identification of Rainfall Events and Heavy Rainfall Events From Radar Measurements in Southeastern Australia A. Bowden et al. 10.1029/2023JD039253
- Estimation of Intensity‐Duration‐Area‐Frequency Relationships Based on the Full Range of Non‐Zero Precipitation From Radar‐Reanalysis Data A. Haruna et al. 10.1029/2023WR035902
- Regionalisation of rainfall depth–duration–frequency curves with different data types in Germany B. Shehu et al. 10.5194/hess-27-1109-2023
- Quantitative precipitation estimation with weather radar using a data- and information-based approach M. Neuper & U. Ehret 10.5194/hess-23-3711-2019
- Simulation and forecasting of fishery weather based on statistical machine learning X. Fu et al. 10.1016/j.inpa.2023.05.001
- Proxy Data of Surface Water Floods in Rural Areas: Application to the Evaluation of the IRIP Intense Runoff Mapping Method Based on Satellite Remote Sensing and Rainfall Radar A. Cerbelaud et al. 10.3390/w14030393
- Intensity–duration–frequency curves exploiting neighbouring extreme precipitation data A. Bárdossy & G. Pegram 10.1080/02626667.2018.1524987
- Regionalization of anthropogenically forced changes in 3 hourly extreme precipitation over Europe P. Hosseinzadehtalaei et al. 10.1088/1748-9326/ab5638
- Spatial Frequency Analysis by Adopting Regional Analysis with Radar Rainfall in Taiwan C. Chang et al. 10.3390/w14172710
- Effect of temporal sampling mismatches between satellite rainfall estimates and rain gauge observations on modelling extreme rainfall in the Upper Awash Basin, Ethiopia K. Mekonnen et al. 10.1016/j.jhydrol.2021.126467
- Decision-Support Tool for Constructing Robust Rainfall IDF Relations in Consideration of Model Uncertainty T. Nguyen & V. Nguyen 10.1061/(ASCE)HE.1943-5584.0001802
- The Impact of Extreme Rainstorms on Escarpment Morphology in Arid Areas: Insights From the Central Negev Desert Y. Shmilovitz et al. 10.1029/2023JF007093
- Exploring the use of underground gravity monitoring to evaluate radar estimates of heavy rainfall L. Delobbe et al. 10.5194/hess-23-93-2019
- Regional Frequency Analysis applied to extreme rainfall events: Evaluating its conceptual assumptions and constructing null distributions G. BLAIN et al. 10.1590/0001-3765202120190406
- Using a regional frequency analysis approach for calculating the Standardized Precipitation Index: an operational approach based on the two-parameter gamma distribution E. dos Santos Junior et al. 10.1007/s00704-022-03989-7
- Analysis on the temporal scaling behavior of extreme rainfall in Korean Peninsula based on high-resolution radar-based precipitation data S. Kim et al. 10.1016/j.ejrh.2024.101915
- The accuracy of weather radar in heavy rain: a comparative study for Denmark, the Netherlands, Finland and Sweden M. Schleiss et al. 10.5194/hess-24-3157-2020
- Adapting the regional frequency analysis based on L-moments to improve the standardized precipitationevapotranspiration index L. Martins et al. 10.1590/1678-4499.20240029
- Is it possible to apply the regional frequency analysis to daily extreme air temperature data? L. Martins et al. 10.1590/1678-4499.20220061
- Precipitation frequency analyses based on radar estimates: An evaluation over the contiguous United States D. McGraw et al. 10.1016/j.jhydrol.2019.03.032
- Estimating Rainfall Design Values for the City of Oslo, Norway—Comparison of Methods and Quantification of Uncertainty J. Lutz et al. 10.3390/w12061735
- Enhancing the Performance of Quantitative Precipitation Estimation Using Ensemble of Machine Learning Models Applied on Weather Radar Data E. Mihuleţ et al. 10.3390/atmos14010182
- The 3D Neural Network for Improving Radar-Rainfall Estimation in Monsoon Climate N. Roslan et al. 10.3390/atmos12050634
- Survey on the Application of Deep Learning in Extreme Weather Prediction W. Fang et al. 10.3390/atmos12060661
- A process-based flood frequency analysis within a trivariate statistical framework. Application to a semi-arid Mediterranean case study S. Salazar-Galán et al. 10.1016/j.jhydrol.2021.127081
- Frequency analysis of extreme rainfall over the Japanese archipelago by leveraging gauge-adjusted radar and satellite estimates S. Mtibaa 10.1016/j.jhydrol.2024.131425
- Estimation of design precipitation using weather radar in Germany: A comparison of statistical methods K. Lengfeld & F. Marra 10.1016/j.ejrh.2024.101952
- Estimating IDF Curves Consistently over Durations with Spatial Covariates J. Ulrich et al. 10.3390/w12113119
Latest update: 14 Dec 2024
Short summary
Knowing the characteristics of extreme precipitation is useful for flood management applications like sewer system design. The potential of a 12-year high-quality weather radar precipitation dataset is investigated by comparison with rain gauges. Despite known limitations, a good agreement is found between the radar and the rain gauges. Using the radar data allow us to reduce the uncertainty of the extreme value analysis, especially for short duration extremes related to thunderstorms.
Knowing the characteristics of extreme precipitation is useful for flood management applications...
