Articles | Volume 19, issue 9
https://doi.org/10.5194/hess-19-4001-2015
© Author(s) 2015. 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-19-4001-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
29 Sep 2015
Research article |
| 29 Sep 2015
Singularity-sensitive gauge-based radar rainfall adjustment methods for urban hydrological applications
Hydraulics Laboratory, Katholieke Universiteit Leuven, 3001 Heverlee (Leuven), Belgium
S. Ochoa-Rodríguez
Department of Civil and Environmental Engineering, Imperial College London, London, SW7 2AZ, UK
Department of Civil and Environmental Engineering, Imperial College London, London, SW7 2AZ, UK
P. Willems
Hydraulics Laboratory, Katholieke Universiteit Leuven, 3001 Heverlee (Leuven), Belgium
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Cited
22 citations as recorded by crossref.
- Weather radar rainfall data in urban hydrology S. Thorndahl et al. 10.5194/hess-21-1359-2017
- Commercial microwave links for urban drainage modelling: The effect of link characteristics and their position on runoff simulations J. Pastorek et al. 10.1016/j.jenvman.2019.109522
- Uncertainty assessment of radar-raingauge merged rainfall estimates in river discharge simulations N. Nanding et al. 10.1016/j.jhydrol.2021.127093
- Demonstrating the value of community-based (‘citizen science’) observations for catchment modelling and characterisation E. Starkey et al. 10.1016/j.jhydrol.2017.03.019
- Evaluation of the Radar QPE and Rain Gauge Data Merging Methods in Northern China Q. Qiu et al. 10.3390/rs12030363
- Evaluation of Radar-Gauge Merging Techniques to Be Used in Operational Flood Forecasting in Urban Watersheds D. Wijayarathne et al. 10.3390/w12051494
- Comparing Approaches to Deal With Non‐Gaussianity of Rainfall Data in Kriging‐Based Radar‐Gauge Rainfall Merging F. Cecinati et al. 10.1002/2016WR020330
- Evaluation of Gauge‐Radar Merging Methods Using a Semi‐Distributed Hydrological Model in the Upper Thames River Basin, Canada J. McKee et al. 10.1111/1752-1688.12625
- The Potential of Knowing More: A Review of Data-Driven Urban Water Management S. Eggimann et al. 10.1021/acs.est.6b04267
- Autocorrelation structure of convective rainfall in semiarid-arid climate derived from high-resolution X-Band radar estimates F. Marra & E. Morin 10.1016/j.atmosres.2017.09.020
- Quantitative precipitation estimation with weather radar using a data- and information-based approach M. Neuper & U. Ehret 10.5194/hess-23-3711-2019
- Validating city-scale surface water flood modelling using crowd-sourced data D. Yu et al. 10.1088/1748-9326/11/12/124011
- Fast Bayesian Regression Kriging Method for Real‐Time Merging of Radar, Rain Gauge, and Crowdsourced Rainfall Data P. Yang & T. Ng 10.1029/2018WR023857
- Hydrological modeling and uncertainty analysis for a snow-covered mountainous river basin A. Gogineni & M. Chintalacheruvu 10.1007/s11600-023-01270-7
- Improving the precipitation accumulation analysis using lightning measurements and different integration periods E. Gregow et al. 10.5194/hess-21-267-2017
- A High-Resolution Quantitative Precipitation Estimate over Alaska through Kriging-Based Merging of Rain Gauges and Short-Range Regional Precipitation Forecasts B. Hoover et al. 10.1175/JTECH-D-21-0132.1
- Application of Very Short-Term Rainfall Forecasting to Urban Water Simulation using TREC Method J. Kim et al. 10.3741/JKWRA.2015.48.5.409
- Spatial and temporal variability of rainfall and their effects on hydrological response in urban areas – a review E. Cristiano et al. 10.5194/hess-21-3859-2017
- Radar polygon method: an areal rainfall estimation based on radar rainfall imageries W. Cho et al. 10.1007/s00477-016-1348-x
- Impact of spatial and temporal resolution of rainfall inputs on urban hydrodynamic modelling outputs: A multi-catchment investigation S. Ochoa-Rodriguez et al. 10.1016/j.jhydrol.2015.05.035
- Enhancement of radar rainfall estimates for urban hydrology through optical flow temporal interpolation and Bayesian gauge-based adjustment L. Wang et al. 10.1016/j.jhydrol.2015.05.049
- Parameter sensitivity analysis of SWAT model for streamflow simulation with multisource precipitation datasets J. Guo & X. Su 10.2166/nh.2019.083
16 citations as recorded by crossref.
- Weather radar rainfall data in urban hydrology S. Thorndahl et al. 10.5194/hess-21-1359-2017
- Commercial microwave links for urban drainage modelling: The effect of link characteristics and their position on runoff simulations J. Pastorek et al. 10.1016/j.jenvman.2019.109522
- Uncertainty assessment of radar-raingauge merged rainfall estimates in river discharge simulations N. Nanding et al. 10.1016/j.jhydrol.2021.127093
- Demonstrating the value of community-based (‘citizen science’) observations for catchment modelling and characterisation E. Starkey et al. 10.1016/j.jhydrol.2017.03.019
- Evaluation of the Radar QPE and Rain Gauge Data Merging Methods in Northern China Q. Qiu et al. 10.3390/rs12030363
- Evaluation of Radar-Gauge Merging Techniques to Be Used in Operational Flood Forecasting in Urban Watersheds D. Wijayarathne et al. 10.3390/w12051494
- Comparing Approaches to Deal With Non‐Gaussianity of Rainfall Data in Kriging‐Based Radar‐Gauge Rainfall Merging F. Cecinati et al. 10.1002/2016WR020330
- Evaluation of Gauge‐Radar Merging Methods Using a Semi‐Distributed Hydrological Model in the Upper Thames River Basin, Canada J. McKee et al. 10.1111/1752-1688.12625
- The Potential of Knowing More: A Review of Data-Driven Urban Water Management S. Eggimann et al. 10.1021/acs.est.6b04267
- Autocorrelation structure of convective rainfall in semiarid-arid climate derived from high-resolution X-Band radar estimates F. Marra & E. Morin 10.1016/j.atmosres.2017.09.020
- Quantitative precipitation estimation with weather radar using a data- and information-based approach M. Neuper & U. Ehret 10.5194/hess-23-3711-2019
- Validating city-scale surface water flood modelling using crowd-sourced data D. Yu et al. 10.1088/1748-9326/11/12/124011
- Fast Bayesian Regression Kriging Method for Real‐Time Merging of Radar, Rain Gauge, and Crowdsourced Rainfall Data P. Yang & T. Ng 10.1029/2018WR023857
- Hydrological modeling and uncertainty analysis for a snow-covered mountainous river basin A. Gogineni & M. Chintalacheruvu 10.1007/s11600-023-01270-7
- Improving the precipitation accumulation analysis using lightning measurements and different integration periods E. Gregow et al. 10.5194/hess-21-267-2017
- A High-Resolution Quantitative Precipitation Estimate over Alaska through Kriging-Based Merging of Rain Gauges and Short-Range Regional Precipitation Forecasts B. Hoover et al. 10.1175/JTECH-D-21-0132.1
6 citations as recorded by crossref.
- Application of Very Short-Term Rainfall Forecasting to Urban Water Simulation using TREC Method J. Kim et al. 10.3741/JKWRA.2015.48.5.409
- Spatial and temporal variability of rainfall and their effects on hydrological response in urban areas – a review E. Cristiano et al. 10.5194/hess-21-3859-2017
- Radar polygon method: an areal rainfall estimation based on radar rainfall imageries W. Cho et al. 10.1007/s00477-016-1348-x
- Impact of spatial and temporal resolution of rainfall inputs on urban hydrodynamic modelling outputs: A multi-catchment investigation S. Ochoa-Rodriguez et al. 10.1016/j.jhydrol.2015.05.035
- Enhancement of radar rainfall estimates for urban hydrology through optical flow temporal interpolation and Bayesian gauge-based adjustment L. Wang et al. 10.1016/j.jhydrol.2015.05.049
- Parameter sensitivity analysis of SWAT model for streamflow simulation with multisource precipitation datasets J. Guo & X. Su 10.2166/nh.2019.083
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Short summary
A new methodology is proposed in this paper, focusing on improving the applicability of the operational weather radar data to urban hydrology with rain gauge data. The proposed methodology employed a simple yet effective technique to extract additional information (called local singularity structure) from radar data, which was generally ignored in related works. The associated improvement can be particularly seen in capturing storm peak magnitudes, which is critical for urban applications.
A new methodology is proposed in this paper, focusing on improving the applicability of the...
