Towards a roadmap for use of radar rainfall data in urban drainage

Einfalt, Thomas; Arnbjerg‐Nielsen, Karsten; Golz, Claudia; Jensen, N. E.; QUIRMBACH, M; Vaes, Guido; Vieux, Baxter E.

doi:10.1016/s0022-1694(04)00365-8

Cited by 117 publications

(92 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Rainfall is an important driver for many hydrological processes and represents one of the main sources of uncertainty in studying hydrological response (Niemczynowicz, 1988;Einfalt et al, 2004;Thorndahl et al, 2017;Rico-Ramirez et al, 2015). Urban areas affect the local hydrological system, not only by increasing the imperviousness degree of the soil but also by changing rainfall generation and intensity patterns.…”

Section: Rainfall Measurement and Variability In Urban Regionsmentioning

confidence: 99%

“…In the last decades considerable advances in quantitative estimation of distributed rainfall have been made, thanks to new technologies, in particular weather radars (Leijnse et al, 2007;van de Beek et al, 2010;Otto and Russchenberg, 2011). These developments have been applied in urban hydrology researches; see Einfalt et al (2004) and Thorndahl et al (2017) for a review. The hydrological response is sensitive to small-scale rainfall variability in both space and time (Faures et al, 1995;Emmanuel et al, 2012;Smith et al, 2012;Ochoa-Rodriguez et al, 2015b), due to a typically high degree of imperviousness and to a high spatial variability of urban land use.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Spatial and temporal variability of rainfall and their effects on hydrological response in urban areas – a review

Cristiano

Veldhuis

Giesen

2017

Hydrol. Earth Syst. Sci.

264

146

View full text Add to dashboard Cite

Abstract. In urban areas, hydrological processes are characterized by high variability in space and time, making them sensitive to small-scale temporal and spatial rainfall variability. In the last decades new instruments, techniques, and methods have been developed to capture rainfall and hydrological processes at high resolution. Weather radars have been introduced to estimate high spatial and temporal rainfall variability. At the same time, new models have been proposed to reproduce hydrological response, based on smallscale representation of urban catchment spatial variability. Despite these efforts, interactions between rainfall variability, catchment heterogeneity, and hydrological response remain poorly understood. This paper presents a review of our current understanding of hydrological processes in urban environments as reported in the literature, focusing on their spatial and temporal variability aspects. We review recent findings on the effects of rainfall variability on hydrological response and identify gaps where knowledge needs to be further developed to improve our understanding of and capability to predict urban hydrological response.

show abstract

Section: Rainfall Measurement and Variability In Urban Regionsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Spatial and temporal variability of rainfall and their effects on hydrological response in urban areas – a review

Cristiano

Veldhuis

Giesen

2017

Hydrol. Earth Syst. Sci.

264

146

View full text Add to dashboard Cite

show abstract

“…The use of radar measurements for urban hydrological applications has substantially increased during the last years (e.g., Berne et al, 2004;Einfalt et al, 2004;Bruni et al, 2015). Given the fast response time of urban catchments and sewer systems, radar-based very short-term precipitation forecasting (nowcasting) has the potential to extend the lead time of hydrological and hydraulic flow predictions.…”

Section: Introductionmentioning

confidence: 99%

Development and verification of a real-time stochastic precipitation nowcasting system for urban hydrology in Belgium

Foresti

Reyniers

Seed

et al. 2016

Hydrol. Earth Syst. Sci.

View full text Add to dashboard Cite

Abstract. The Short-Term Ensemble Prediction System (STEPS) is implemented in real-time at the Royal Meteorological Institute (RMI) of Belgium. The main idea behind STEPS is to quantify the forecast uncertainty by adding stochastic perturbations to the deterministic Lagrangian extrapolation of radar images. The stochastic perturbations are designed to account for the unpredictable precipitation growth and decay processes and to reproduce the dynamic scaling of precipitation fields, i.e., the observation that largescale rainfall structures are more persistent and predictable than small-scale convective cells. This paper presents the development, adaptation and verification of the STEPS system for Belgium (STEPS-BE). STEPS-BE provides in realtime 20-member ensemble precipitation nowcasts at 1 km and 5 min resolutions up to 2 h lead time using a 4 C-band radar composite as input. In the context of the PLURISK project, STEPS forecasts were generated to be used as input in sewer system hydraulic models for nowcasting urban inundations in the cities of Ghent and Leuven. Comprehensive forecast verification was performed in order to detect systematic biases over the given urban areas and to analyze the reliability of probabilistic forecasts for a set of case studies in 2013 and 2014. The forecast biases over the cities of Leuven and Ghent were found to be small, which is encouraging for future integration of STEPS nowcasts into the hydraulic models. Probabilistic forecasts of exceeding 0.5 mm h −1 are reliable up to 60-90 min lead time, while the ones of exceeding 5.0 mm h −1 are only reliable up to 30 min. The STEPS ensembles are slightly under-dispersive and represent only 75-90 % of the forecast errors.

show abstract

“…Although radar data have been available for almost half a century, operational assimilation has not been widely achieved to date. Many hydrological models have been developed and refined over the past four decades for research and operational purposes (Einfalt et al, 2004;Zhu et al, 2014), and their characteristics must be fully understood if they are to be used effectively. Some models use gridded rainfall data, but their calculated runoff is often output at intervals of greater than 1 hr.…”

Section: Application Of Weather Radar Data For Hydrological Modelingmentioning

confidence: 99%

Quantitative Precipitation Estimation and Hydrological Modeling in Japan

Shakti

2017

J. Japan Soc. Hydrol. and Water Resour.

View full text Add to dashboard Cite

Towards a roadmap for use of radar rainfall data in urban drainage

Cited by 117 publications

References 0 publications

Spatial and temporal variability of rainfall and their effects on hydrological response in urban areas – a review

Spatial and temporal variability of rainfall and their effects on hydrological response in urban areas – a review

Development and verification of a real-time stochastic precipitation nowcasting system for urban hydrology in Belgium

Quantitative Precipitation Estimation and Hydrological Modeling in Japan

Contact Info

Product

Resources

About