A radar rainfall forecasting method designed for hydrological purposes

Einfalt, Thomas; Denœux, Thierry; Jacquet, G

doi:10.1016/0022-1694(90)90058-6

Cited by 59 publications

(46 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The radar operated by Météo-France is located in the city of Manduel, 40 km south east of Anduze. The radar images provided by the SCP-GD were processed with the software CALA-MAR® developed by the RHEA company (Einfalt et al, 1990;Jacquet et al, 2004). The CALAMAR® software produces rainfall estimates obtained from radar images adjusted with a time-varying correction factor, using the rain gauge monitoring network for calibration.…”

Section: Hydrological Datasetsmentioning

confidence: 99%

Impact of rainfall spatial distribution on rainfall-runoff modelling efficiency and initial soil moisture conditions estimation

Tramblay

Bouvier

Ayral³

et al. 2011

Nat. Hazards Earth Syst. Sci.

View full text Add to dashboard Cite

Abstract.A good knowledge of rainfall is essential for hydrological operational purposes such as flood forecasting. The objective of this paper was to analyze, on a relatively large sample of flood events, how rainfall-runoff modeling using an event-based model can be sensitive to the use of spatial rainfall compared to mean areal rainfall over the watershed. This comparison was based not only on the model's efficiency in reproducing the flood events but also through the estimation of the initial conditions by the model, using different rainfall inputs. The initial conditions of soil moisture are indeed a key factor for flood modeling in the Mediterranean region. In order to provide a soil moisture index that could be related to the initial condition of the model, the soil moisture output of the Safran-Isba-Modcou (SIM) model developed by Météo-France was used. This study was done in the Gardon catchment (545 km 2 ) in South France, using uniform or spatial rainfall data derived from rain gauge and radar for 16 flood events. The event-based model considered combines the SCS runoff production model and the Lag and Route routing model. Results show that spatial rainfall increases the efficiency of the model. The advantage of using spatial rainfall is marked for some of the largest flood events. In addition, the relationship between the model's initial condition and the external predictor of soil moisture provided by the SIM model is better when using spatial rainfall, in particular when using spatial radar data with R 2 values increasing from 0.61 to 0.72.

show abstract

Section: Hydrological Datasetsmentioning

confidence: 99%

Impact of rainfall spatial distribution on rainfall-runoff modelling efficiency and initial soil moisture conditions estimation

Tramblay

Bouvier

Ayral³

et al. 2011

Nat. Hazards Earth Syst. Sci.

View full text Add to dashboard Cite

show abstract

“…Austin and Bellon, 1974;Einfalt et al, 1990;Sharif et al, 2006;Smith et al, 2007;Javier et al, 2007;Achleitner et al, 2009;Einfalt et al, 2009;Schellart et al, 2012a;Wang et al, 2012;Ntegeka et al, 2015). Due to the short response time of the urban drainage system and the short lifetime and small spatial size of convective rain cells, urban rainfall forecasts are only reliable for very short lead times (Achleitner et al, 2009;Foresti et al, 2016).…”

Section: Nowcasting Of Radar Rainfallmentioning

confidence: 99%

“…Several generic methods have been developed to nowcast radar data, based on deterministic approaches, e.g. TREC (Rinehart and Garvey, 1978), CO-TREC (Li et al, 1995), SCIT (Johnson et al, 1998;Mecklenburg et al, 2000), and SCOUT (Einfalt et al, 1990), or stochastic approaches, e.g. MAPLE (Turner et al, 2004), SBMcast (Berenguer et al, 2005(Berenguer et al, , 2011, and STEPS (Bowler et al, 2006).…”

Section: Nowcasting Of Radar Rainfallmentioning

confidence: 99%

Weather radar rainfall data in urban hydrology

Thorndahl

Einfalt

Willems

et al. 2017

Hydrol. Earth Syst. Sci.

Self Cite

159

108

View full text Add to dashboard Cite

Abstract. Application of weather radar data in urban hydrological applications has evolved significantly during the past decade as an alternative to traditional rainfall observations with rain gauges. Advances in radar hardware, data processing, numerical models, and emerging fields within urban hydrology necessitate an updated review of the state of the art in such radar rainfall data and applications. Three key areas with significant advances over the past decade have been identified: (1) temporal and spatial resolution of rainfall data required for different types of hydrological applications, (2) rainfall estimation, radar data adjustment and data quality, and (3) nowcasting of radar rainfall and real-time applications. Based on these three fields of research, the paper provides recommendations based on an updated overview of shortcomings, gains, and novel developments in relation to urban hydrological applications. The paper also reviews how the focus in urban hydrology research has shifted over the last decade to fields such as climate change impacts, resilience of urban areas to hydrological extremes, and online prediction/warning systems. It is discussed how radar rainfall data can add value to the aforementioned emerging fields in current and future applications, but also to the analysis of integrated water systems.

show abstract

“…By using the mean squared error as performance measure between observed and forecast rainfall at different LTs in combination with an error component analysis they found that 70% of the events were predictable until up to 30 min LTs within reliable bounds and 50% of the events showed reasonable LTs up to 60 min. Achleitner et al (2009) used the tracking approach by Einfalt et al (1990) for radar rainfall forecasting to simulate CSO spills in the city of Linz. Five events were studied and it was concluded that the level of uncertainties in the forecast was only tolerable for a LT of up to 90 min, and that the uncertainty in the forecast precipitation exceeds, by far, the associated uncertainty in the flow predictions.…”

Section: Introductionmentioning

confidence: 99%

Comparing quantitative precipitation forecast methods for prediction of sewer flows in a small urban area

Schellart

Liguori

Krämer

et al. 2014

Hydrological Sciences Journal

View full text Add to dashboard Cite

., 2014. Comparing quantitative precipitation forecast methods for prediction of sewer flows in a small urban area. Hydrological Sciences Journal, 59 (7), 1418-1436. http://dx.doi.org/ 10. 1080/02626667.2014.920505 Abstract Due to the relatively small spatial scale, as well as rapid response, of urban drainage systems, the use of quantitative rainfall forecasts for providing quantitative flow and depth predictions is a challenging task. Such predictions are important when consideration is given to urban pluvial flooding and receiving water quality, and it is worthwhile to investigate the potential for improved forecasting. In this study, three quantitative precipitation forecast methods of increasing complexity were compared and used to create quantitative forecasts of sewer flows 0-3 h ahead in the centre of a small town in the north of England. The HyRaTrac radar nowcast model was employed, as well as two different versions of the more complex STEPS model. The STEPS model was used as a deterministic nowcasting system, and was also blended with the Numerical Weather Prediction (NWP) model MM5 to investigate the potential of increasing forecast lead-times (LTs) using high-resolution NWP. Predictive LTs between 15 and 90 min gave acceptable results, but were a function of the event type. It was concluded that higher resolution rainfall estimation as well as nowcasts are needed for prediction of both local pluvial flooding and combined sewer overflow spill events.Key words rainfall runoff; radar nowcasting; numerical weather prediction; flow forecasting; urban drainageComparaison des méthodes quantitatives de prévision des précipitations pour la prévision du débit des égouts dans une petite zone urbaine Résumé En raison de l'échelle spatiale relativement petite ainsi que de la réponse rapide des systèmes de drainage urbain, l'utilisation des prévisions quantitatives des précipitations pour fournir des prévisions quantitatives de débits et de hauteurs d'eau est une tâche difficile. Ces prévisions sont importantes lorsque l'on s'intéresse aux inondations pluviales urbaines et à la qualité des eaux réceptrices, et il vaut la peine de chercher les possibilités d'améliorer les prévisions. Dans cette étude, nous avons utilisé et comparé trois méthodes de prévision quantitative des précipitations, de complexité croissante, réalisant des prévisions quantitatives du débit des égouts de 0 à 3 h à l'avance dans le centre d'une petite ville du Nord de l'Angleterre. Nous avons utilisé le modèle de prévision immédiate radar HyRaTrac, ainsi que deux versions différentes du modèle plus complexe STEPS. Le modèle STEPS a été utilisé comme système de prévision immédiate déterministe, et a également été couplé avec le modèle de prévision météorologique numérique (PMN) MM5 pour étudier la possibilité d'augmenter l'horizon de prévision grâce à l'utilisation de PMN à haute résolution. Des résultats acceptables ont été obtenus pour des horizons de prévision compris entre 15 et 90 min, mais ils dépendaient du type d'événement météorolo...

show abstract

A radar rainfall forecasting method designed for hydrological purposes

Cited by 59 publications

References 15 publications

Impact of rainfall spatial distribution on rainfall-runoff modelling efficiency and initial soil moisture conditions estimation

Impact of rainfall spatial distribution on rainfall-runoff modelling efficiency and initial soil moisture conditions estimation

Weather radar rainfall data in urban hydrology

Comparing quantitative precipitation forecast methods for prediction of sewer flows in a small urban area

Contact Info

Product

Resources

About