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Small-Scale Rainfall Variability Impacts Analyzed by Fully-Distributed Model Using C-Band and X-Band Radar Data

1
HMCO, Ecole des Ponts ParisTech, University of Paris-Est, 77455 Champs-sur-Marne, France
2
Instituto Militar de Engenharia, Praça General Tibúrcio 80, Praia Vermelha, Rio de Janeiro 22290-270, Brazil
3
Veolia Eau Ile-de-France, 91300 Massy, France
4
Direction Technique et Performance, Veolia, 30 rue Madeleine Vionnet, 93300 Aubervilliers, France
5
SIAVB, Syndicat Intercommunal pour l’Assainissement de la Vallée de la Bièvre, 91370 Verrières-le-Buisson, France
6
Veolia Recherche et Innovation, 78600 Maisons-Laffitte, France
*
Author to whom correspondence should be addressed.
Water 2019, 11(6), 1273; https://doi.org/10.3390/w11061273
Received: 7 May 2019 / Revised: 2 June 2019 / Accepted: 13 June 2019 / Published: 18 June 2019
(This article belongs to the Special Issue Study for Ungauged Catchments—Data, Models and Uncertainties)
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Abstract

Recent studies have highlighted the need for high resolution rainfall measurements for better modelling of urban and peri-urban catchment responses. In this work, we used a fully-distributed model called “Multi-Hydro” to study small-scale rainfall variability and its hydrological impacts. The catchment modelled is a semi-urban area located in the southwest region of Paris, an area that has been previously partially validated. At this time, we make some changes to the model, henceforth using its drainage system globally, and we investigate the influence of small-scale rainfall variability by modelling three rainfall events with two different rainfall data inputs: the C-band radar data provided by Météo-France at a 1 km × 1 km × 5 min resolution, and the new X-band radar (recently installed at Ecole des Ponts, France) data at a resolution of 250 m × 250 m × 3.41 min, thereby presenting the gains of better resolution (with the help of Universal Multifractals). Finally, we compare the Multi-Hydro hydrological results with those obtained using an operational semi-distributed model called “Optim Sim” over the same area to revalidate Multi-Hydro modelling, and discuss the model’s limitations and the impacts of data quality and resolution, observing the difficulties associated with semi-distributed models when accounting the spatial variability of weather radar data. This work concludes that it may be useful in future to improve rainfall data acquisition, aiming for better spatio-temporal resolution (now achieved by the weather dual-polarized X-band radars) and data quality when considering small-scale rainfall variability, and to merge deterministic, fully-distributed and stochastic models into a hybrid model which would be capable of taking this small-scale rainfall variability into account. View Full-Text
Keywords: small scale; rainfall variability; X-band radar; fully-distributed model; multi-hydro; multifractals small scale; rainfall variability; X-band radar; fully-distributed model; multi-hydro; multifractals
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Paz, I.; Willinger, B.; Gires, A.; Alves de Souza, B.; Monier, L.; Cardinal, H.; Tisserand, B.; Tchiguirinskaia, I.; Schertzer, D. Small-Scale Rainfall Variability Impacts Analyzed by Fully-Distributed Model Using C-Band and X-Band Radar Data. Water 2019, 11, 1273.

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