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

• Published in: Water (Basel) 2019-06, Vol.11 (6), p.1273
• Main Authors: Paz, Igor, Willinger, Bernard, Gires, Auguste, Alves de Souza, Bianca, Monier, Laurent, Cardinal, Hervé, Tisserand, Bruno, Tchiguirinskaia, Ioulia, Schertzer, Daniel
• Format: Article
• Language: English
• Subjects: C band; Case studies; Data acquisition; Drainage systems; Earth Sciences; Environmental Engineering; Environmental Sciences; Floods; Geophysics; Hydrology; Information management; Meteorological radar; Meteorological stations, Radar; Meteorology; Modelling; Precipitation; Precipitation variability; Radar; Radar data; Rain; Rain and rainfall; Rainfall; Rainfall measurement; Sciences of the Universe; Sewer systems; Simulation; Software; Statistical analysis; Stochastic models; Stormwater management; Superhigh frequencies; Temporal resolution; Urban areas; Urban catchments; Variability; Weather
• ISSN: 2073-4441; 2073-4441
• DOI: 10.3390/w11061273

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.