@Article{TomasellaGFCDRPNMS:2019:EfBaSc,
               author = "Tomasella, Javier and Gon{\c{c}}alves, A. Sene and Falck, Aline 
                         Schneider and Caram, R. Oliveira and Diniz, F{\'a}bio Luiz 
                         Rodrigues and Rodriguez, Daniel Andres and Prado, Maria 
                         Cec{\'{\i}}lia Rdorigues do and Negr{\~a}o, Anne Caroline and 
                         Medeiros, Gustavo Sueiro and Siqueira, Gracielle Chagas",
          affiliation = "{Centro Nacional de Monitoramento e Alertas de Desastres Naturais 
                         (CEMADEN)} and {Centro Nacional de Monitoramento e Alertas de 
                         Desastres Naturais (CEMADEN)} and {Instituto Nacional de Pesquisas 
                         Espaciais (INPE)} and {Centro Nacional de Monitoramento e Alertas 
                         de Desastres Naturais (CEMADEN)} and {Instituto Nacional de 
                         Pesquisas Espaciais (INPE)} and {Instituto Nacional de Pesquisas 
                         Espaciais (INPE)} and {Instituto Nacional de Pesquisas Espaciais 
                         (INPE)} and {Instituto Nacional de Pesquisas Espaciais (INPE)} and 
                         {Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)}",
                title = "Probabilistic flood forecasting in the Doce Basin in Brazil: 
                         Effects of the basin scale and orientation and the spatial 
                         distribution of rainfall",
              journal = "Journal of Flood Risk Management",
                 year = "2019",
               volume = "12",
               number = "1",
                pages = "e12452",
                month = "mar.",
             keywords = "extreme events, forecasting and warning, natural flood 
                         management.",
             abstract = "We critically examined the performance of probabilistic streamflow 
                         forecasting inthe prediction of flood events in 19 subbasins of 
                         the Doce River in Brazil using theEta (4 members, 5 km spatial 
                         resolution) and European Centre for Medium-RangeWeather Forecasts 
                         (ECMWF; 51 members, 32 km resolution) weather forecastmodels as 
                         inputs for the MHD-INPE hydrological model. We observed that 
                         theshapes and orientations of subbasins influenced the 
                         predictability of floods due tothe orientation of rainfall events. 
                         Streamflow forecasts that use the ECMWF dataas input showed higher 
                         skill scores than those that used the Eta model for subbasinswith 
                         drainage areas larger than 20,000 km2. Since the skill scores were 
                         similar forboth models in smaller subbasins, we concluded that the 
                         grid size of the weathermodel could be important for smaller 
                         catchments, while the number of memberswas crucial for larger 
                         scales. We also evaluated the performance of 
                         probabilisticstreamflow forecasting for the severe flood event of 
                         late 2013 through a compari-son of observations and streamflow 
                         estimations derived from interpolated rainfallfields. In many 
                         cases, the mean of the ensemble outperformed the streamflow 
                         esti-mations from the interpolated rainfall because the spatial 
                         structure of a rainfallevent is better captured by weather 
                         forecast models.",
                  doi = "10.1111/jfr3.12452",
                  url = "http://dx.doi.org/10.1111/jfr3.12452",
                 issn = "1753-318X",
             language = "en",
           targetfile = "tomasella_probabilistic.pdf",
        urlaccessdate = "27 abr. 2024"
}