@InProceedings{FalckBCNIOMHTMDVCR:2017:ApSoBr,
               author = "Falck, A. S. and Beneti, C. and Calvetti, L. and Neundorf, R. L. 
                         and Inouye, R. T. and Oliveira, C. and Maske, B. B. and Herdies, 
                         Dirceu Luis and Tomasella, J. and Maggioni, V. and Diniz, 
                         F{\'a}bio Luiz Rodrigues and Vila, Daniel Alejandro and Caram, R. 
                         and Rodriguez, Daniel Andres",
          affiliation = "SIMEPAR and SIMEPAR and {Universidade Federal de Pelotas (UFPel)} 
                         and SIMEPAR and SIMEPAR and SIMEPAR and SIMEPAR and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)} and {Centro Nacional de 
                         Monitoramento e Alertas de Desastres Naturais (CEMADEN)} and GMU 
                         and {Instituto Nacional de Pesquisas Espaciais (INPE)} 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)}",
                title = "Uncertainty assessment of radar rainfall estimates on streamflow 
                         simulation - an application in southern Brazil",
                 year = "2017",
         organization = "American Meteorological Society Annual Meeting, 97.",
             abstract = "The performance of hydrological forecast models depends on the 
                         reliability and availability of real-time precipitation data. Due 
                         to its high spatialtemporal resolution, the availability of radar 
                         precipitation estimates is an option as an additional tool for 
                         monitoring and as input of hydrological forecast models. However, 
                         radar rainfall estimates have errors associated, for example: 
                         echoes from the local topography, conversion of reflectivity in 
                         precipitation rate (e.g., Z-R relationship), among others. In this 
                         context, we evaluated the use of radar ensemble precipitation 
                         estimates generated through the errors associated with its 
                         measure, and as a tool in streamflow simulation. To achieve this 
                         goal, we calibrated the MHD-INPE hydrological model using 
                         raingauge data over upper Igua{\c{c}}u Basin in Brazil. Then we 
                         used the Two Dimensional Satellite Rainfall Error Model (SREM2D), 
                         developed by Hossain and Anagnastou (2006), to simulate the error 
                         propagation of the radar precipitation estimation. This model 
                         quantified the error in space, time, and magnitude.",
  conference-location = "Seattle",
      conference-year = "21-26 jan.",
             language = "en",
        urlaccessdate = "27 abr. 2024"
}