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      Coupling WRF and NRCS-CN Models for Flood Forecasting in Paraíba do Meio River Basin in Alagoas, Brazil Translated title: Acoplamento dos modelos WRF e NRCS-CN para previsão de cheias na bacia do rio Paraíba do Meio em Alagoas, Brasil

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          Abstract

          Abstract Coupling the WRF and NRCS-CN models was assessed as a tool for a flood forecast system. The models were applied to the Paraíba do Meio River basin, located in Alagoas, Brazil. FNL (Final Analysis GFS) data provided by the Global Forecast System model were used as initial conditions for WRF. Precipitations and observed discharges were collected in data collection platforms. Nine microphysics configurations were used to optimize WRF forecast. For hydrological, the automatic calibrations, available in HMS was used to get the optimum CN model parameters. Optimized precipitations Model performance was assessed with the indicators: bias, root-mean-square error, Pearson’s linear correlation coefficient, Nash-Sutcliffe coefficient, Heidke skill score, hit rate and false alarm rate. WRF´s predictive ability for the optimum configuration was satisfactory. The NRCS-CN yielded good results. The predictive ability of the hydrological model was ranked between satisfactory and acceptable. In a flood forecasting step, the coupled model yielded Nash-Sutcliffe of 0.749 and 0.572 for Atalaia and Viçosa basins. Overall, the method showed potential for the development of a flood alert system.

          Translated abstract

          Resumo O acoplamento dos modelos WRF e NRCS-CN foram avaliados como ferramentas para um sistema de previsão de cheias. Os modelos foram aplicados na bacia hidrográfica do rio Paraíba do Meio, localizada em Alagoas, Brasil. FNL (Final Análises GFS) dados obtidos do Sistema de Previsão Global foram utilizados como condições iniciais para o WRF. Precipitações e vazões observadas foram coletadas das plataformas de observação de dados. Nove configurações de microfísica foram usadas para otimizar as previsões do WRF. Para o modelo hidrológico, foram utilizadas calibrações automáticas disponíveis no HMS. Foram otimizados os parâmetros do modelo NRCS-CN. O desempenho dos modelos foi avaliado com os indicadores: viés, mínimo erro quadrático, coeficiente de correlação linear de Pearson, coeficiente de Nash-Sutcliffe, Heidke skill score, acertos e alarmes falsos. A habilidade de previsão do WRF para a configuração ótima foi considerada satisfatória. O modelo NRCS-CN gerou bons resultados de cheias. A habilidade preditiva do modelo hidrológico variou de satisfatória a aceitável. Na etapa de previsão de cheias, o modelo acoplado gerou coeficientes de Nash-Sutcliffe de 0.749 e 0.572 para as bacias Atalaia e Viçosa. Em seu todo, o modelo acoplado apresentou um bom potencial para desenvolvimento de sistemas de alerta.

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          Most cited references 38

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          Explicit Forecasts of Winter Precipitation Using an Improved Bulk Microphysics Scheme. Part I: Description and Sensitivity Analysis

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            The integrated WRF/urban modelling system: development, evaluation, and applications to urban environmental problems

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              A Combined Local and Nonlocal Closure Model for the Atmospheric Boundary Layer. Part I: Model Description and Testing

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                Author and article information

                Contributors
                Role: ND
                Role: ND
                Role: ND
                Journal
                rbmet
                Revista Brasileira de Meteorologia
                Rev. bras. meteorol.
                Sociedade Brasileira de Meteorologia (São Paulo, SP, Brazil )
                0102-7786
                1982-4351
                December 2019
                : 34
                : 4
                : 545-556
                Affiliations
                Maceió orgnameUniversidade Federal de Alagoas orgdiv1Instituto de Ciências Atmosféricas Brazil
                Fortaleza Ceará orgnameUniversidade Federal do Ceará orgdiv1Departamento de Engenharia Hidráulica e Ambiental Brazil
                Article
                S0102-77862019000400545 S0102-7786(19)03400400545
                10.1590/0102-7786344068

                This work is licensed under a Creative Commons Attribution 4.0 International License.

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                Figures: 0, Tables: 0, Equations: 0, References: 45, Pages: 12
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