Coupling WRF and NRCS-CN Models for Flood Forecasting in Paraíba do Meio River Basin in Alagoas, Brazil
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....
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| Format: | Article |
| Language: | English |
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Sociedade Brasileira de Meteorologia
2020-01-01
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| Series: | Revista Brasileira de Meteorologia |
| Subjects: | |
| Online Access: | http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0102-77862019000400545&tlng=en |
| _version_ | 1828126130188582912 |
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| author | André Gonçalo dos Santos José Nilson Beserra Campos Rosiberto Salustiano Silva Junior |
| author_facet | André Gonçalo dos Santos José Nilson Beserra Campos Rosiberto Salustiano Silva Junior |
| author_sort | André Gonçalo dos Santos |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-04-11T15:30:00Z |
| format | Article |
| id | doaj.art-f7bb05b4b7f244aa8980409cb718a874 |
| institution | Directory Open Access Journal |
| issn | 1982-4351 |
| language | English |
| last_indexed | 2024-04-11T15:30:00Z |
| publishDate | 2020-01-01 |
| publisher | Sociedade Brasileira de Meteorologia |
| record_format | Article |
| series | Revista Brasileira de Meteorologia |
| spelling | doaj.art-f7bb05b4b7f244aa8980409cb718a8742022-12-22T04:16:09ZengSociedade Brasileira de MeteorologiaRevista Brasileira de Meteorologia1982-43512020-01-0134454555610.1590/0102-7786344068Coupling WRF and NRCS-CN Models for Flood Forecasting in Paraíba do Meio River Basin in Alagoas, BrazilAndré Gonçalo dos Santoshttps://orcid.org/0000-0003-1826-4787José Nilson Beserra Camposhttps://orcid.org/0000-0001-6321-1284Rosiberto Salustiano Silva Juniorhttps://orcid.org/0000-0001-7152-0095Abstract 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.http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0102-77862019000400545&tlng=enWRF modelNRCS-CN modelshort-term rainfall forecastingflood forecast |
| spellingShingle | André Gonçalo dos Santos José Nilson Beserra Campos Rosiberto Salustiano Silva Junior Coupling WRF and NRCS-CN Models for Flood Forecasting in Paraíba do Meio River Basin in Alagoas, Brazil Revista Brasileira de Meteorologia WRF model NRCS-CN model short-term rainfall forecasting flood forecast |
| title | Coupling WRF and NRCS-CN Models for Flood Forecasting in Paraíba do Meio River Basin in Alagoas, Brazil |
| title_full | Coupling WRF and NRCS-CN Models for Flood Forecasting in Paraíba do Meio River Basin in Alagoas, Brazil |
| title_fullStr | Coupling WRF and NRCS-CN Models for Flood Forecasting in Paraíba do Meio River Basin in Alagoas, Brazil |
| title_full_unstemmed | Coupling WRF and NRCS-CN Models for Flood Forecasting in Paraíba do Meio River Basin in Alagoas, Brazil |
| title_short | Coupling WRF and NRCS-CN Models for Flood Forecasting in Paraíba do Meio River Basin in Alagoas, Brazil |
| title_sort | coupling wrf and nrcs cn models for flood forecasting in paraiba do meio river basin in alagoas brazil |
| topic | WRF model NRCS-CN model short-term rainfall forecasting flood forecast |
| url | http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0102-77862019000400545&tlng=en |
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