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| Formato: | Artículo científico |
| Lenguaje: | en |
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Universidad de Guanajuato
2008
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| Acceso en línea: | https://www.redalyc.org/articulo.oa?id=41618202 |
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| _version_ | 1866572792414076928 |
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| author | Sergio Ledesma |
| author_facet | Sergio Ledesma |
| contents | Weather Radar Estimations Feeding an Artificial Neural Network Model Sergio Ledesma Gustavo Cerda Villafaña Dawei Han Multidisciplinarias (Ciencias Sociales) runoff Rainfall Lumped model Weather radar Distributed model The application of ANNs (Artifi cial Neural Networks) has been studied by many researchersin modelling rainfall runoff processes. However, the work so far has been focused on the rainfalldata from traditional raingauges. Weather radar is a modern technology which couldprovide high resolution rainfall in time and space. In this study, a comparison in rainfallrunoff modelling between the raingauge and weather radar has been carried out. The datawere collected from Brue catchment in Southwest of England, with 49 raingauges covering136 km2 and two C-band weather radars. This raingauge network is extremely dense (forresearch purposes) and does not represent the usual raingauge density in operational fl oodforecasting systems. The ANN models were set up with both lumped and spatial rainfallinput. The results showed that raingauge data outperformed radar data in all the eventstested, regardless of the lumped and spatial input. 2008 artículo científico 0188-6266 https://www.redalyc.org/articulo.oa?id=41618202 en http://www.redalyc.org/revista.oa?id=416 Acta Universitaria application/pdf Universidad de Guanajuato Acta Universitaria (México) Num.2 Vol.18 |
| format | Artículo científico |
| id | redalyc_41618202 |
| language | en |
| publishDate | 2008 |
| publisher | Universidad de Guanajuato |
| spellingShingle | Weather Radar Estimations Feeding an Artificial Neural Network Model Sergio Ledesma Multidisciplinarias (Ciencias Sociales) runoff Rainfall Lumped model Weather radar Distributed model Weather Radar Estimations Feeding an Artificial Neural Network Model Sergio Ledesma Gustavo Cerda Villafaña Dawei Han Multidisciplinarias (Ciencias Sociales) runoff Rainfall Lumped model Weather radar Distributed model The application of ANNs (Artifi cial Neural Networks) has been studied by many researchersin modelling rainfall runoff processes. However, the work so far has been focused on the rainfalldata from traditional raingauges. Weather radar is a modern technology which couldprovide high resolution rainfall in time and space. In this study, a comparison in rainfallrunoff modelling between the raingauge and weather radar has been carried out. The datawere collected from Brue catchment in Southwest of England, with 49 raingauges covering136 km2 and two C-band weather radars. This raingauge network is extremely dense (forresearch purposes) and does not represent the usual raingauge density in operational fl oodforecasting systems. The ANN models were set up with both lumped and spatial rainfallinput. The results showed that raingauge data outperformed radar data in all the eventstested, regardless of the lumped and spatial input. 2008 artículo científico 0188-6266 https://www.redalyc.org/articulo.oa?id=41618202 en http://www.redalyc.org/revista.oa?id=416 Acta Universitaria application/pdf Universidad de Guanajuato Acta Universitaria (México) Num.2 Vol.18 |
| title | Weather Radar Estimations Feeding an Artificial Neural Network Model |
| topic | Multidisciplinarias (Ciencias Sociales) runoff Rainfall Lumped model Weather radar Distributed model |
| url | https://www.redalyc.org/articulo.oa?id=41618202 |