Daily river level forecast based on the development of an artificial neural network: case study in La Virginia - Risaralda
The municipality of La Virginia (Risaralda, Colombia) is constantly affected by fl oods that originate from increased water levels in the Cauca River. Disaster relief agencies do not currently have adequate monitoring systems to identify potential overfl ow events in time-series observations to pre...
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| Format: | Article |
| Language: | English |
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Universidad de Antioquia
2015-09-01
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| Series: | Revista Facultad de Ingeniería Universidad de Antioquia |
| Subjects: | |
| Online Access: | https://revistas.udea.edu.co/index.php/ingenieria/article/view/20792 |
| _version_ | 1797861787435008000 |
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| author | Tito Morales-Pinzón Juan David Céspedes-Restrepo Manuel Tiberio Flórez-Calderón |
| author_facet | Tito Morales-Pinzón Juan David Céspedes-Restrepo Manuel Tiberio Flórez-Calderón |
| author_sort | Tito Morales-Pinzón |
| collection | DOAJ |
| description |
The municipality of La Virginia (Risaralda, Colombia) is constantly affected by fl oods that originate from increased water levels in the Cauca River. Disaster relief agencies do not currently have adequate monitoring systems to identify potential overfl ow events in time-series observations to prevent fl ood damage to homes or injury to the general population. In this paper, various simulation models are proposed for the prediction of fl ooding that contributes as a technical tool to the development and implementation of early warning systems to improve the responsiveness of disaster relief agencies. The models, which are based on artifi cial neural networks, take hydroclimatological information from different stations along the Cauca River Basin, and the trend indicates the average daily level of the river within the next 48 hours. This methodology can be easily applied to other urban areas exposed to fl ood risks in developing countries.
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| first_indexed | 2024-04-09T22:10:01Z |
| format | Article |
| id | doaj.art-d6796bd13d9e4c33a4815fd410223b26 |
| institution | Directory Open Access Journal |
| issn | 0120-6230 2422-2844 |
| language | English |
| last_indexed | 2024-04-09T22:10:01Z |
| publishDate | 2015-09-01 |
| publisher | Universidad de Antioquia |
| record_format | Article |
| series | Revista Facultad de Ingeniería Universidad de Antioquia |
| spelling | doaj.art-d6796bd13d9e4c33a4815fd410223b262023-03-23T12:30:58ZengUniversidad de AntioquiaRevista Facultad de Ingeniería Universidad de Antioquia0120-62302422-28442015-09-017610.17533/udea.redin.n76a06Daily river level forecast based on the development of an artificial neural network: case study in La Virginia - RisaraldaTito Morales-Pinzón0Juan David Céspedes-Restrepo1Manuel Tiberio Flórez-Calderón2Technological University of PereiraTechnological University of PereiraTechnological University of Pereira The municipality of La Virginia (Risaralda, Colombia) is constantly affected by fl oods that originate from increased water levels in the Cauca River. Disaster relief agencies do not currently have adequate monitoring systems to identify potential overfl ow events in time-series observations to prevent fl ood damage to homes or injury to the general population. In this paper, various simulation models are proposed for the prediction of fl ooding that contributes as a technical tool to the development and implementation of early warning systems to improve the responsiveness of disaster relief agencies. The models, which are based on artifi cial neural networks, take hydroclimatological information from different stations along the Cauca River Basin, and the trend indicates the average daily level of the river within the next 48 hours. This methodology can be easily applied to other urban areas exposed to fl ood risks in developing countries. https://revistas.udea.edu.co/index.php/ingenieria/article/view/20792flood forecastingflood riskartificial neural networks |
| spellingShingle | Tito Morales-Pinzón Juan David Céspedes-Restrepo Manuel Tiberio Flórez-Calderón Daily river level forecast based on the development of an artificial neural network: case study in La Virginia - Risaralda Revista Facultad de Ingeniería Universidad de Antioquia flood forecasting flood risk artificial neural networks |
| title | Daily river level forecast based on the development of an artificial neural network: case study in La Virginia - Risaralda |
| title_full | Daily river level forecast based on the development of an artificial neural network: case study in La Virginia - Risaralda |
| title_fullStr | Daily river level forecast based on the development of an artificial neural network: case study in La Virginia - Risaralda |
| title_full_unstemmed | Daily river level forecast based on the development of an artificial neural network: case study in La Virginia - Risaralda |
| title_short | Daily river level forecast based on the development of an artificial neural network: case study in La Virginia - Risaralda |
| title_sort | daily river level forecast based on the development of an artificial neural network case study in la virginia risaralda |
| topic | flood forecasting flood risk artificial neural networks |
| url | https://revistas.udea.edu.co/index.php/ingenieria/article/view/20792 |
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