Early flood warning system for the Arauca river based on artificial intelligence techniques

This article establishes the design of an early warning system for flooding in the Arauca River, in the municipality of Arauca, Colombia. The information corresponding to this study is extracted from the IDEAM and is processed obtaining a model through the variables that intervene such as precipitation, level and flow. This information model supplies the data to the mathematical model corresponding to the river channel, which is obtained from three kinds of trends: linear, power and potential relationships. This model is compared with an observer based on intelligent techniques such as neural networks and ANFIS, which make the difference of their outputs and a residue is obtained that is in charge of supplying the information that provides the current state of the river level under study, which in turn generates alerts that are addressed by government entities dedicated to risk management.

• Tipo de recurso: http://purl.org/coar/resource_type/c_6573
• Fecha de publicación: 2022
• Institución: Universidad Pedagógica y Tecnológica de Colombia
• Repositorio: RiUPTC: Repositorio Institucional UPTC
• Idioma: spa
• OAI Identifier: oai:repositorio.uptc.edu.co:001/10401
• Acceso en línea: https://revistas.uptc.edu.co/index.php/investigacion_duitama/article/view/15274; https://repositorio.uptc.edu.co/handle/001/10401
• Palabra clave: flood; water level; mathematical model; early warnings; inundación; nivel de agua; modelo matemático; alerta temprana
• License: Derechos de autor 2022 Revista de Investigación, Desarrollo e Innovación