Predicción de caudales en la cabecera de la cuenca del Paute mediante el modelo DBM

Autores/as

  • A. Quichimbo Departamento de Recursos Hídricos y Ciencias Ambientales, Universidad de Cuenca, Av. 12 de abril S/N, Cuenca, Ecuador.
  • R. F. Vázquez Departamento de Recursos Hídricos y Ciencias Ambientales, Universidad de Cuenca, Av. 12 de abril S/N, Cuenca, Ecuador. Facultad de Ingeniería, Universidad de Cuenca, Av. 12 de abril S/N, Cuenca, Ecuador.

Resumen

RESUMEN

El modelo Mecanicista Basado en Datos (DBM) se ha utilizado conjuntamente con el filtro de Kalman (como una técnica de asimilación de datos) para la predicción de caudales en una subcuenca ubicada en la parte alta de la cuenca del río Paute. Los resultados sugieren que el modelo DBM, conjuntamente con la técnica de asimilación de datos empleada, produce predicciones de mejor calidad en la subcuenca de estudio, en comparación al uso exclusivo del modelo DBM; de hecho, el filtro de Kalman provee una medida de la incertidumbre asociada al empleo del modelo DBM para efectuar pronósticos de caudales. Estos resultados, no solo que alientan el uso futuro de modelos basados en técnicas de minado de datos, sino que además alientan el uso de la herramienta actual tanto para realizar predicciones como para el pronóstico y alerta temprana en cuencas Andinas.

Palabras clave: Modelización numérica; DBM; asimilación de datos; función de transferencia (TF); parámetros dependientes de estado (SDP).

ABSTRACT

The Data-Based Mechanistic (DBM) model was used in conjunction with the Kalman filter (as a data assimilation technique), to predict the discharge from a sub-catchment located in the upper part of the Paute basin. The results showed that this conjunctive use of the DBM model and the Kalman filter produced better predictions of the discharge in the study site, as compared to the solely use of the DBM model; indeed, the use of the Kalman filter provided an estimate of the uncertainty associated to the use of the DBM model for forecasting purposes. These results not only motivate the future use of data mining techniques for discharge forecasting, but also encourage the use of the current tool for both, prediction as well as forecasting extreme events on Andean catchments.

Keywords: Numerical modelling; DBM; data assimilation; transfer function (TF); state dependent parameters (SDP).

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Citas

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Publicado

2016-01-05

Cómo citar

Quichimbo, A., & Vázquez, R. F. (2016). Predicción de caudales en la cabecera de la cuenca del Paute mediante el modelo DBM. Maskana, 5, 125–134. Recuperado a partir de https://publicaciones.ucuenca.edu.ec/ojs/index.php/maskana/article/view/560