Pronóstico de caudales con Filtro de Kalman Discreto en el río Turbio

Translated title of the contribution: Streamflow forecasting for the Turbio River using the discrete Kalman filter

Fernando González-Leiva, Laura Alicia Ibáñez-Castillo, Juan B. Valdés, Mario Alberto Vázquez-Peña, Agustín Ruiz-García

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

This paper proposes the use of the discreet Kalman filter (DKF) along with an autoregressive model with exogenous inputs (ARX) for short-term streamflow forecasting with lead times of 24, 48, 72 and 96 hours. This model was applied to the Turbio River basin, located in the state of Guanajuato and a portion of the state of Jalisco, Mexico. This area is vulnerable to flooding during rainy periods which normally occur in the region. The forecasting was based on available precipitation and streamflow data from the years 2003 and 2004. The results indicate that the forecasts performed with one-step ahead, that is with a 24-hour lead time, present better fits than 48, 72 and 96-hour lead times in terms of Nash-Sutcliffe, MSE and RMSE.

Translated title of the contributionStreamflow forecasting for the Turbio River using the discrete Kalman filter
Original languageSpanish
Pages (from-to)5-24
Number of pages20
JournalTecnologia y Ciencias del Agua
Volume6
Issue number4
StatePublished - Jul 1 2015

Keywords

  • Autoregressive models
  • Kalman filter
  • Short-term streamflow forecasting

ASJC Scopus subject areas

  • Civil and Structural Engineering
  • Water Science and Technology

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