Kalman filter estimation model in flood forecasting

Tahir Husain*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

18 Scopus citations

Abstract

Elementary precipitation and runoff estimation problems associated with hydrologic data collection networks are formulated in conjunction with the Kalman Filter Estimation Model. Examples involve the estimation of runoff using data from a single precipitation station and also from a number of precipitation stations. The formulations demonstrate the role of state-space, measurement, and estimation equations of the Kalman Filter Model in flood forecasting. To facilitate the formulation, the unit hydrograph concept and antecedent precipitation index is adopted in the estimation model. The methodology is then applied to estimate various flood events in the Carnation Creek of British Columbia.

Original languageEnglish
Pages (from-to)15-21
Number of pages7
JournalAdvances in Water Resources
Volume8
Issue number1
DOIs
StatePublished - Mar 1985

Keywords

  • Carnation Creek
  • Kalman filter
  • estimation
  • measurement
  • multivariate
  • rainfall
  • state-space
  • statistics

ASJC Scopus subject areas

  • Water Science and Technology

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