Improvements to the Automated Real-Time Tidal Elevation System

Abstract

Two statistical techniques for making rapid, short-term predictions of the harmonically determined tidal residual are presented. The techniques are applied to an Automated Real-Time Tidal Elevation System (ARTTES) to improve short-term tide prediction. The techniques investigated are conventionally called 'Kriging' and autoregression. The autoregressive method is based on the Yule-Walker equations for stationary time series. Evaluations using both synthetic and prototype data indicate that although Kriging has a slightly larger root mean square error than the autoregressive technique, the autoregressive technique shows bias, while Kriging gives an unbiased estimate.

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Document Details

Document Type
Technical Report
Publication Date
Oct 01, 1993
Accession Number
ADA273150

Entities

People

  • Andrew W. Garcia
  • Leon E. Borgman
  • Todd L. Walton

Organizations

  • Coastal Engineering Research Center

Tags

Communities of Interest

  • C4I
  • Ground and Sea Platforms
  • Sensors

DTIC Thesaurus Topics

  • Algorithms
  • Army Corps Of Engineers
  • Coastal Engineering
  • Computations
  • Computer Programs
  • Computers
  • Eigenvalues
  • Elevation
  • Engineering
  • Engineers
  • Equations
  • Frequency
  • Low Pass Filters
  • Residuals
  • Stationary
  • Surveys
  • Waterways

Readers

  • Approximation Theory.
  • Coastal and Marine Engineering/Sediment Transport/Hydraulic Engineering