Simulation of Nonstationary, Non-Gaussian Water Levels on the Great Lakes

Abstract

A methodology for simulating nonstationary, non-Gaussian water levels on the Great Lakes is presented for use in providing input scenarios for erosion modeling on the Great Lakes. The methodology utilizes a low pass filtering technique to reduce the data to a stationary time series after which the data is transformed to a Gaussian series via use of the empirical distribution function coupled with a specialized tail fitting procedure for the extreme values in the data. The reduced series can then be resimulated in the frequency or time domain. The present series is resimulated in the frequency domain via a target spectrum, the spectrum of the reduced series. Inverse procedures are then utilized to simulate the original series. Comparisons of statistical and time series properties on the Great Lakes and it is found that the methodology provides a reasonable simulation for the original data. Keywords: Coastal engineering, Coastal flooding, Coastal planning, Storm erosion, Water level simulation.

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Document Details

Document Type
Technical Report
Publication Date
Jul 01, 1990
Accession Number
ADA226029

Entities

People

  • Leon E. Borgman
  • Todd L. Walton Jr.

Organizations

  • Coastal Engineering Research Center

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Army
  • Army Corps Of Engineers
  • Classification
  • Coastal Engineering
  • Coastal Flooding
  • Databases
  • Discrete Fourier Transforms
  • Distribution Functions
  • Engineering
  • Frequency
  • Frequency Domain
  • Geography
  • Great Lakes
  • Normal Distribution
  • Probability Distributions
  • Spectral Lines
  • Standards

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Coastal Oceanography
  • Computational Modeling and Simulation