Nonstationarities in Hydrologic and Environmental Time Series

  • A. Ramachandra Rao
  • Khaled H. Hamed
  • Huey-Long Chen

Part of the Water Science and Technology Library book series (WSTL, volume 45)

Table of contents

  1. Front Matter
    Pages i-xxvii
  2. A. Ramachandra Rao, Khaled H. Hamed, Huey-Long Chen
    Pages 1-3
  3. A. Ramachandra Rao, Khaled H. Hamed, Huey-Long Chen
    Pages 4-26
  4. A. Ramachandra Rao, Khaled H. Hamed, Huey-Long Chen
    Pages 27-55
  5. A. Ramachandra Rao, Khaled H. Hamed, Huey-Long Chen
    Pages 56-114
  6. A. Ramachandra Rao, Khaled H. Hamed, Huey-Long Chen
    Pages 115-159
  7. A. Ramachandra Rao, Khaled H. Hamed, Huey-Long Chen
    Pages 160-212
  8. A. Ramachandra Rao, Khaled H. Hamed, Huey-Long Chen
    Pages 213-252
  9. A. Ramachandra Rao, Khaled H. Hamed, Huey-Long Chen
    Pages 253-276
  10. A. Ramachandra Rao, Khaled H. Hamed, Huey-Long Chen
    Pages 277-311
  11. A. Ramachandra Rao, Khaled H. Hamed, Huey-Long Chen
    Pages 312-319
  12. A. Ramachandra Rao, Khaled H. Hamed, Huey-Long Chen
    Pages 320-346
  13. A. Ramachandra Rao, Khaled H. Hamed, Huey-Long Chen
    Pages 347-357
  14. Back Matter
    Pages 359-365

About this book

Introduction

Conventionally, time series have been studied either in the time domain or the frequency domain. The representation of a signal in the time domain is localized in time, i.e . the value of the signal at each instant in time is well defined . However, the time representation of a signal is poorly localized in frequency , i.e. little information about the frequency content of the signal at a certain frequency can be known by looking at the signal in the time domain . On the other hand, the representation of a signal in the frequency domain is well localized in frequency, but is poorly localized in time, and as a consequence it is impossible to tell when certain events occurred in time. In studying stationary or conditionally stationary processes with mixed spectra , the separate use of time domain and frequency domain analyses is sufficient to reveal the structure of the process . Results discussed in the previous chapters suggest that the time series analyzed in this book are conditionally stationary processes with mixed spectra. Additionally, there is some indication of nonstationarity, especially in longer time series.

Keywords

Curve fitting Fitting Time series Wavelet algorithm algorithms calculus entropy linearity marine model optimization statistics

Authors and affiliations

  • A. Ramachandra Rao
    • 1
  • Khaled H. Hamed
    • 2
  • Huey-Long Chen
    • 3
  1. 1.School of Civil EngineeringPurdue UniversityWest LafayetteUSA
  2. 2.Irrigation and Hydraulics Department, Faculty of EngineeringCairo UniversityGizaEgypt
  3. 3.Department of Environmental EngineeringLan-Yang Institute of TechnologyTouchen, IlanTaiwan

Bibliographic information

  • DOI https://doi.org/10.1007/978-94-010-0117-5
  • Copyright Information Springer Science+Business Media Dordrecht 2003
  • Publisher Name Springer, Dordrecht
  • eBook Packages Springer Book Archive
  • Print ISBN 978-94-010-3979-6
  • Online ISBN 978-94-010-0117-5
  • Series Print ISSN 0921-092X
  • About this book