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Chaos in Hydrology pp 321–339Cite as

Studies on Hydrologic Data Issues

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Abstract

Despite the tremendous growth in the applications of chaos theory in hydrology, there have been lingering criticisms. These criticisms have been based on the fundamental assumptions involved in the development of methods for identification and prediction of chaos (e.g. infinite and noise-free time series, lack of clear-cut guidelines on the selection of parameters involved) and/or the limitations of hydrologic data (e.g. short and noisy data, presence of zeros). A number of issues have been raised in this regard, but some have attracted far more attention than the others. This chapter presents a review of studies that have addressed such issues in chaos studies in hydrology. The review mainly focuses on four major issues: selection of an optimum delay time for phase space reconstruction, minimum data size for correlation dimension estimation, effects of data noise, and influence of the presence of zeros in data. Examples are also provided to illustrate how these issues have been addressed to gain more confidence in the applications of the methods and in the interpretation of the outcomes.

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Authors and Affiliations

  1. School of Civil and Environmental Engineering, The University of New South Wales, Sydney, NSW, Australia

    Bellie Sivakumar

  2. Department of Land, Air and Water Resources, University of California, Davis, CA, USA

    Bellie Sivakumar

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Sivakumar, B. (2017). Studies on Hydrologic Data Issues. In: Chaos in Hydrology. Springer, Dordrecht. https://doi.org/10.1007/978-90-481-2552-4_12

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