Titlebook: Chaos in Hydrology; Bridging Determinism Bellie Sivakumar Book 2017 Springer Science+Business Media Dordrecht 2017 Chaos.Complexity.Hydrolo

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Reflection and Self-assessment in Practice,resence 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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Reflection and Self-assessment in Practice, development of catchment classification framework, extensions of chaos studies using multiple hydrologic variables, reconstruction of hydrologic system equations, and downscaling of global climate models. Finally, the need and the potential to establish reliable links between chaos theory, hydrolog

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Characteristics of Hydrologic Systems of these characteristics in hydrologic system dynamics and the methods for their identification. At the end, a particularly interesting property of hydrologic systems, wherein simple nonlinear deterministic systems with sensitive dependence on initial conditions can give rise to complex and ‘random

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Stochastic Time Series Methodsl structure, and it is essentially determined from the data themselves. This chapter presents an overview of stochastic time series methods in hydrology. First, a brief account of the history of development of stochastic methods is presented. Next, the concept of time series and relevant statistical

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Issues in Chaos Identification and Predictions four important issues in the applications of chaos methods to real time series, especially those that have particular relevance and gained considerable interest in hydrology: selection of delay time in phase space reconstruction, minimum data size required for correlation dimension estimation, inf

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