2001
DOI: 10.1080/02626660109492805
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Evidence of chaos in the rainfall-runoff process

Abstract: The transformation of rainfall into runoff is one of the most important processes in hydrology. In the past few decades, a wide variety of automated or computer-based approaches have been applied to model this process. However, many such approaches have an important limitation in that they treat the rainfall-runoff process as a realization of only a few parameters of linear relationships rather than the process as a whole. What is required, therefore, is an approach that can capture not only the overall appear… Show more

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Cited by 90 publications
(46 citation statements)
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“…This follows naturally from the existence of deterministic chaos-a highly non-linear sensitivity to initial conditionsin the weather, as it is impossible to know the exact state of the atmosphere at any given time (Lorenz, 1963). The possible existence of chaos in hydrological processes has been investigated with inconclusive results (Sivakumar, 2000;Sivakumar et al, 2001;Khan et al, 2005). Nevertheless, errors in initial conditions are recognized as an important source of uncertainty in hydrological modelling as well (Liu and Gupta, 2007).…”
Section: Framework For the Anticipation Of Forecast Uncertaintymentioning
confidence: 99%
“…This follows naturally from the existence of deterministic chaos-a highly non-linear sensitivity to initial conditionsin the weather, as it is impossible to know the exact state of the atmosphere at any given time (Lorenz, 1963). The possible existence of chaos in hydrological processes has been investigated with inconclusive results (Sivakumar, 2000;Sivakumar et al, 2001;Khan et al, 2005). Nevertheless, errors in initial conditions are recognized as an important source of uncertainty in hydrological modelling as well (Liu and Gupta, 2007).…”
Section: Framework For the Anticipation Of Forecast Uncertaintymentioning
confidence: 99%
“…Wiener (1938) has shown that if deterministic dynamical model is highly nonlinear (with a tendency to exhibit chaotic behavior), then it is possible to approximate both inputs and outputs (treated here as random processes) of the uncertain model through series expansion of standard random variables using Hermite Polynomials. Although the presence of chaotic behavior in the hydrologic system under study is not addressed herein, recent literature supports the wisdom of choosing the "Theory of Homogeneous Chaos" as a basis for formulation of the interpolator (Sivakumar, 2000;Sivakumar et al, 2001a, b;Rodriguez-Iturbe et al, 1991). Rodriguez-Iturbe et al (1991) has demonstrated chaotic behavior of soil moisture dynamics at seasonal time scales.…”
Section: Algorithm Of the Inperpolatormentioning
confidence: 99%
“…We do not demonstrate the presence or absence of chaotic behavior of simulations in this study. However, we are encouraged by the recent well-documented discovery of chaos in hydrologic systems (Sivakumar et al, 2001a and2001b;Sivakumar, 2000;Jayawardena and Lai, 1994;Rodriguez-Iturbe et al, 1991). Essential concepts of the interpolator are inferred from an uncertainty estimation tool originally developed by Isukapalli et al (2000).…”
Section: Introductionmentioning
confidence: 99%
“…However, a large number of studies employing the science of chaos to model and predict various hydrological phenomena have emerged only in the past decade (Elshorbagy et al, 2002;Islam and Sivakumar, 2002;Jayawardena and Lai, 1994;Ridolfi, 1996, 1997;Puente and Obregon, 1996;Rodriguez-Iturbe et al, 1989, Liu et al, 1998Sangoyomi et al, 1996;Sivakumar et al, 1999;Sivakumar, 2001;Sivakumar et al, 2001;Shang et al, 2009;Wang and Gan, 1998). Most of these studies dealt with scalar time series data of various hydrological phenomena like rainfall, runoff, sediment transport, lake volume etc.…”
Section: Introductionmentioning
confidence: 99%