Efficient nonlinear modeling of rainfall-runoff process using wavelet compression

Chou, Chien-Ming

doi:10.1016/j.jhydrol.2006.07.015

Cited by 32 publications

(16 citation statements)

References 16 publications

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“…Wavelet transformation has been shown to be a powerful technique for characterization of the frequency, intensity, time position, and duration of variations in climate and hydrological time series (Smith et al 1998;Labat et al 2004;Chou 2007;Xu et al 2008a, b;Partal 2009). Wavelet analysis can also reveal the localized time and frequency information without requiring the time series to be stationary, as required by the Fourier transform and other spectral methods (Torrence and Compo 1998).…”

Section: Wavelet Analysismentioning

confidence: 99%

An integrated statistical approach to identify the nonlinear trend of runoff in the Hotan River and its relation with climatic factors

Chen

et al. 2010

Stoch Environ Res Risk Assess

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A number of studies have indicated a transition from warm-dry to warm-wet climate in Northwest China after the 1980s. This transition was characterized by an increase in temperature and precipitation, added river runoff volume, increased lake water surface elevation and area, and elevated groundwater table. However, some literatures showed that the Hotan River has presented a contrary situation, i.e. the runoff decreased, whereas temperature and precipitation increased. In order to discover the nonlinear runoff trend and its causes in the Hotan River, based on the related data from hydrological stations, ground and air sounding meteorological stations, this study applied a comprehensive method combing correlation analysis, wavelet analysis and regression analysis to investigate the runoff change in the Hotan River with its relevant climatic factors over the past decades. The main findings are: (a) the hydrological process of the Hotan River is a nonlinear system, with a periodicity of 24 year cycle, and it shows different nonlinear trends at different time scales; (b) the data from the ground meteorological stations in the Hotan area shows a false appearance that there is almost no correlation between runoff and temperature, and a little negative correlation between runoff and precipitation; (c) but the data from air sounding meteorological stations shows the truth that there is a close relation between the runoff in the Hotan River and the 0°C level height in summer on the north slope of Kunlun Mountains. The two variables present a same periodicity, i.e. 24-year cycle, having similar nonlinear trends and significant correlations at different time scales.

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Section: Wavelet Analysismentioning

confidence: 99%

An integrated statistical approach to identify the nonlinear trend of runoff in the Hotan River and its relation with climatic factors

Chen

et al. 2010

Stoch Environ Res Risk Assess

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“…As a result, the nonlinearity of runoff processes has been explored using various nonlinear analytical methods and models, including wavelets, artificial neural networks, and the fractal theory (Wilcox et al, 1991;Smith et al, 1998;Chou, 2007;Hu et al, 2008;Movahed and Hermanis, 2008). However, it has proven difficult to achieve a thorough understanding of the nonlinear mechanism of any individual runoff process.…”

Section: Introductionmentioning

confidence: 99%

A comprehensive approach to characterization of the nonlinearity of runoff in the headwaters of the Tarim River, western China

Xu¹,

Li²,

Ji³

et al. 2009

Hydrological Processes

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Abstract:Nonlinear characteristics of the runoff processes in the headwaters of the Tarim River were identified and evaluated using several selected methods, including wavelet analysis, correlation dimension, and R/S analysis. Time-series of annual data describing runoff, average temperature, and precipitation from 1957 to 2005 were used to construct and test empirical models. The primary findings of this study were as follows: (1) The annual runoff of the headwaters are complex and nonlinear in nature, and they each presented periodic, nonlinear trends at the chosen time scales, chaotic dynamics, and long-memory characteristics. (2) These nonlinear trends appeared to have resulted from the regional climatic changes that occurred during the study period. The periodicity of changes in runoff occurred on an approximately 25-year cycle, which appeared to be correlated with temperature and precipitation cycles. In addition, the annual runoff exhibited a significant, positive correlation with the temperature and precipitation factors at the 4-, 8-, 16-, and 32-year temporal scales. (3) The correlation dimensions of the attractor derived from the runoff time series for the Hotan, Yarkand, and Aksu rivers were all greater than 3Ð0 and non-integral, implying that all three rivers are dynamic chaotic systems that are sensitive to initial conditions, and that the dynamic modelling of their annual runoff requires at least four independent variables. (4) The computed Hurst exponents indicate that a long-term memory characteristic exists in the annual runoff processes. However, there were some differences observed, with the Aksu and Yarkand rivers demonstrating a persistent trait, and the Hotan River exhibiting an anti-persistent feature.

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“…Finally, results are described and 138 discussed, and conclusions are drawn. (Chou, 2007). The discrete form of the Volterra model is written as:…”

Section: Abstract 23mentioning

confidence: 99%

“…Since the rainfall and runoff data often includes some errors 568 such as measuring errors, the OLS method is not a very efficient method for solving the R-R 569 models. Moreover, when the model has many parameters to be estimated the OLS method will 570 lose its ability for estimating the parameters precisely (Chou, 2007;Kashani, 2014). Moreover, 571 the identification of kernels of the Volterra filters is a typical example of an ill-posed problem.…”

mentioning

confidence: 99%

Integration of Volterra model with artificial neural networks for rainfall-runoff simulation in forested catchment of northern Iran

Kashani

Ghorbani

Dinpashoh

et al. 2016

Journal of Hydrology

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Efficient nonlinear modeling of rainfall-runoff process using wavelet compression

Cited by 32 publications

References 16 publications

An integrated statistical approach to identify the nonlinear trend of runoff in the Hotan River and its relation with climatic factors

An integrated statistical approach to identify the nonlinear trend of runoff in the Hotan River and its relation with climatic factors

A comprehensive approach to characterization of the nonlinearity of runoff in the headwaters of the Tarim River, western China

Integration of Volterra model with artificial neural networks for rainfall-runoff simulation in forested catchment of northern Iran

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