Post-blackening approach for modeling dependent annual streamflows

Srinivas, V. V.; Srinivasan, K.

doi:10.1016/s0022-1694(00)00168-2

Cited by 42 publications

(41 citation statements)

References 51 publications

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“…9 Metoda je založena na následujích krocích. Základní myšlenkou metody MBB je přetrhání dlouhodobých vazeb v časové řadě a ponechání krátkodobých vazeb společně s distribucí, potenciální heteroskedasticitou a trendováním (Efron, 1979;Srinivas, Srinivasan, 2000). Pokud je náš odhad pro původní řadu výrazně odlišný od odhadů založených na MBB, můžeme zamítnout hypotézu o nepřítomnosti procesu s dlouhou pamětí v původní časové řadě.…”

Section: Promíchávání S Pohyblivými Blokyunclassified

Long-Term Memory and Its Evolution in Returns of Stock Index PX Between 1997 and 2009

Krištoufek¹

2010

Politicka ekonomie

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Section: Promíchávání S Pohyblivými Blokyunclassified

Long-Term Memory and Its Evolution in Returns of Stock Index PX Between 1997 and 2009

Krištoufek¹

2010

Politicka ekonomie

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“…Chattopadhyay and Chattopadhyay [26] compared ARIMA and ARNN models using univariate modeling of summer-monsoon rainfall time series. Anctil et al [27] studied the impact of the length of observed records on the performance of ANN and of conceptual parsimonious rainfall-runoff forecasting models. The results showed that the best performance about evenly for 3-and 5-year training sets, but multiple-layer perceptrons (MLPs) performed better whenever the training set was dominated by wet weather.…”

Section: Introductionmentioning

confidence: 99%

How Much Meteorological Information Is Necessary to Achieve Reliable Accuracy for Rainfall Estimations?

Valipour

2016

Agriculture

144

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This paper reports the study of the effect of the length of the recorded data used for monthly rainfall forecasting. Monthly rainfall data for three periods of 5, 10, and 49 years were collected from Kermanshah, Mashhad, Ahvaz, and Babolsar stations and used for calibration time series models. Then, the accuracy of the forecasting models was investigated by the following year's data. The following was concluded: In temperate and semi-arid climates, 60 observation data is sufficient for the following year's rainfall forecasting. The accuracy of the time series models increased with increasing amounts of observation data of arid and humid climates. Time series models are appropriate tools for forecasting monthly rainfall forecasting in semi-arid climates. Determining the most critical rainfall month in each climate condition for agriculture schedules is a recommended aim for future studies.

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“…Because ARMA models can be fitted to normal data only, it is necessary to apply an appropriate transformation in the case of non-normal data. Srinivas & Srinivasan (2000) discuss the drawbacks of parametric models.…”

Section: Introductionmentioning

confidence: 99%

“…Difficulties are encountered in reproducing the autocorrelation structure of the original time series. Model-based resampling, moving block bootstrap, nearest neighbour bootstrap and post-blackening approaches are developed to model dependent data (Srinivas & Srinivasan, 2000). Sharma et al (1997) used kernel estimates of the joint and conditional probability density functions to generate synthetic streamfiow sequences.…”

Section: Introductionmentioning

confidence: 99%

Nonparametric streamflow simulation by wavelet or Fourier analysis

Bayazit

Önöz

Aksoy

2001

Hydrological Sciences Journal

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Wavelet or Fourier analysis is proposed as an alternative nonparametric method to simulate streamflows. An observed series is decomposed into its components at various resolutions and then recombined randomly to generate synthetic series. The mean and standard deviation are perfectly reproduced and coefficient of skewness tends to zero as the number of simulations increases. Normalizing transforms can be used for skewed series. Autocorrelation coefficients and the dependence structure are better preserved when Fourier analysis is used, but the mean and variance remain constant when the simulated and observed series have the same length. Monthly as well as annual flows can be simulated by this technique as illustrated on some examples. Wavelet analysis should be preferred as it generates flow series that exhibit a wider range of required reservoir capacities.

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Post-blackening approach for modeling dependent annual streamflows

Cited by 42 publications

References 51 publications

Long-Term Memory and Its Evolution in Returns of Stock Index PX Between 1997 and 2009

Long-Term Memory and Its Evolution in Returns of Stock Index PX Between 1997 and 2009

How Much Meteorological Information Is Necessary to Achieve Reliable Accuracy for Rainfall Estimations?

Nonparametric streamflow simulation by wavelet or Fourier analysis

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