A stochastic methodology for generation of seasonal time series reproducing overyear scaling behaviour

A. Langousis, and D. Koutsoyiannis, A stochastic methodology for generation of seasonal time series reproducing overyear scaling behaviour, Journal of Hydrology, 322, 138–154, 2006.



In generating synthetic time series of hydrological processes at sub-annual scales it is important to preserve seasonal characteristics and short-term persistence. At the same time, it is equally important to preserve annual characteristics and overyear scaling behaviour. This scaling behaviour, which is equivalent to the Hurst phenomenon, has been detected in a large number of hydroclimatic series and affects seriously planning and design of hydrosystems. However, when seasonal models are used the preservation of annual characteristics and overyear scaling is a difficult task and is often ignored unless disaggregation techniques are applied, which, however, involve several difficulties (e.g. in parameter estimation) and inaccuracies. As an alternative, a new methodology is proposed that directly operates on seasonal time scale, avoiding disaggregation, and simultaneously preserves annual statistics and the scaling properties on overyear time scales. Two specific stochastic models are proposed, a simple widely used seasonal model with short memory to which long-term persistence is imposed using a linear filter, and a combination of two sub-models, a stationary one with long memory and a cyclostationary one with short memory. Both models are tested in a real world case and found to be accurate in reproducing all the desired statistical properties and virtually equivalent from an operational point of view.

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See also: http://dx.doi.org/10.1016/j.jhydrol.2005.02.037

Our works referenced by this work:

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Our works that reference this work:

1. D. Koutsoyiannis, H. Yao, and A. Georgakakos, Medium-range flow prediction for the Nile: a comparison of stochastic and deterministic methods, Hydrological Sciences Journal, 53 (1), 142–164, doi:10.1623/hysj.53.1.142, 2008.
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6. D. Koutsoyiannis, Generic and parsimonious stochastic modelling for hydrology and beyond, Hydrological Sciences Journal, 61 (2), 225–244, doi:10.1080/02626667.2015.1016950, 2016.
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8. I. Tsoukalas, A. Efstratiadis, and C. Makropoulos, Building a puzzle to solve a riddle: A multi-scale disaggregation approach for multivariate stochastic processes with any marginal distribution and correlation structure, Journal of Hydrology, 575, 354–380, doi:10.1016/j.jhydrol.2019.05.017, 2019.

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Tagged under: Hurst-Kolmogorov dynamics, Scaling, Stochastics, Students' works