Generation Of Synthetic Time Series Research Articles

Choice of reliability, resilience and vulnerability estimators for risk assessments of water resources systems / Choix d’estimateurs de fiabilité, de résilience et de vulnérabilité pour les analyses de risque de systèmes de ressources en eau

Definitions and estimators of water resources system reliability (the probability that the system will remain in a non-failure state), resilience (the ability of the system to return to non-failure state after a failure has occurred) and vulnerability (the likely damage of a failure event) have been thoroughly investigated. A behaviour analysis addressing monotonic behaviour, overlap and correlation between the estimators was carried out by routing time series of monthly runoff through a reservoir with a specified storage volume that is operated according to a fixed operation policy. Estimation based on historical time series is shown to be problematic and a procedure encompassing generation of synthetic time series with a length of at least 1000 years is recommended in order to stabilize the estimates. Moreover, the strong correlation between resilience and vulnerability may suggest that resilience should not be explicitly accounted for.

Analysis of monthly time series of solar radiation and sunshine hours in tropical climates

This paper analyses the interannual variability of solar radiation and sunshine hours for a large tropical region (Brazil), located between latitude 0°S and 30°S, in order to improve knowledge on solar resources, generate statistical parameters for model checking or to be used as input data of synthetic time series generation. The statistics for the daily, monthly average solar radiation deviations, and daily, monthly average sunshine hours, for the various localities in Brazil, tested with the Kolmogorov–Smirnov method, show that they are random variables, normally distributed. On the other hand, the sequential properties analysis shows that the auto-correlation coefficients with lag 1 are statistically significant only for a few locals: Fortaleza, São Luís, Manaus and Belém. But it is necessary to emphasize that the auto-correlation coefficients with lag 1, though not usually statistically significant, are positive for almost all the locals. The AR-1 is the suggested procedure for monthly solar radiation synthetic time series generation, with auto-correlation coefficients varying from 0.30 to 0.47 for the localities in the north of Brazil and zero for other regions.

Digital generation of surface-pressure fluctuations with spiky features

Abstract The paper presents a new method for generating artificial surface-pressure time series focused on the simulation of non-Gaussian spiky fluctuation features. The method is based on the Fourier representation of time series with special selection of random Fourier phases. The unique properties of the Fourier phases are utilized for generation and control of the large-amplitude spikes which are the essential feature of surface-pressure signals typically observed around the corners and edges of a building. The synthetic time-series generation, focused on extreme-value distribution properties, are presented for a given target surface-pressure signal with skewed spiky features and non-Gaussian probability distribution.

A discrete linear cascade model for hydrology

The discrete analogies of the classical Muskingum and the equal-reservoir cascade models are compared with the ARMA-type models used in the generation of synthetic time series. Applying the cascade concept to the ARMA-type difference equation and including a pure translation parameter, a family of discrete linear parametric models is developed. Expressions are derived for the direct estimation of model parameters by cumulants for the general input-output case and for the special case of a white-noise input. The family of models can be applied in unit-hydrograph analysis, in flood routing, and in the generation of synthetic time series.