UWMH develops user friendly knowledge-intensive digital products and tools to ensure that new knowledge creates real-world impact. We also look at the business case and market opportunities to turn research prototypes into practical, large scale implementations.


is an R package that implements methodological framework for the multi-scale and multivariate stochastic simulation of stochastic processes, building upon the works of Koutsoyiannis (2000) and Efstratiadis et al. (2014).


Briefly, the overall scheme reproduces the statistical characteristics (mean, variance, skewness and correlations) of the historical data at three temporal scales (annual, monthly and daily).

The generation procedure lies upon a symmetric moving average process for the annual scale and a periodic autoregressive process for the finer scales, while a Monte Carlo disaggregation approach re-establishes consistency across the three temporal scales.


Available upon request

  • Tsoukalas I., P. Kossieris, A. Efstratiadis, C. Makropoulos, and D. Koutsoyiannis (2018) CastaliaR: An R package for multivariate stochastic simulation at multiple temporal scales, European Geosciences Union General Assembly 2018, Geophysical Research Abstracts, Vol. 20, Vienna, EGU2018-18433, doi:10.13140/RG.2.2.20978.81605, European Geosciences Union, 2018.
  • Efstratiadis A., Y. Dialynas, S. Kozanis, and D. Koutsoyiannis (2014) A multivariate stochastic model for the generation of synthetic time series at multiple time scales reproducing long-term persistence, Environmental Modelling and Software, 62, 139–152, doi:10.1016/j.envsoft.2014.08.017.
  • Koutsoyiannis D. (2000) A generalized mathematical framework for stochastic simulation and forecast of hydrologic time series, Water Resources Research, 36 (6), 1519–1533, doi:10.1029/2000WR900044.

+ 30 210 7722828-2886

NTUA Campus, Heroon Polytechneiou str. 9, 15780, Zographou, Athens Greece, Hydraulics Building