D. Koutsoyiannis, Stochastic simulation of hydrosystems, Water Encyclopedia, Vol. 4, Surface and Agricultural Water, edited by J. H. Lehr and J. Keeley, 421–430, doi:10.1002/047147844X.sw913, Wiley, New York, 2005.
Due to their complexity, hydrosystems, including water resource systems, flood management systems, and hydropower systems are frequently studied using stochastic simulation. A generalized solution procedure for hydrosystems problems, including systems identification, modeling and forecasting, hydrologic design, water resources management, and flood management, is discussed. Emphasis is given on the stochastic representation of hydrologic processes, which have a dominant role in hydrosystems. Peculiarities of hydrologic and other geophysical processes (seasonality, long-term persistence, intermittency, skewness, spatial variability) gave rise to substantial research that resulted in numerous stochastic tools appropriate for applications in hydrosystems. Four examples of such tools are discussed: (1) the multivariate periodic autoregressive model of order 1 [PAR(1)], which reproduces seasonality and skewness but not long-term persistence;(2) a generalized multivariate stationary model that reproduces all kinds of persistence and simultaneously skewness but not seasonality; (3) a combination of the previous two cases in a multivariate disaggregation framework that can respect almost all peculiarities except intermittency; and (4) the Bartlett-Lewis process that is appropriate for modeling rainfall and emphasizes its intermittent character on a fine time scale.
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Our works that reference this work:
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