Titlebook: Stochastic Hydrology and its Use in Water Resources Systems Simulation and Optimization; J. B. Marco,R. Harboe,J. D. Salas Book 1993 Sprin

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Stochastic Models of Temporal Rainfall: Reproducibility, Estimation and Prediction of Extreme Eventsation are also presented in the light of applications to real-world hydrology. Finally, an extensive field data analysis is presented, in order to assess the capability of the mathematical models investigated to represent the actual behaviour of the natural process.

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A Nonlinear, Nonstationary Stochastic Model for the Prediction of Storage in the Edwards Aquifer, Te 15% to almost 90% of the annual recharge, there is growing concern about the possibility of important reductions in storage or about the capacity of the aquifer to stand dry periods at ever increasing levels of pumping.

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Book 1993lts. These results have to be incorporated ina decision-making process regarding the planning and management ofwater systems. It is through this application that stochastichydrology finds its true meaning, otherwise it becomes merely anacademic exercise..A set of well known specialists from both sto

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Aggregation and Disaggregation Modellingestimates. Disaggregation is stochastic generation that starts with a previously generated aggregate series and subdivides or disaggregates that series into a finer scale time series. Disaggregation modelling has proven to be a very practical approach, especially for multisite and multivariate analysis.

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Models for Data Generation in Hydrology: Univariate Techniquesl properties generally present in most seasonal series and the procedures for dealing with trends, periodicity, non-normality and correlation structure. Modelling approaches are viewed under the categories of direct modelling, disaggregation and aggregation approaches. In addition, models of intermi