This book contains a selection of papers from a NATO Advanced Research Workshop entitled "Stochastic models of hydrological processes and their applications to problems of environmental preservation" convened in Moscow over the period 23-27 November 1998. The Workshop was unique in providing the first opportunity for over a decade for countries of the Russian Federation to interact with other countries across the world to discuss hydrological science issues relevant to environmental management. The contrasting schools of thought within the Russian Federation and with other countries proved a fascinating and valuable experience for those fortunate enough to attend. The scientific content of the Workshop was motivated by a number of concerns. Water is a key natural resource whose modelling and management is made complex by its inherent spatial unevenness and time variability. Traditional methods for investigating hydrological processes in nature employ stochastic modelling and forecasting. However these are not well developed with regard to (i) representing the characteristics of hydrological regimes, and (ii) investigating the influence of water factors on processes which arise in biological systems and those involving hydrochemical, geophysical and other processes.

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Preface. Acknowledgements. 1: Hydrometeorological extremes. Bayesian analysis of a simultaneous change in both the mean and the variance; L. Perreault, E. Parent, B. Bobee. On the distribution of the maximum of a random sample; V.F. Pisarenko. Stochastic model of the runoff fluctuations for rivers with a flood flow regime; A.V. Khristoforov, G.V. Kruglova, T.V. Samborski. 2: Stochastic models of long-term and seasonal variation in water balance. A study of the synchronicity of annual runoff fluctuations; V.M. Evstigneev, T.A. Akimenko. Stochastic models with periodic-correlation of seasonal river runoff variations; M.V. Bolgov. Identification of regional stochastic models from short time-series; M.I. Fortus, M.V. Bolgov. A method for simulation of periodic hydrological time series using wavelet transform; G. Feng. The Caspian Sea as a stochastic reservoir; A.V. Frolov. Geophysical time series and climatic change: A sceptic's view; V. Klemes. On the development of the stochastic approach in hydrology; D.Ya. Ratkovich. Stochastic models of the long-term river runoff fluctuations with application water in construction and management; A.V. Rozhdestvensky. 3: River and sediment dynamics. Statistical model of river-bed stream: parameters of turbulence, energy characteristics; V.K. Debolksy, E.N. Dolgopolova. 4: Water resource system management. Management of water resources systems under non-stationary conditions; I.L. Khranovich, A.L. Velikanov. Interactive river-aquifer simulation and stochastic analyses for predicting and evaluating the ecologic impacts of alternative land and water management policies; D.P. Loucks. A decision-making support system for selecting water protection and reservoir control measures; V.G.Priazhinskaya, L.K. Levit-Gourevich, D.M. Yaroshevskii. Control of regimes of water resource systems with stochastic indeterminacy of the hydrometeorological data; A.M. Reznikovsky, M.I. Rubinshtein. 5: Risk assessment. Risk mapping of groundwater contamination; W.K. Wong, I. Krasovskaia, L. Gottschalk, A. Bárdossy. Economic risk of flooding: a case study for the Glomma River, Norway; L. Gottschalk, I. Krasovskaia, N.R. Sælthun.