Description

Book Synopsis
The discipline of Stochastic Processes is usually treated as a branch of mathematics, and there are plenty of books for mathematicians on the subject. Equally, there are very many books, both for statisticians and environmental scientists, on Time Series Analysis, analysing the structure of data sequences where measurements are made at equal time-intervals and are free from intermittent behaviour. But this book deals with the analysis of events which occur intermittently in time and space; through a very wide range of examples drawn from many areas of environmental science in which the role of water is central, the book shows how the same analytical procedures can be applied to very many different problems. The book s many examples include: analysis of time intervals between el Ni?o events, frequency of dry spells, the relation between heavy rainfall and flooding, occurrences of gravel disturbance in upland trout streams which damages trout spawn deposits and the cellular structure of

Table of Contents
Models: Deterministic, Time Series and Stochastic.

Mathematical Preliminaries.

Markov Chains: Applications to Modelling of Daily Rainfall.

More on Markov Chains: Storage.

Stochastic Reservoir Theory Applied to Rainfall-RunoffModelling.

The Poisson and Related Processes.

Random Walks and Diffusion Processes.

Some Computational Methods.

References.

Index.

Stochastic Processes for Water Scientists

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A Hardback by Robin T. Clarke

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    View other formats and editions of Stochastic Processes for Water Scientists by Robin T. Clarke

    Publisher: John Wiley & Sons Inc
    Publication Date: 29/01/1998
    ISBN13: 9780471973485, 978-0471973485
    ISBN10: 0471973483

    Description

    Book Synopsis
    The discipline of Stochastic Processes is usually treated as a branch of mathematics, and there are plenty of books for mathematicians on the subject. Equally, there are very many books, both for statisticians and environmental scientists, on Time Series Analysis, analysing the structure of data sequences where measurements are made at equal time-intervals and are free from intermittent behaviour. But this book deals with the analysis of events which occur intermittently in time and space; through a very wide range of examples drawn from many areas of environmental science in which the role of water is central, the book shows how the same analytical procedures can be applied to very many different problems. The book s many examples include: analysis of time intervals between el Ni?o events, frequency of dry spells, the relation between heavy rainfall and flooding, occurrences of gravel disturbance in upland trout streams which damages trout spawn deposits and the cellular structure of

    Table of Contents
    Models: Deterministic, Time Series and Stochastic.

    Mathematical Preliminaries.

    Markov Chains: Applications to Modelling of Daily Rainfall.

    More on Markov Chains: Storage.

    Stochastic Reservoir Theory Applied to Rainfall-RunoffModelling.

    The Poisson and Related Processes.

    Random Walks and Diffusion Processes.

    Some Computational Methods.

    References.

    Index.

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