Stochastic Processes for Water Scientists: Developments and Applications

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 Niño 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 rainfall. The book does not aim to be an exhaustive treatment of all possible applications of stochastic process models in the environmental sciences, but should be regarded as a source book. Its aim is to encourage students and research workers to see how environmental problems can be put into a probabilistic framework, and to draw their attention to analogous problems and solutions in other fields of environmental science in which water, and the transport of material by water, is an essential characteristic.

Spis treści:
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–Runoff Modelling.
The Poisson and Related Processes.
Random Walks and Diffusion Processes.
Some Computational Methods.
References.
Index.

Okładka tylna:
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 Niño 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 rainfall. The book does not aim to be an exhaustive treatment of all possible applications of stochastic process models in the environmental sciences, but should be regarded as a source book. Its aim is to encourage students and research workers to see how environmental problems can be put into a probabilistic framework, and to draw their attention to analogous problems and solutions in other fields of environmental science in which water, and the transport of material by water, is an essential characteristic.