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Stochastic and Statistical Methods in Hydrology and Environmental Engineering

Volume 2: Stochastic and Statistical Modelling with Groundwater and Surface Water Applications

197,94 € Lieferbar in 5-7 Tagen


Vol.4: Effective Environmental Management for Sustainable Development


Titel: Stochastic and Statistical Methods in Hydrology and Environmental Engineering
Autoren/Herausgeber: Keith W. Hipel (Hrsg.)
Aus der Reihe: Water Science and Technology Library
Ausgabe: 2nd ed. 1994. Softcover reprint of the original 2nd ed. 1994

ISBN/EAN: 9789401044677

Seitenzahl: 372
Format: 24 x 16 cm
Produktform: Taschenbuch/Softcover
Gewicht: 630 g
Sprache: Englisch

Objectives The current global environmental crisis has reinforced the need for developing flexible mathematical models to obtain a better understanding of environmental problems so that effective remedial action can be taken. Because natural phenomena occurring in hydrology and environmental engineering usually behave in random and probabilistic fashions, stochastic and statistical models have major roles to play in the protection and restoration of our natural environment. Consequently, the main objective of this edited volume is to present some of the most up-to-date and promising approaches to stochastic and statistical modelling, especially with respect to groundwater and surface water applications. Contents As shown in the Table of Contents, the book is subdivided into the following main parts: GENERAL ISSUES PART I PART II GROUNDWATER PART III SURFACE WATER PART IV STOCHASTIC OPTIMIZATION PART V MOMENT ANALYSIS PART VI OTHER TOPICS Part I raises some thought-provoking issues about probabilistic modelling of hydro logical and environmental systems. The first two papers in Part I are, in fact, keynote papers delivered at an international environmetrics conference held at the University of Waterloo in June, 1993, in honour of Professor T. E. Unny. In his keynote pa per, Dr. S. J. Burges of the University of Washington places into perspective the historical and future roles of stochastic modelling in hydrology and environmental engineering. Additionally, Dr. Burges stresses the need for developing a sound scien tific basis for the field of hydrology. Professor P. E.

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