Statistical Methods In Hydrology And Hydroclimatology

This second edition focuses on the application of statistical methods in the field of hydrology and hydroclimatology. Among the latest theories being used in these fields, the book introduces the theory of copulas and its applications in this context. The purpose is to develop an understanding and illustrate the usefulness of the statistical techniques with detailed theory and numerous worked out examples. Apart from this, sample scripts based on MATLAB, Python and R for some examples are also provided to assist the readers to handle real life data. Besides serving as a textbook for graduate courses on stochastic modeling in hydrology and related disciplines, the book offers a valuable resource for researchers and professionals involved in the field of hydrology and climatology.

This classic text and reference has been totally revised, redesigned, and comprehensively updated for the new millennium and beyond—bound in a new, revamped hardcover version. Inside, the reader will find improved coverage of time series analysis by the addition of a treatment of IRIMA models, improved coverage of regression with the addition of consideration of multicollinarity and correlated errors, increased material on Bayesian statistics, and a major section on the use of statistics in hydrologic and water quality modeling; which includes sensitivity analysis, Monte Carlo simulation, First Order Analysis, uncertainty analysis, parameter estimation for models, and calibration and verification of models. A greater emphasis, in this new edition, has been on the use of computers in statistical analysis without the dependence on any one particular software vendor. The reader of this new edition will also notice improved coverage on plotting and graphical analysis and some added coverage of nonparametric terms applicable in hydrology. Exercises follow nearly every chapter for increased retention and learning.

International experts from around the globe present a rich variety of intriguing developments in time series analysis in hydrology and environmental engineering. Climatic change is of great concern to everyone and significant contributions to this challenging research topic are put forward by internationally renowned authors. A range of interesting applications in hydrological forecasting are given for case studies in reservoir operation in North America, Asia and South America. Additionally, progress in entropy research is described and entropy concepts are applied to various water resource systems problems. Neural networks are employed for forecasting runoff and water demand. Moreover, graphical, nonparametric and parametric trend analyses methods are compared and applied to water quality time series. Other topics covered in this landmark volume include spatial analyses, spectral analyses and different methods for stream-flow modelling. Audience The book constitutes an invaluable resource for researchers, teachers, students and practitioners who wish to be at the forefront of time series analysis in the environmental sciences.

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.