This book 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, MATLAB-based codes and solutions of some worked out examples are also provided to assist the readers to handle real life data. This book presents a comprehensive knowledge of statistical techniques combining the basics of probability and the current advances in stochastic hydrology. Besides serving as a textbook for graduate courses on stochastic modeling in hydrology and related disciplines, the book offers valuable resources for researchers and professionals involved in the field of hydrology and climatology.

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 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 book presents a systematic approach to understanding and applying the principles of hydrology and hydroclimatology, examining the interactions among different components of the water cycle. It takes a fresh look at the fundamentals and challenges in hydrologic and hydroclimatic systems as well as climate change. The author describes the application of nontraditional data sets and new investigation techniques to water-related problems. He also examines long lead forecasting and simulation, time series analysis, and risk and uncertainty in hydrologic design.

Global climate change is typically understood and modeled using global climate models (GCMs), but the outputs of these models in terms of hydrological variables are only available on coarse or large spatial and time scales, while finer spatial and temporal resolutions are needed to reliably assess the hydro-environmental impacts of climate change. To reliably obtain the required resolutions of hydrological variables, statistical downscaling is typically employed. Statistical Downscaling for Hydrological and Environmental Applications presents statistical downscaling techniques in a practical manner so that both students and practitioners can readily utilize them. Numerous methods are presented, and all are illustrated with practical examples. The book is written so that no prior background in statistics is needed, and it will be useful to graduate students, college faculty, and researchers in hydrology, hydroclimatology, agricultural and environmental sciences, and watershed management. It will also be of interest to environmental policymakers at the local, state, and national levels, as well as readers interested in climate change and its related hydrologic impacts. Features: Examines how to model hydrological events such as extreme rainfall, floods, and droughts at the local, watershed level. Explains how to properly correct for significant biases with the observational data normally found in current Global Climate Models (GCMs). Presents temporal downscaling from daily to hourly with a nonparametric approach. Discusses the myriad effects of climate change on hydrological processes.

A graduate textbook on the interdisciplinary significance of hydroclimatology, explaining the relationship between the climate system and the hydrologic cycle.

Statistical methods are now widely used in different fields such as Business and Management, Economics, Biological, Physical sciences and including the new fields such as Data Science and Machine Learning. The data which form the basis for the statistical methods helps us to take scientific and informed decisions. Statistical methods deal with the collection, compilation, analysis and making inference from the data. This book deals with the statistical methods which are useful in Business and Management decision making. The methods include Probability, Sampling, Correlation, Regression and Hypothesis Testing, Time Series, Forecasting and Non-Parametric tests and advanced statistical models. The book uses open source R statistical software to carry out different statistical analysis with sample datasets. This book is third in series of Statistics books by the Author. Some of the contents are adopted from the author’s previous statistical book introduction to statistical methods and non-parametric methods.

Accurate prediction of hydrological variables is essential for efficient water resources planning and management. Proper understanding of the characteristics of the time series may help in improving the simulation and forecasting accuracy of hydrological variables. This book presents a detailed description and application of multiscale time-frequency characterization tool for the spectral analysis of hydrological time series. It presents spectral analysis methods for hydrological applications through a wide variety of illustrative case studies including Wavelet transforms, Hilbert Huang Transform and their extensions.