Stochastic and Statistical Methods in Hydrology and Environmental Engineering: Time Series Analysis in Hydrology and Environmental Engineering(10/3 Water Science and Technology Library)

Volume 1: (edited by Keith W. Hipel) In this landmark collection of papers, highly respected scientists and engineers from around the world present the latest research results in extreme value analyses for floods and droughts. Two approaches that are commonly employed in flood frequency analyses are the maximum annual flood and partial duration series or peak over threshold procedures. Recent theoretical advances as well as illustrative applications are described in detail for each of these approaches. Additionally, droughts and storms are systematically studied using appropriate probabilistic models. A major part of the volume is devoted to frequency analyses and fitting extreme value distributions to hydrological data. Other thought-provoking topics include regionalization techniques, distributed models, entropy and fractal analysis. Volume 1 is of interest to researchers, teachers, students and practitioners who wish to place themselves at the leading edge of flood frequency and drought analyses. Volume 2: (edited by Keith W. Hipel) World renowned scientists present valuable contributions to stochastic and statistical modelling of groundwater and surface water systems. The philosophy of probabilistic modelling in the hydrological sciences is put into proper perspective and the importance of stochastic differential equations in the environmental sciences is explained and illustrated. The new research ideas put forward in groundwater modelling will assist decision makers in tackling challenging problems such as controlling pollution of underground aquifers and obtaining adequate water supplies. Additionally, different types of stochastic models are used in modelling a range of interesting surface water problems. Other topics covered in this landmark volume include stochastic optimization, moment analysis, carbon dioxide modelling and rainfall prediction. Volume 2 is of interest to researchers, teachers, students and practitioners who wish to be at the leading edge of stochastic and statistical modelling in the environmental sciences. Volume 3: (edited by Keith W. Hipel; A. Ian McLeod; U.S. Panu; Vijay P. Singh) 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. Volume 3 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. Volume 4: (edited by Keith W. Hipel; Liping Fang) In this landmark set of papers, experts from around the world present the latest and most promising approaches to both the theory and practice of effective environmental management. To achieve sustainable development, organizations and individual citizens must comply with environmental laws and regulations. Accordingly, a major contribution of this book is the presentation of original techniques for designing effective environmental policies, regulations, inspection procedures and monitoring systems. Interesting methods for modelling risk and decision making problems are discussed from an environmental management perspective. Moreover, knowledge-based techniques for handling environmental problems are also investigated. Finally, the last main part of the book describes optimal approaches to reservoir operation and control that take into account appropriate multiple objectives. Volume 4 is of direct interest to researchers, teachers, students and practitioners concerned with the latest developments in environmental management and sustainable development.

Table of Contents:
I: Climatic Change.- Applications of Stochastic Modeling in Climate Change Impact Assessment.- Knowledge Based Classification of Circulation Patterns for Stochastic Precipitation Modeling.- Grey Theory Approach to Quantifying the Risks Associated with General Circulation Models.- A Nonparametric Renewal Model for Modeling Daily Precipitation.- II: Forecasting.- Forecasting B.C. Hydro’s Operation of Williston Lake — How Much Uncertainty is Enough.- Evaluation of Streamflow Forecasting Models.- Application of a Transfer Function Model to a Storage-Runoff Process.- Seeking User Input in Inflow Forecasting.- Linear Procedures for Time Series Analysis in Hydrology.- III: Entropy.- Application of Probability and Entropy Concepts in Hydraulics.- Assessment of the Entropy Principle as Applied to Water Quality Monitoring Network Design.- Comparisons betweeen Bayesian and Entropic Methods for Statistical Inference.- An Entropy-Based Approach to Station Discontinuance.- Assessment of Treatment Plant Efficiencies by the Entropy Principle.- Infilling Missing Monthly Streamflow Data Using a Multivariate Approach.- IV: Neural Networks.- Application of Neural Networks to Runoff Prediction.- Prediction of Daily Water Demands by Neural Networks.- Backpropagation in Hydrological Time Series Forecasting.- V: Trend Assessment.- Tests for Monotonic Trend.- Analysis of Water Quality Time Series Obtained for Mass Discharge Estimation.- De-Acidification Trends in Clearwater Lake near Sudbury, Ontario 1973–1992.- VI: Spatial Analysis.- Multivariate Kernel Estimation of Functions of Space and Time Hydrologic Data.- Comparing Spatial Estimation Techniques for Precipitation Analysis.- VII: Spectral Analysis.- Exploratory Spectral Analysis of Time Series.- On the Simulation of Rainfall Basedon the Characteristics of Fourier Spectrum of Rainfall.- VIII: Topics in Streamflow Modelling.- Cluster Based Pattern Recognition and Analysis of Streamflows.- RéMus, Software for Missing Data Recovery.- Seasonality of Flows and its Effect on Reservoir Size.- Estimation of the Hurst Exponent h and Geos Diagrams for a Non-Stationary Stochastic Process.- Optimal Parameter Estimation of Conceptually-Based Streamflow Models by Time Series Aggregation.- On Identification of Cascade Systems by Nonparametric Techniques with Applications to Pollution Spread Modeling in River Systems.- Patching Monthly Streamflow Data — A Case Study Using the EM Algorithm and Kalman Filtering.- Runoff Analysis by the Quasi Channel Network Model in the Toyohira River Basin.- Author Index.