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.
Inhaltsverzeichnis
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.
