Stochastic and Statistical Methods in Hydrology and Environmental Engineering

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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pWorld 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. /ppbAudiencebr/bThe book 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. /pp

Contenu
I: General Issues.- Unny Symposium: Why are we Here?.- Stochastic Differential Equations in Environmental Modelling and Their Numerical Solution.- The Meaning of Stochasticity, Randomness and Uncertainty in Environmental Modeling.- II: Groundwater.- Indentification of Stochastic Dispersion Models.- Solving and Calibrating Groundwater Flow Systems with the Penalty Method.- Calibration of Groundwater Models by Optimization of Parameters in Homogeneous Geological Zones.- Stochastic Characterization of Aquifer Heterogeneity from Drill Log Data.- Groundwater Contaminant Transport: Estimating The Pollution at a Well.- Transport by Two-Dimensional Random Velocity Fields: Effective Dispersion Coefficients of a Finite Plume.- Spatial Correlation Analysis of Two-Dimensional Solute Transport in the Unsaturated Zone.- Geostatistical Consideration on the Water Retention Volume and Pore Volume in Unsaturated Granular Material Composed of Various Particles.- Derivation of a Distribution for the Piezometric Head in G round water Flow Using Entropy.- L1 and L2 Estimators in Ground water Problems: Parameter Estimates and Covariances.- A Version of Dynamic-Stochastic Modelling of Hydrological Processes.- III: Surface Water.- Computational Methods in Stochastic River Waters Quality Modeling.- A Random Flight Model in General Coordinates.- Application of a Distributed Parameter Filter to Predict Simulated Tidal Induced Shallow Water Flow.- Stochastic Behaviour of Storage in Conceptual Reservoirs.- Stochastic Response of Storage Function Model for Flood Runoff.- Stochastic Model of Finite Storage Processes: Input with Finite Support.- IV: Stochastic Optimization.- A Regularized Algorithm for Solving Two-Stage Stochastic Linear Programming Problems: A Water Resources Example.- Stochastic Characterization of Optimal Response of a Hydroelectric System Via Dynamic Programming.- V: Moment Analysis.- Estimating Mean and Covariance of the Solution of a Linear System with Random Coefficients.- Second Moment Analysis of Dynamic Systems with Probabilistic Components in the Frequency Domain.- VI: Other Topics.- Uncertainty Analysis in Global Carbon Dioxide Modeling.- A Real-Time Estimation of the Accuracy of Short-Term Rainfall Prediction Using Radar.- Fourier Approximations for Estimation and Smoothing of Irregularly Observed Spatial Processes.- Author Index.