Calibration and Reliability in Groundwater Modelling: Coping with Uncertainty

Edited by F. Stauffer, W. Kinzelbach, K. Kovar & E. Hoehn

IAHS Publication no. 265 (published September 2000) in the IAHS Series of Proceedings and Reports

ISBN 1-901502-36-8; 524 + xii pp.; price £69

The usefulness of predictive simulations obtained by groundwater models is often hampered by the inability to indicate and quantify the reliability of model results. Uncertainty in model predictions primarily stems from errors relating to model formulation such as inadequate conception and description of processes and interactions, inadequate description of spatial and temporal variability, and of the state of the system, and use of incorrect coefficient values (parameter values) and improper specification of error bounds. Significant research is resulting in a variety of approaches that can be used to incorporate information about these errors into the modelling process, and to establish the level of uncertainty in model-based decision-making, and these techniques are now being applied to a variety of problems and sites.

This volume addresses the issues and their resolution. The 74 papers arise from the International Conference on Calibration and Reliability in Groundwater Modelling: Coping with Uncertainty held in Zürich, Switzerland (September 1999), the third in the ModelCARE conference series. ModelCARE 99 provided an international forum for state-of-the-art presentations on relevant methodologies and techniques, and the identification of the needs for future development, and so this volume forms a comprehensive overview.

Modelling concepts, stochastic modelling, parameter estimation and model calibration, prediction reliability, use of field information, and nonlinear and coupled flow and transport modelling, are covered in separate sections which incorporate both the theoretical and the applied. There are applications of well-known inverse models such as MODFLOWP, PEST and UCODE, as well as innovative approaches including the development and use of artificial neural networks and genetic algorithms. The paper by Mary Hill et al. presents guidelines for producing calibrated groundwater models likely to represent the associated real systems more accurately than typically used methods. The titles and authors of the papers are listed below and the corresponding abstract can be obtained by clicking on the title.

Contents
Alphabetical List of Authors


     
  1. Modelling Concepts
     
     
  2. Stochastic Modelling
     
     
  3. Parameter Estimation and Model Calibration
     
     
  4. Reliability of Model Prediction
     
     
  5. Comprehensive Use of Field Information
     
     
  6. Nonlinear and Coupled Flow and Transport Modelling