7. Parameter Estimation and Predictive Uncertainty

  1. Keith Beven

Published Online: 17 FEB 2012

DOI: 10.1002/9781119951001.ch7

Rainfall-Runoff Modelling: The Primer, Second Edition

Rainfall-Runoff Modelling: The Primer, Second Edition

How to Cite

Beven, K. (2012) Parameter Estimation and Predictive Uncertainty, in Rainfall-Runoff Modelling: The Primer, Second Edition, John Wiley & Sons, Ltd, Chichester, UK. doi: 10.1002/9781119951001.ch7

Author Information

  1. Lancaster University, UK

Publication History

  1. Published Online: 17 FEB 2012
  2. Published Print: 13 JAN 2012

ISBN Information

Print ISBN: 9780470714591

Online ISBN: 9781119951001

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Keywords:

  • parameter estimation, predictive uncertainty;
  • protocol, reducing parameter uncertainty;
  • model calibration;
  • model calibrations and uncertainty;
  • Sobol' Global Sensitivity Analysis;
  • performance, likelihood measures;
  • automatic optimisation techniques;
  • input uncertainties, within Bayesian;
  • GLUE, Saeternbekken MINIFELT, Norway

Summary

This chapter contains sections titled:

  • Model Calibration or Conditioning

  • Parameter Response Surfaces and Sensitivity Analysis

  • Performance Measures and Likelihood Measures

  • Automatic Optimisation Techniques

  • Recognising Uncertainty in Models and Data: Forward Uncertainty Estimation

  • Types of Uncertainty Interval

  • Model Calibration Using Bayesian Statistical Methods

  • Dealing with Input Uncertainty in a Bayesian Framework

  • Model Calibration Using Set Theoretic Methods

  • Recognising Equifinality: The GLUE Method

  • Case Study: An Application of the GLUE Methodology in Modelling the Saeternbekken MINIFELT Catchment, Norway

  • Case Study: Application of GLUE Limits of Acceptability Approach to Evaluation in Modelling the Brue Catchment, Somerset, England

  • Other Applications of GLUE in Rainfall–Runoff Modelling

  • Comparison of GLUE and Bayesian Approaches to Uncertainty Estimation

  • Predictive Uncertainty, Risk and Decisions

  • Dynamic Parameters and Model Structural Error

  • Quality Control and Disinformation in Rainfall–Runoff Modelling

  • The Value of Data in Model Conditioning

  • Key Points from Chapter 7

  • Likelihood Measures for use in Evaluating Models

  • Combining Likelihood Measures

  • Defining the Shape of a Response or Likelihood Surface