Nonlinear, discrete flood event models, 3. Analysis of prediction uncertainty

Abstract

This series of papers consists of three parts. Part 1 ∗ ∗ Bates and Townley (this volume). described and illustrated the application of maximum a posteriori (MAP) estimation to nonlinear, discrete flood event models. Part 2 ∗∗ ∗∗ Bates (this volume). dealt with the application of measures of statistical nonlinearity to model and rainfall-runoff data set combinations. The present paper (Part 3) is concerned with the assessment of the precision of model predictions. The use of first-order, second-order and Monte Carlo analyses to evaluate the prediction uncertainty caused by errors in model parameter estimates is described. A case study is presented to demonstrate the utility of prediction uncertainty analysis.