Bates, B.C., and Townley, L.R. (1988), Nonlinear, discrete flood event models, 1. Bayesian estimation of parameters, Journal of Hydrology, 99, 61-76.

In this paper (Part 1), a Bayesian procedure for parameter estimation is applied to discrete flood event models. The essence of the procedure is the minimisation of a sum of squares function for models in which the computed peak discharge is nonlinear in terms of the parameters. This objective function is dependent on the observed and computed peak discharges for several storms on the catchment, information on the structure of observation error, and prior information on parameter values. The posterior covariance matrix gives a measure of the precision of the estimated parameters. The procedure is demonstrated using rainfall and runoff data from seven Australian catchments. It is concluded that the procedure is a powerful alternative to conventional parameter estimation techniques in situations where a number of floods are available for parameter estimation. Parts 2 and 3 will discuss the application of statistical nonlinearity measures and prediction uncertainty analysis to calibrated flood models.


Copyright © 2005 by Lloyd Townley
Last revised: 17 July 2018