Spatial Interpolation Models Research Articles

Input errors in rainfall-runoff modelling

Precipitation is one of the most variable of the hydrologic processes. This presents two particular problems when hydrologic process of basin scale are studied via mathematical models. The first is the extent to which areal rainfall distribution can be determined from point measurements and the second is the effect of precipitation uncertainty on the uncertainty of catchment model parameters. This paper presents a state-of-the-art survey of methods used for handling the first problem. Spatial interpolation models commonly in use are discussed. A Bayesian type optimisation procedure to estimate model parameters is presented and demonstrated for a real world example. The technique relaxes the usual least squares assumption of normally distributed residuals and estimates an error distribution which is a member of a family of distributions which includes the normal and Laplace distribution.