Flood frequency estimation in New Zealand using a region of influence approach and statistical depth functions.

• A region of influence approach and data depth is used to estimate flood magnitude. • Performance is affected by statistical outliers having unusual physical features. • More accurate rainfall information will significantly improve method performance. • The method can be used for design in ungauged catchments. A region of influence approach in which statistical depth functions are used to select gauged catchments having similar flood generation behaviour to a given ungauged basin coupled with nonparametric regression on catchment characteristics is employed to estimate mean annual and a quantile flood of 100 year return period in New Zealand basins. This approach may be applied internationally. Relative and root mean square errors assessed by jack-knife resampling are too large to be useful for detailed design in ungauged catchments but are much smaller than those resulting from a conventional multiple nonlinear regression approach. The distribution of errors for samples of sites indicates that large error values result from contributions from a relatively small number of statistical outliers Although these are all natural catchments, the outlier basins have particular physical characteristics such as moraines, karst features and pumice sediments which affect their flood generation processes. Relative errors in estimates for an ungauged basin may be predicted using a relationship involving differences in area, rainfall and statistical depth between the ungauged catchment and gauged similar catchments. Improved analytical techniques and selection and measurement of catchment characteristics should reduce error magnitude but not perhaps sufficiently for use in detailed design. Parallel development based on rainfall-runoff models is desirable but the present lack of requisite information largely concerning rainfalls means that attainment of desired accuracy is a distant prospect. [ABSTRACT FROM AUTHOR]