Region of influence (ROI) approach to regional flood frequency analysis

Good extreme flow estimation is a necessity for the proper design of river engineering development, flood protection or urban engineering works. Usually, a short record length, or no data record at all, at the site of interest necessitates the use of the regional flood frequency approach. Regional flood frequency analysis employs spatial information in order to enhance the reliability of the temporal data. The region of influence (ROI), employed here, ensures that each site has a region with a potentially unique combination of stations. The regionalization incorporating a homogeneity test ensures that the selected stations have similar extreme flow characteristics. The hierarchical feature is added to the ROI approach in order to further enhance the efficiency of the spatial information transfer. It does this by taking advantage of the different spatial similarity scales that have been observed for different orders of moments for a flood frequency distribution. The incorporation of this concept into the ROI framework is accomplished by allowing for a set of ROIs for a site as opposed to a single ROI.;The regional flood frequency approach presented in this study can be applied to both the case of gauged sites and ungauged sites. The relative merits of the methodology for the ungauged case are demonstrated through an application to extreme flow data for sites in Newfoundland, Canada. The new approach is compared with results obtained from regression analysis and is shown to provide improved estimates of extreme flow quantiles at sites which are considered to be ungauged. The hierarchical ROI approach is evaluated through the use of a Monte Carlo experiment applied to data from another collection of unregulated catchments in midwest Canada. The simulation experiment shows that with this refinement of the new methodology, an improvement in flood quantile estimation is achieved.