A network approach for delineating homogenous regions in regional flood frequency analysis

Regional flood frequency analysis forms the basis for ascertaining design thresholds for extreme flow events for the purpose of resource management and design of hydraulic structures, especially at ungauged or partially gauged basins. A crucial step in this analysis is transferring available information from gauged sites to ungauged sites, which is achieved through delineation of homogeneous regions encompassing multiple catchment locations, followed by the formulation of a flood estimation model. While this process has been accomplished through a range of statistical homogenization alternatives, the present study offers a new approach rooted in the theory of complex networks, offering considerable advantages over what is traditionally followed. Data from 202 sites in Australia representing catchments of varying geographic, climatic, and vegetation attributes are used to assess the alternative proposed. The results are examined via (1) direct comparison of the location and number of homogeneous neighbors from network theory with results using canonical correlation analysis (CCA) and (2) assessing the accuracy of estimated flood quantiles by applying a common model that estimates flood quantiles using information from the two alternate groups of homogeneous sites (from network theory and CCA). Results show that network theory offers merit in delineating homogenous regions, with resulting design flood estimates showing improvements across different return periods compared to the CCA alternative used.