Abstract. Some regional procedures to estimate hydrological quantiles at ungauged sites, such as the index-flood method, require the delineation of homogeneous regions as a basic step for their application. The homogeneity of these delineated regions is usually tested providing a yes/no decision. However, complementary measures that are able to quantify the degree of heterogeneity of a region are needed to compare regions, evaluate the impact of particular sites, and rank the performance of different delineating methods. Well-known existing heterogeneity measures are not well-defined for ranking regions, as they entail drawbacks such as assuming a given probability distribution, providing negative values and being affected by the region size. Therefore, a framework for defining and assessing desirable properties of a heterogeneity measure in the regional hydrological context is needed. In the present study, such a framework is proposed through a four-step procedure based on Monte Carlo simulations. Several heterogeneity measures, some of which commonly known and others which are derived from recent approaches or adapted from other fields, are presented and developed to be assessed. The assumption-free Gini index applied on the at-site L-variation coefficient (L-CV) over a region led to the best results. The measure of the percentage of sites for which the regional L-CV is outside the confidence interval of the at-site L-CV is also found to be relevant, as it leads to more stable results regardless of the regional L-CV value. An illustrative application is also presented for didactical purposes, through which the subjectivity of commonly used criteria to assess the performance of different delineation methods is underlined.
Uncertainty of quantile estimators using the population index flood method
