Intercomparison of regional flood frequency estimation methods at ungauged sites for a Mexican case study

This paper presents an adaptation of some regional estimation approaches to tropical climates and a comparison of their performance on the basis of their application to data from the Balsas, Lerma and Pánuco River Basins located in Mexico. Four approaches are used in this study for the delineation of homogeneous regions: The first one is the hierarchical cluster analysis approach which leads to fixed hydrologic regions. The second one is the canonical correlation analysis (CCA) which allows the determination of hydrologic neighborhoods that are specific to the site of interest. The third one is a revised version of the canonical correlation analysis approach that is free of parameter optimization and which can be automated easily. Finally, the fourth one is the technique of canonical kriging which consists in interpolating hydrological variables over the canonical physiographical space. The methods based on the canonical correlation analysis approach provide also the basis for identifying the explanatory variables to be used during the step of regional estimation. Regional estimation is carried out based on a multiple regression approach. A data set of 29 stations from several Mexican River Basins in and around the Balsas region is used to show the advantages and weaknesses of each method and to demonstrate their usefulness in the context of regional flood quantile estimation. This study allows also to test the robustness of these methods through their application to a real world case study with a relatively limited number of stations. While all methods performed quite adequately, results indicate clearly the advantages of the neighborhood type of approach and the superiority of the canonical correlation analysis based methods. Results demonstrate that CCA-based methods lead to best performances overall. While hierarchical clustering seems generally to lead to less biased quantile estimates, the lowest root mean square error values are almost consistently obtained for the CCA-based methods. Results seem also to point out that all methods are quite sensitive to the quality and quantity of data available. The method of canonical kriging does not seem to be more sensitive to the database quality than the other two CCA-based methods.