Regional Flood Frequency Estimation for the Mexican Mixteca Region by Clustering Techniques

Regionalization methods can help to transfer information from gauged catchments to ungauged river basins. Finding homogeneous regions is crucial for regional flood frequency estimation at ungauged sites. As it is the case for the Mexican Mixteca region site, where actually only one gauging station is working at present. One way of delineate these homogeneous watersheds into natural groups is by clustering techniques. In this paper, two different clustering approaches are used and compared for the delineation of homogeneous regions. The first one is the hierarchical clustering approach, which is widely used for regionalization studies. The second one is the Fuzzy C-Means technique which allow a station belong, at different grades, to several regions. The optimal number of regions is based on fuzzy cluster validation measures. The experimental results of both approaches are similar which confirm the delineated homogeneous region for this case study. Finally, the stepwise regression model using the forward selection approach is applied for the flood frequency estimation in each found homogeneous region.