Catchment classification: multivariate statistical analyses for physiographic similarity in the Upper Niger Basin

The objective of this study was to determine physiographic similarity, as indicator of hydrologic similarity\ud between catchments located in the Upper Niger Basin, and to derive the dominant factors controlling each group\ud singularity. We utilized a dataset of 9 catchments described by 16 physical and climatic properties distributed\ud across a wide region with strong environmental gradients. Catchments attributes were first standardized before\ud they underwent an integrated exploratory data analysis composed by Principal Component Analysis (PCA)\ud followed by Hierarchical Clustering. Results showed a clear distribution into 2 major clusters: a group of\ud easterly flat catchments and another of westerly hilly catchments. This nomenclature came from the\ud interpretation of the main factors, topography and longitude, that seem to control the most important variability\ud between both clusters. In addition, the hilly catchments were designated to be dominated by forest and\ud ACRISOL soil type, two additional drivers of similarity. The outcome of this study can help understanding\ud catchment functioning and provide a support for regionalization of hydrological information