Understanding Catchments' Hydrologic Response Similarity of Upper Blue Nile (Abay) basin through catchment classification

In hydrology study and modeling, watershed classification techniques are critical for finding groups of hydrologically similar catchments, and they are used to predict streamflow for ungauged catchments in data-scarce regions during regionalization. In addition, it improves our understanding of the interaction between climate variability, catchment characteristics, and the resulting hydrological response. The goal of this work was to understand the catchments' hydrologic response similarity by combining climatic, physiographic, and flow signature characteristics to highlight the regional pattern of Upper Blue Nile basin flow signatures. Similarities in nine (9) flow signatures and 15 catchment descriptors were explored for 32 catchments of the upper Blue Nile (Abay) basin. Correlation analysis was done using PCA for each catchment characteristic to decrease the multicollinearity problems between different catchment descriptors and flow signatures. The catchments were grouped together and analyzed for flow signature values and physiography characteristics using an advanced hierarchical k-means algorithm combined with Euclidean distance and Ward's linkage method. We found that catchments are classified into three types with both similar flow signatures and catchment descriptors. The most dominant physiographic characteristic in all clusters is the aridity index, which separates the energy-limited catchments from the moisture-limited catchments. In addition, explanatory variables such as higher mean annual precipitation (P-mean), soil type, topography, and other aspects of the climate/weather had an impact on clustering. Moreover, the results of this study showed that catchment clustering patterns are mainly dependent on discharge characteristics, geographical proximity, and climatic factors of catchments.