Streamflow estimation in ungauged basins using watershed classification and regionalization techniques

Classifying watersheds prior to regionalization improves streamflow predictions in ungauged basin. Present study aims to assess the ability of combining watershed classification using dimensionality reduction techniques with regionalization methods for reliable streamflow prediction using soil and water assessment tool (SWAT). Isomap and principal component analysis (PCA) are applied to watershed attributes of 30 watersheds from Godavari river basin in India to classify them. The best classification technique is determined by calculating similarity index (SI). The results showed that Isomap is better at classifying hydrologically similar watersheds than PCA with an average SI value of 0.448. The regionalization methods such as global mean, inverse distance weighted (IDW) and physical similarity were applied to transfer the parameters from watersheds of best watershed classification group to the pseudo-ungauged watersheds, using SWAT model. The present study suggests that classifying watersheds with Isomap and regionalization using physical similarity improves the efficiency of streamflow estimation in ungauged basins.