Journal of Water and Climate Change (Dec 2023)
Regionalization of flow duration curves for catchments in southern India using a hierarchical cluster approach
Abstract
The present study on the hydrologic regionalization was taken up to evaluate the utility of hierarchical cluster analysis for the delineation of hydrologically homogeneous regions and multiple linear regression (MLR) models for information transfer to derive flow duration curve (FDC) in ungauged basins. For this purpose, 50 catchments with largely unregulated flows located in South India were identified and a dataset of historical streamflow records and 16 catchment attributes was created. Using selected catchment attributes, three hydrologically homogenous regions were delineated using a hierarchical agglomerative cluster approach, and nine flow quantiles (10–90%) for each of the catchments in the respective clusters was derived. Regionalization approach was then adopted, whereby using step-wise regression, flow quantiles were related with readily derived basin-physical characteristics through MLR models. Cluster-wise performance analysis of the developed models indicated excellent performance with an average coefficient of determination (R2) values of 0.85, 0.97, and 0.8 for Cluster-1, -2, and -3, respectively, in comparison to poor performance when all 50 stations were considered to be in a single region. However, Jackknife cross-validation showed mixed performances with regard to the reliability of developed models with performance being good for high-flow quantiles and poor for low-flow quantiles. HIGHLIGHTS Hierarchical cluster analysis was used to delineate 50 unregulated catchments into homogenous groups.; Nine flow quantiles of the flow duration curve were extracted for each catchment and related to significant catchment attributes through multiple linear regression models.; Accuracies of models developed for each cluster were good but jackknife cross-validation showed fairly high reliability for only high-flow quantiles.;
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