Automated Selection of Pure Base Flows from Regular Daily Streamflow Data: Objective Algorithm

The identification of base flow from an available record of streamflow measurements for recession rate analysis is often a difficult and time-consuming process affected by unavoidable errors and subjective aspects. Here, several stringent criteria are proposed for automated selection of base flows for this method and are applied to select pure base flows in 26 catchments from the United States, Australia, and China. The characteristic drainage timescale parameter ($K$) of the linear response function was chosen as the effectiveness measure of the automated method; the $K$ values estimated using this method are $44.5\pm 13.2$ days compared with $45.7\pm 10.5\mathrm{days}$ estimated manually for the catchments with long records. The effects of different imposed criteria on the base flow selection are also quantified using this parameter. The proposed algorithm provides a faster and more objective methodology for automated selection of base flows for recession rate analysis and will thus greatly facilitate its application.