A synthetic study to evaluate the utility of hydrological signatures for calibrating a base flow separation filter

Abstract

Estimation of base flow from streamflow hydrographs has been a major challenge in hydrology for decades, leading to developments of base flow separation filters. When without tracer or groundwater data to calibrate the filters, the standard approach to apply these filters in practice involves some degrees of subjectivity in choosing the filter parameters. This paper investigates the use of signature-based calibration in implementing base flow filtering by testing seven possible hydrological signatures of base flow against modeled daily base flow produced by Li et al. (2014) for a range of synthetic catchments simulated with HydroGeoSphere. Our evaluation demonstrates that such a calibration method with few selected signatures as objectives is capable of calibrating a filter–Eckhardt filter–to yield satisfactory base flow estimates at daily, monthly and long-term time scales, outperforming the standard approach. The best performing signatures can be readily derived from streamflow time series. While their performance depends on the catchment characteristics, the catchments where the signature method performs can be distinguished using commonly-used descriptors of flow dynamics.