Baseflow separation combined with stratified sampling serving the accurate estimation of pollutant loads—the example of a small catchment with high anthropogenic pressures

Abstract

Abstract This study presents a modified baseflow separation framework for stratified pollutant load estimation in managed catchments subject to substantial point-source wastewater discharge, applied to the Koppány stream (Hungary), a system characterized by intensive agricultural and wastewater-derived pollution. Three established baseflow separation methods were evaluated, namely the Lyne–Hollick, Eckhardt, and Rimmer–Hartmann approaches. Where the standard Rimmer–Hartmann method yielded physically unrealistic results, a modified three-component formulation was developed by incorporating wastewater as an explicit end-member in the electrical conductivity (EC)-based mixing equation. The modified method produced baseflow-index (BFI) values of 0.80 at Törökkoppány and 0.83 at Tamási, consistent with the Eckhardt filter result of 0.80 at both stations. Event classification thresholds of 0.77 and 0.82 were selected through a sensitivity analysis across nine candidate values per station, yielding non-event volume fractions of 75% and 76%, respectively—in close agreement with the long-term regional BFI of 0.72–0.75 reported for the catchment. Annual loads of metals, nutrients, pharmaceuticals, and per- and polyfluoroalkyl substances were partitioned between event and non-event conditions using a stratified sampling design combining weekly grab samples, event-based automatic sampling, and continuous monitoring of discharge and EC. Load estimates carry inherent uncertainty arising from the binary classification of event and non-event periods and from the assumption of constant wastewater EC and discharge during calibration. The modified framework offers a practical and transferable tool for catchments where point-source discharges substantially alter the natural flow regime.