Using large-scale tracer-aided models to constrain ecohydrological partitioning in complex, heavily managed lowland catchments

Abstract. Tracer-aided modelling (TAM) enhances ecohydrological process understanding, as stable water isotopes (ẟ¹⁸O and ẟ²H) can help constrain equifinality and provide complementary information beyond streamflow. Despite being primarily applied in rural (<100 km²) catchments with minimal disturbance, TAM may assess epistemic uncertainties from unrecorded human activities affecting streamflow, improving model reliability. This study investigated four sub-catchments (Berste, Wudritz, Vetschauer, and Dobra) in the heavily-managed Middle Spree River basin (ca. 2800 km²), in NE Germany, a strategically vital water resource supplying drinking water to Berlin, Germany’s capital, and sustaining agricultural and industrial demands. Detailed evaluation of ecohydrological water partitioning in this evapotranspiration (ET)-dominated region is complicated by heterogeneous land use, extensive hydraulic infrastructure and overall intensive management. We used the spatially distributed tracer-aided model STARR to simulate the effects of natural water storage-flux dynamics and management interventions on streamflow over a 6-year period. Seasonal isotope data used for calibration additionally to streamflow effectively captured subsurface runoff, with isotope fractionation intensity strongly linked to ET apportionment. This multi-criteria calibration helped reduce equifinality in complex systems with human-induced epistemic challenges. Epistemic errors were manifested as strong trade-offs between the information content of the different calibration constraints (i.e., streamflow and isotopes). Although compromised solutions occasionally failed to meet acceptable performance thresholds for both calibrated variables, such conflicts highlight potentially important mismatches in process representation. Our modelling framework shows the potential for informative insights from wider use of (even sparse) isotope data sets in tracer-aided modelling of complex, heavily managed catchments.