Enhancing process interpretation with isotopes: potential discharge-isotope trade-offs in ecohydrological modelling of heavily managed lowland catchments

Abstract

Tracer-aided modelling (TAM) can help quantify ecohydrological processes, as stable water isotopes (δ18O and δ2H) can provide complementary information beyond streamflow and help constrain equifinality. Whilst TAM has been successfully undertaken in smaller rural research (< 100 km2) catchments with limited anthropogenic impacts, its utility in more heavily managed catchments remains untested, particularly as isotope samples are usually unavailable. 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 the capital of Berlin, Germany, and sustaining agricultural and industrial demands. Disentangling ecohydrological water partitioning in this evapotranspiration (ET) dominated region is complicated by heterogeneous land use, extensive hydraulic infrastructure and a long legacy of intensive management. We used the spatially distributed tracer-aided model STARR to simulate water fluxes and storage dynamics over a 6-year period. Temporally coarse (seasonal) isotope data was used in calibration as well as streamflow to help constrain estimates of subsurface runoff sources and ET partitioning. In most cases balanced calibrations using both isotopes and discharge increased confidence in plausible process representation in the modelling. When the trade-offs between dual calibration targets could not be reconciled, these were likely explained by anthropogenic factors that were not easily incorporated in the modelling framework. Such trade-offs therefore provide opportunities for learning about epistemic errors (e.g. un-represented water withdrawls for irrigation) that can be used to improve future models for heavily managed catchments. 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.