Can we realistically use archetypal transit time distributions for integrating soil moisture, surface and subsurface flows in order to determine temporally variable catchment response?

The management of water resources is complicated, in particular when dealing with the prediction of solute export from entire catchments. One common approach is to set up physically-based, distributed hydrologic models for specific catchments, to calibrate them with recorded time series of precipitation and discharge and thus to simulate in detail every aspect of solute transport in the catchments. However, the setup of such models is relatively laborious and the application often computationally expensive. Also, the results are usually not directly transferable to other catchments.

We facilitated a simpler approach for the prediction of solute export by using a physically-based model to integrate more realism into a conceptual model (at the catchment scale). This could be achieved by linking the shape of transfer functions (which are used in many conceptual models to convert solute input into solute output) with physically measurable catchment and climate parameters. These transfer functions are forward transit time distributions that contain detailed information on how long waters and substances entering with a particular precipitation event stay inside of a catchment before they discharge. The shape of transit time distributions changes depending on which flow paths are preferentially activated during and after a precipitation event. The shape also varies spatially with specific catchment characteristics like, for example, soil depth or hydraulic conductivity.

In a virtual experiment that forms the basis of this study we used a physically-based, distributed model (HydroGeoSphere) to examine how the shape of transit time distributions changes spatially between catchments with different properties and how it changes temporally within one catchment with changing antecedent moisture content. Now we verified the results of the virtual modeling study with the help of empirical field data in real-world catchments. To this end we used discharge and nitrate time series of the freely accessible data base Germany, selected, set up and calibrated six uniquely representative (archetypal) catchments in HydroGeoSphere and compared the resulting transit time distributions with the ones produced in the virtual catchments.