Treating an artificial catchment as ungauged: Increasing the plausibility of an uncalibrated, process-based SVAT scheme by using additional soft and hard data

The 1-D process-based model SIMULAT was applied to the 6 ha large artificial catchment “Chicken Creek” in Lausatia, Germany. Within the framework of a model intercomparison study, data availability was improved step by step, starting from sparse data conditions. Initially, the model was parameterised based on transfer functions (e.g., soil hydraulic properties were estimated from pedotransfer functions) and literature (e.g., plant parameters, boundary conditions), only. Then parameterisation was revised based on field inspection and additional quantitative data (e.g., from point measurements). Finally, soil moisture data were used for validation and calibration purposes. During this parameterisation process, model results became increasingly plausible although calibration and validation against observed discharge were not feasible because discharge data were not available to the modellers. Simulated discharge dynamics changed from an initially base flow-dominated and continuous flow regime to a system in which different flow components contribute similarly to the event-based total discharge, better conforming to the hydrological process understanding with respect to the development of a gully network. Qualitative information (=soft data) gained from a field visit particularly contributed to this improvement in process understanding towards a flow regime dominated by surface runoff, while additional quantitative information on system characteristics rather served the purpose of verifying (or revising) of model parameterisation and defining appropriate initial conditions. An evaluation of simulated surface runoff rates based on event-based discharge information for a subcatchment revealed that the model overestimated the surface runoff generation for all advanced modelling steps. A final validation of model results is not yet feasible as continuous discharge data at the catchment outlet are not available so far. However, the model application indicated that integration of soft and quantitative information can considerably increase the plausibility of model results in the case of poorly gauged basins while applying transfer functions developed under natural conditions might fail in artificial catchments.

► A 1-D SVAT model was applied to the artificial Chicken Creek catchment without calibration.
► Data availability was improved within several modelling steps.
► Qualitative information gained from a field visit particularly improved the process understanding.
► Quantitative information on system characteristics served to revise model parameterisation and initial conditions.
► Soft and hard data can considerably increase the plausibility of model results for poorly gauged basins.