Inhaltszusammenfassung

Process-behavioural hydrological modelling aims not only at predicting the discharge of an area within a model, but also at understanding and correctly depicting the underlying hydrological processes. Here, we present a new approach for the calibration and evaluation of water balance models, exemplarily applied to the Riverisbach catchment in Rhineland-Palatinate, Germany. For our approach, we used the behavioural model WaSiM. The first calibration step is the adjustment of the evapotranspira...Process-behavioural hydrological modelling aims not only at predicting the discharge of an area within a model, but also at understanding and correctly depicting the underlying hydrological processes. Here, we present a new approach for the calibration and evaluation of water balance models, exemplarily applied to the Riverisbach catchment in Rhineland-Palatinate, Germany. For our approach, we used the behavioural model WaSiM. The first calibration step is the adjustment of the evapotranspiration (ETa) parameters based on MODIS evapotranspiration data. This aims at providing correct evapotranspiration behaviour of the model and at closing the water balance at the gauging station. In the second step, geometry and transmissivity of the aquifer are determined using the characteristic delay curve (CDC). The portion of groundwater recharge was calibrated using the delayed flow index (DFI). In the third step, inappropriate pedotransfer functions (PTFs) could be filtered out by comparing dominant runoff process patterns under a synthetic precipitation event with a soil hydrological reference map. Then, the discharge peaks were adjusted based on so-called signature indices. This ensured a correct depiction of high-flow volume in the model. Finally, the overall model performance was determined using signature indices and efficiency measures. The results show a very good model fit with values of 0.87 for the NSE (Nash-Sutcliffe model efficiency coefficient) and 0.89 for the KGE (Kling-Gupta efficiency) in the calibration period, as well as an NSE of 0.78 and a KGE of 0.87 for the validation period. Simultaneously, our calibration approach ensured a correct depiction of the underlying processes (groundwater behaviour, runoff patterns). We were also able to detect the model parameterisations based on the PTFs that showed satisfactory results across all calibration steps. This enables a targeted selection of the most suitable PTFs for determining the soil properties. This means that our calibration approach allows selecting a process-behaviourally faithful one from many possible parameterisation variants» weiterlesen» einklappen

Autoren

Klassifikation

DFG Fachgebiet:
3.46 - Wasserforschung

DDC Sachgruppe:
Naturwissenschaften