Evaluating Subsurface Parameterization to Simulate Hyporheic Exchange: The Steinlach River Test Site |
| |
| Authors: | Reynold Chow Jeremy Bennett Jürnjakob Dugge Thomas Wöhling Wolfgang Nowak |
| |
| Institution: | 1. Institute for Modelling Hydraulic and Environmental Systems (LS3)/SimTech, University of Stuttgart, Stuttgart,, Germany;2. Center for Applied Geoscience, University of Tübingen, Hölderlinstr. 12, Tübingen, 72074 Germany;3. Department of Hydrology, Technical University of Dresden, Dresden, Germany
Lincoln Agritech Ltd., Ruakura Research Centre, Hamilton, New Zealand |
| |
| Abstract: | Hyporheic exchange is the interaction of river water and groundwater, and is difficult to predict. One of the largest contributions to predictive uncertainty for hyporheic exchange has been attributed to the representation of heterogeneous subsurface properties. Our study evaluates the trade-offs between intrinsic (irreducible) and epistemic (reducible) model errors when choosing between homogeneous and highly complex subsurface parameter structures. We modeled the Steinlach River Test Site in Southwest Germany using a fully coupled surface water-groundwater model to simulate hyporheic exchange and to assess the predictive errors and uncertainties of transit time distributions. A highly parameterized model was built, treated as a “virtual reality” and used as a reference. We found that if the parameter structure is too simple, it will be limited by intrinsic model errors. By increasing subsurface complexity through the addition of zones or heterogeneity, we can begin to exchange intrinsic for epistemic errors. Thus, the appropriate level of detail to represent the subsurface depends on the acceptable range of intrinsic structural errors for the given modeling objectives and the available site data. We found that a zonated model is capable of reproducing the transit time distributions of a more detailed model, but only if the geological structures are known. An interpolated heterogeneous parameter field (cf. pilot points) showed the best trade-offs between the two errors, indicating fitness for practical applications. Parameter fields generated by multiple-point geostatistics (MPS) produce transit time distributions with the largest uncertainties, however, these are reducible by additional hydrogeological data, particularly flux measurements. |
| |
| Keywords: | |
|
|
