Enhancing Streamflow Predictions with a River Parameterization in an Integrated Hydrological Model

Flow conditions in rivers and open channels are often incorporated into hydrogeological models with a constant horizontal grid resolution, typically without considering real river channel widths. Such grid mismatches can lead to an underestimation of flow velocity where river widths are narrower than the model’s grid size. Furthermore, the exchange between rivers and the subsurface is often too large, leading to erroneously high vertical exchange rates. To address these challenges, this study approximates subscale river channel flow using the kinematic wave equation for overland flow calculation of the ParFlow integrated hydrological model, enhanced by a scaled roughness coefficient as proposed by Schalge et al. (2019). The scaling exploits a relationship between grid cell size and river width, derived from a simplified modification of the Manning-Strickler equation. Additionally, subsurface-river exchange rates, including exfiltration and infiltration rates, are adjusted along riverbeds based on grid resolution. These adjustments correct the exchange rates even when the grid size is relatively coarse. The proposed scaling approach was implemented and validated using the ParFlow integrated hydrological model with its integrated land surface model CLM. The model setup for the test runs features a spatial resolution of 611m over Germany and surrounding regions. The reliability of the results was assessed using an innovative application of the First Order Reliability Method (FORM) that shows significantly improved streamflow predictions. A cross-validation with observations from gauging stations confirms these improvements, underscoring the effectiveness of the proposed river-width parameterization.