Multi-Model Comparison of Atmospheric River Flood Simulations in the Russian River Basin

Abstract. Extreme atmospheric river (AR) events are a dominant driver of flood risk in Northern California. Traditional flood studies and operational forecasts often rely on a single model; however, substantial structural differences persist across hydrologic modelling frameworks due to variations in process representations. Here, we present a multi-model comparison framework to evaluate differences in streamflow and flood inundation during an AR-driven flood event in the Russian River Basin (Sonoma County, California) in late February 2019. Three physical-based modelling systems, each forced with a common observation-based precipitation dataset, are compared: (1) Torrent, a computationally efficient overland flow model operating directly on digital elevation models (DEMs); (2) HEC-RAS, implemented using a two-dimensional shallow-water (Saint-Venant) solver in rain-on-grid mode; and (3) WRF-Hydro-HAND, a multi-scale hydrologic routing framework that combines distributed runoff generation with terrain-based inundation mapping. These systems differ fundamentally in their treatments of runoff generation, infiltration, and flow routing, enabling an explicit comparison of model behavior across frameworks. Model performance for channel water levels is evaluated against observations from U.S. Geological Survey stream gauges using the modified Kling–Gupta Efficiency (KGE′) and its components, including correlation, bias ratio, and variability ratio, together with diagnostics of peak timing. In addition, inundation extent is evaluated using the Landsat-derived Dynamic Surface Water Extent (DSWE) product, which provides spatially distributed observations of flood extent. Analysis of channel dynamics shows that variability and bias dominate model performance differences, while timing errors play a secondary role. Results indicate that all models capture the primary inundation along the mainstem Russian River, but substantial differences emerge in tributary and floodplain regions. Torrent and HEC-RAS tend to overestimate flood extent, while WRF-Hydro-HAND tends to underestimate it. These findings highlight the importance of model structure in flood simulation and demonstrate the value of multi-model frameworks for improving understanding of flood behavior in complex watershed systems.