The improvements in computational abilities and availability of large high-resolution datasets have made the use of partial differential equation based numerical models in hydrology an effective tool for predictions of extreme events and management of water supplies. These advances combined with climate change driven increases in extreme hydrologic events, such as flooding, has created a demand for more accurate and informed water management and prediction tools. Hans, an extreme storm event in 2023, saw 100-139 mm of precipitation over a large interior area of Norway in a short time. The event caused flooding and landslides, particularly in the area of Nesbyen, which lead to widespread damage of infrastructure and property. To improve future responses and preparation to these types of events this study aims to create more accurate and informed runoff model based on finite element discretizations of surrogates to the shallow water equations. These surrogates include the Diffusive Wave Approximation [1], and the multi-dimensional Kinematic Wave Approximation [2]. In the present work, we develop finite element approximations of these shallow water surrogates. Our focus in the development of a model that utilizes the elevation and landcover data for the Nesbyen catchment and precipitation data from the Hans event as input and model data. Focus is given to the validation of the developed approximations utilizing the diffusive wave model, whereas a novel 1D-2D coupled model utilizing the kinematic wave equation is also presented. References [1] R Alonso, Mauricio Santillana, and Clint Dawson. On the diffusive wave approximation of the shallow water equations. European Journal of Applied Mathematics, 19(5):575–606, 2008. [2] Dustin W West, Ethan J Kubatko, Colton J Conroy, Mariah Yaufman, and Dylan Wood. A multidimensional discontinuous galerkin modeling frame- work for overland flow and channel routing. Advances in Water Resources, 102:142–160, 2017.