Abstract
Floods represent a severe cause of deaths and economic loss. In order to prevent, mitigate, and reduce flood risks and their consequences, hydraulic models allow analysing and mapping floods. The results of an appropriate model that works under local conditions are a valuable tool for local governments leading to sustainable management of floodplains. Around the world, high-mountain rivers have been poorly modelled; their orography and data scarcity present an extra research difficulty. Considering that all one-dimensional models assume that the river bed slope is small, this study evaluated two widely applied one-dimensional models: Mike11 and HEC-RAS, for modelling a high mountain river. Their best configuration under complex topographical conditions and their potential use was assessed by calibration and validation of the models. We found that the HEC-RAS model was not able to define a stable solution of the hydrodynamic modelling of the river, while Mike11 yielded stable results. Furthermore, the validation of the Mike11 model showed good performance. This study sets a precedent in the 1D modelling of high-mountain rivers with data scarcity.
Highlights
Floods represent about 40% of the natural disasters in the world (Ohl & Tapsell, 2000) and they killed most people by 2016 (Guha-Sapir, Hoyois, & Below, 2011)
Considering that all one-dimensional models assume that the river bed slope is small, this study evaluated two widely applied one-dimensional models: Mike11 and HEC-RAS, for modelling a high mountain river
We found that the HEC-RAS model was not able to define a stable solution of the hydrodynamic modelling of the river, while Mike11 yielded stable results
Summary
Floods represent about 40% of the natural disasters in the world (Ohl & Tapsell, 2000) and they killed most people by 2016 (Guha-Sapir, Hoyois, & Below, 2011). Different methodologies are useful for flow modelling and the analysis of river flood events, from linear interpolation of water level records (0D) Model selection depends on the information required, flow characteristics, and type and scale of the specific application. 1D models are most widely used since they require less information (cross sections and roughness coefficients) to be robust and to provide good quality results when the flow is aligned with the main channel axis of the river (Pender & Néelz, 2007; Vojinovic & Seyoum, 2011). 2D models are more popular lately due to the increase of the computational capacity and information availability, they have difficulties when
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