Discharge hydrograph estimation at upstream-ungauged sections by coupling a Bayesian methodology and a 2D GPU Shallow Water model

Alessia Ferrari, Marco D'Oria, Renato Vacondio, Alessandro Dal Palù, Paolo Mignosa, Maria Giovanna Tanda
2018 Hydrology and Earth System Sciences Discussions  
<p><strong>Abstract.</strong> In this paper a novel methodology to estimate the unknown discharge hydrograph at the entrance of a river reach, where no information is available, is presented. The methodology is obtained by coupling an optimization procedure, based on the Bayesian Geostatistical Approach (BGA), with a forward self-developed 2D hydraulic model of the stream. In order to accurately describe the flow propagation in real rivers characterized by large floodable areas, the forward
more » ... as, the forward model solves the 2D Shallow Water Equations by means of a Finite Volume explicit shock-capturing algorithm. The forward code exploits the computational power of Graphics Processing Units (GPUs) achieving ratio of physical to computational time up to 1000. With the aim of enhancing the computational efficiency of the inverse estimation, the Bayesian technique is parallelized developing a procedure based on the Secure Shell (SSH) protocol which allows to take advantage of remote High Performance Computing clusters (including those available on the Cloud) equipped with GPUs. The capability of the coupled models is assessed estimating irregular and synthetic inflow hydrographs in real river reaches, taking into account also the presence of downstream corrupted observations. Finally, the capability to adopt this methodology for real cases is demonstrated by reconstructing a real flood wave in a river reach located in Northern Italy.</p>
doi:10.5194/hess-2018-118 fatcat:qiuhniqgkbg2fpsnrt4thb62aq