In this work, we present a reverse flow routing procedure, which allows estimating discharge hydrographs at upstream ungauged stations by means of information available at downstream monitored sites. The reverse routing problem is solved adopting a Bayesian Geostatistical Approach (BGA). In order to capture the complex hydrodynamic field typical of many real cases of rivers including large floodable areas, meanwhile overcoming the computational time limitations, we adopted as forward model a selfdeveloped 2D-SWE parallel numerical model (PARFLOOD) that allows achieving ratio of physical to computational time of about 500-1000. To exploit the computational capabilities of modern GPU cluster, a parallel procedure to estimate the Jacobian matrix required by the BGA approach has been implemented. The inflow hydrograph in a river reach with several meanders and floodplains has been estimated in "only" 13 hours using a HPC cluster with 10 P100 Nvidia GPUs.

Hydrograph estimation at upstream ungauged sections on the Secchia River (Italy) by means of a parallel Bayesian inverse methodology / Ferrari, Alessia; D'Oria, Marco; Vacondio, Renato; Mignosa, Paolo; Tanda, Maria Giovanna. - ELETTRONICO. - 40:(2018), p. 06034. ((Intervento presentato al convegno 9th International Conference on Fluvial Hydraulics, River Flow 2018 tenutosi a francia nel 2018 [10.1051/e3sconf/20184006034].

Hydrograph estimation at upstream ungauged sections on the Secchia River (Italy) by means of a parallel Bayesian inverse methodology

Alessia Ferrari;Marco D'Oria;Renato Vacondio;Paolo Mignosa;Maria Giovanna Tanda
2018

Abstract

In this work, we present a reverse flow routing procedure, which allows estimating discharge hydrographs at upstream ungauged stations by means of information available at downstream monitored sites. The reverse routing problem is solved adopting a Bayesian Geostatistical Approach (BGA). In order to capture the complex hydrodynamic field typical of many real cases of rivers including large floodable areas, meanwhile overcoming the computational time limitations, we adopted as forward model a selfdeveloped 2D-SWE parallel numerical model (PARFLOOD) that allows achieving ratio of physical to computational time of about 500-1000. To exploit the computational capabilities of modern GPU cluster, a parallel procedure to estimate the Jacobian matrix required by the BGA approach has been implemented. The inflow hydrograph in a river reach with several meanders and floodplains has been estimated in "only" 13 hours using a HPC cluster with 10 P100 Nvidia GPUs.
Hydrograph estimation at upstream ungauged sections on the Secchia River (Italy) by means of a parallel Bayesian inverse methodology / Ferrari, Alessia; D'Oria, Marco; Vacondio, Renato; Mignosa, Paolo; Tanda, Maria Giovanna. - ELETTRONICO. - 40:(2018), p. 06034. ((Intervento presentato al convegno 9th International Conference on Fluvial Hydraulics, River Flow 2018 tenutosi a francia nel 2018 [10.1051/e3sconf/20184006034].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11381/2851752
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