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

Abstract

Abstract. This paper presents a novel methodology for estimating the unknown discharge hydrograph at the entrance of a river reach when no information is available. The methodology couples an optimization procedure based on the Bayesian geostatistical approach (BGA) with a forward self-developed 2-D hydraulic model. In order to accurately describe the flow propagation in real rivers characterized by large floodable areas, the forward model solves the 2-D shallow water equations (SWEs) by means of a finite volume explicit shock-capturing algorithm. The two-dimensional SWE code exploits the computational power of graphics processing units (GPUs), achieving a ratio of physical to computational time of 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 that allows one to take advantage of remote high-performance computing clusters (including those available on the Cloud) equipped with GPUs. The capability of the methodology is assessed by estimating irregular and synthetic inflow hydrographs in real river reaches, also taking into account the presence of downstream corrupted observations. Finally, the procedure is applied to reconstruct a real flood wave in a river reach located in northern Italy.

Enhancing the resilience to flooding induced by levee breaches in lowland areas: a methodology based on numerical modelling

“…This high-level language allows for the exploitation of both hardware resources: the CPU (the host) and the GPU (the device). The good computational performance of this code for field applications was assessed in previous works (Vacondio et al, 2016;Dazzi et al, 2018;Dazzi et al, 2019;Ferrari et al, 2018;Ferrari et al, 2019).…”

“…In general, the most important results for quantifying the hazard for human lives are the maximum simultaneous water depth and velocity, which can be represented in terms of the Froude number, total head, total force and/or total depth. This last indicator, which represents the water depth at rest D whose static force is equivalent to the total force of the flow, is evaluated as follows (Aureli et al, 2008;Ferrari et al, 2019):…”

A methodology based on numerical models for enhancing the resilience to flooding induced by levee breaches in lowland areas

“…Morales-Hernandez et al (2014) show that a 2D GPU model may even outperform a 1D-2D coupled model in terms of execution time. Moreover, the implementation of optimization techniques, such as the local time stepping strategy (Dazzi et al, 2018), and the development 30 of codes able to exploit the multi-GPU architecture typical of High Performance Computing (HPC) clusters (Turchetto et al, 2018;Ferrari et al, 2018) can further enhance the efficiency.…”

“…CC BY 4.0 License. performance of this code for field applications was assessed in previous works (Vacondio et al, 2016;Dazzi et al, 2018Dazzi et al, , 2019Ferrari et al, 2018Ferrari et al, , 2019.…”

Characterization of Hydraulic Heterogeneity of Alluvial Aquifer Using Natural Stimuli: A Field Experience of Northern Italy

“…These references are by no means exhaustive and serve only to highlight the importance of the overall problem of parameter estimation. The Bayesian Geostatistical Approach (BGA) [13] has become popular for estimating aquifer hydraulic parameters [14][15][16], inflow time series to river sections [17,18] or flow hydrograph in different contexts [19,20] and has been implemented in a freeware software named bgaPEST [21].…”