A GPU-Accelerated Shallow-Water Scheme for Surface Runoff Simulations

Abstract

The capability of a GPU-parallelized numerical scheme to perform accurate and fast simulations of surface runoff in watersheds, exploiting high-resolution digital elevation models (DEMs), was investigated. The numerical computations were carried out by using an explicit finite volume numerical scheme and adopting a recent type of grid called Block-Uniform Quadtree (BUQ), capable of exploiting the computational power of GPUs with negligible overhead. Moreover, stability and zero mass error were ensured, even in the presence of very shallow water depth, by introducing a proper reconstruction of conserved variables at cell interfaces, a specific formulation of the slope source term and an explicit discretization of the friction source term. The 2D shallow water model was tested against two different literature tests and a real event that recently occurred in Italy for which field data is available. The influence of the spatial resolution adopted in different portions of the domain was also investigated for the last test. The achieved low ratio of simulation to physical times, in some cases less than 1:20, opens new perspectives for flood management strategies. Based on the result of such models, emergency plans can be designed in order to achieve a significant reduction in the economic losses generated by flood events.

Interpreting the Manning Roughness Coefficient in Overland Flow Simulations with Coupled Hydrological-Hydraulic Distributed Models

“…The generally high values of the roughness coefficient obtained in the three case studies are far from the values extensively used for hydraulic purposes in flood routing [40], but are within the range of values generally found in the literature for hydrological purposes [26,30,31,42,[88][89][90][91], especially for hillslopes and flood plains, where the rainfallrunoff process predominates.…”

Hydrological and Hydraulic Flood Hazard Modeling in Poorly Gauged Catchments: An Analysis in Northern Italy

“…Moreover, the code is developed in the compute unified device architecture (CUDA) environment, which enables parallel computing on graphics processing units (GPUs), leading to a drastic reduction in runtimes (of about two orders of magnitude) compared to serial codes, even for domains of several million cells [39]. The good performances of the PARFLOOD model in both simulations of theoretical cases and practical applications over complex bathymetries are well documented in previous works [11,34,[58][59][60][61][62], to which the reader is referred for further details.…”

“…For the river beds, in the absence of data for calibration, a value of the Strickler's roughness coefficient of 25 m 1/3 s −1 was assumed based on local inspections, literature suggestions [65], and previous studies conducted by the authors concerning neighboring watersheds with similar characteristics [62]. Moreover, this value allowed the reproduction of, at best, the numerical rating curve previously obtained at Saliceto through 1D hydraulic modeling.…”

A Self-Contained and Automated Method for Flood Hazard Maps Prediction in Urban Areas

“…Nogherotto et al [19] described an integrated hydrological, and hydraulic approach based on the river discharges estimated through the hydrological model CHyM and on the CA2D hydraulic model to calculate the flow over a digital elevation model. More recently, Aureli et al [20] solved the complete 2D SW Equations starting from the precipitations and simulating the propagation on structured non-uniform grids.…”