available at: http://ipweaq.intersearch.com.au/ipweaqjspui/handle/1/5386 (last access: 2 June 2021), At a 5 times finer resolution of Δ x=1 m, all solvers predict a steeper wave front, although the FV1 wave-front prediction at Δ x=1 m is still relatively smooth, being closer to the ACC prediction at Δ x=5 m. Solver runtimes for the entire 5.5 d simulation are shown in Table 5. On the same grid, FV1-GPU is about 2 times faster than ACC on a 16-core CPU, which is consistent with earlier findings in Sect. 3.1 and 3.2. FV1-GPU and ACC runtimes scale as expected: halving the grid spacing quadruples the total number of elements and halves the time step due to the CFL constraint. Hence, halving the grid spacing multiplies the runtime by a factor of about 8. At all grid spacings between 40 and 10 m, FV1-GPU and ACC simulations run faster than real-time and complete in less than 5.5 d, indicating that these solvers are suitable for real-time flood forecasting applications.

While no exact solution is available, DG2, FV1 and ACC predictions of water depth and velocity agree closely with existing industrial model results (Fig. 4.10 and 4.11 in Néelz and Pender, 2013). ACC and DG2 water depth predictions are almost identical at all gauge points (Fig. 6a–d). FV1 predictions are nearly identical, except that the wave front is slightly smoother and arrives several minutes earlier than ACC or DG2, as seen at point 5 (Fig. 6c) and point 6 (Fig. 6d).flood modeling, Water Resour. Res., 48, W05528, https://doi.org/10.1029/2011WR011570, 2012. a, b, c, d, e I have performed dozens of concerts and gone on tour with it! It is very robust, and it is also quite heavy.

refinement level, L, is deduced such that 2 L≥ p x and 2 L≥ p y. Then, a hierarchy of grids of decreasing refinement levels At point 1, ACC and DG2 velocity predictions agree closely with the majority of industrial models (Fig. 4.11 in Néelz and Pender, 2013). LISFLOOD-FV1 predicts faster velocities up to 0.5 ms −1, which is close to the prediction of TUFLOW FV1 ( Huxley et al., 2017, Table 11). during 23 and 55 min, reaching a peak of 5 m 3 s −1, at t=37 min. The area has two different classes of land use: roads and pavements higher reduction in the number of elements (Fig. 6a). With ε = 10 - 3 , the ratios become 21, 7.6 and 4.7 times, respectively. The in which variables with an overline denote temporary modifications to the original variables that ensure well-balancedness and non-negative water depths ( Kesserwani et al., 2018; Liang and Marche, 2009) and F ̃ W , F ̃ E , G ̃ S , G ̃ N denote HLL approximate Riemann fluxes across western, eastern, northern and southern interfaces. Each Riemann solution resolves the discontinuity between the flow variables evaluated at the limits of the locally planar solutions adjacent to the interface. Because of the locally planar nature of the DG2 solutions, such a discontinuity is likely to be very small when the flow is smooth – as is often the case for flood inundation events – and will not be significantly enlarged by grid coarsening.Personally, I like very much the electric piano, the sound of piano1, I have virtually never used the "Mallets," for example, the organs could be better and certain string styles are really very good. This paper presents a new LISFLOOD-DG2 solver of the full shallow-water equations, which is integrated into LISFLOOD-FP 8.0 and freely available under the GNU GPL v3 license ( LISFLOOD-FP developers, 2020). LISFLOOD-FP 8.0 also includes an updated FV1 solver obtained by simplifying the DG2 formulation. Both solvers support standard LISFLOOD-FP configuration parameters and model outputs, meaning that many existing LISFLOOD-FP modelling scenarios can run without modification. However, this approach relies on the availability of observation data, and, due to modelling sensitivities at the scale of the grid, optimal positions can vary depending on the choice of solver and grid resolution. Overall, the FV1, ACC and DG2 solvers converged on similar water depth solutions with successive grid refinement.