SEAMLESS-WAVE is a developing “SoftwarE infrAstructure for Multi-purpose fLood modElling at variouS scaleS” based on "WAVElets" and their versatile properties. The vision behind SEAMLESS-WAVE is to produce an intelligent and holistic modelling framework, which can drastically reduce iterations in building and testing for an optimal model setting, and in controlling the propagation of model-error due to scaling effects and of uncertainty due statistical inputs.
The non-uniform ACC solver is distributed as a new solver in the LISFLOOD-FP ecosystem and follows the same standard usage with a few updates to input/output components.
Setting up the simulations for using the new non-uniform ACC solver follows the same conventions of LISFLOOD-FP as described in section “Input files and their format”, with a few updates to the .par
file:
acc_nugrid
.epsilon
, followed by a float number refering to the value of $\varepsilon$.L
, followed by an integer refering to the value of L..vtk
file format (see section “Non-uniform grid output files (-xxxx.vtk)” for visualising .vtk
files).By default both of these files are generated at the intervals specified by item saveint
. However, the generation of the .vtk
files can be suppressed (to save disk space) by including the item vtkoff
.
These modifications to the .par
files are summarised in the table below.
Item name input |
Description | Solver |
---|---|---|
acc_nugrid | Selects the non-uniofrm ACC solver | non-uniform ACC |
cuda | Runs the selected solver on GPU | All |
epsilon | The choice of error threshold, $\varepsilon$ | non-uniform ACC |
L | The maximum refinement levels, L | non-uniform ACC |
vtkoff | Suppress production of 2D multiresolution map files (*.vtk ) |
non-uniform ACC |
The technical background of how the ACC solver is adapted on the non-uniform grid generated by the multiwavets Galerkin projection of the DEM, and parallised on the GPU can be found in Sharifian et al. (2023), which provides a demonstration of the solver performance for five real-world fluvial/pluvial case studies.
These flooding case studies include three catchment-scale scenarios and two urban-scale scenarios that are summarised in table below.
Test Case | Source | Type | Number of elements (thousands) | L | R (m) | Simulation time (hr) |
---|---|---|---|---|---|---|
Lower triangle catchment | Özgen-Xian et al., 2020 | Pluvial | 149, 594, 3700 | 10, 11, 12 | 10, 5, 2 | 72 |
Upper Lee Catchment | Xia and Liang, 2018 | Pluvial | 2712 | 12 | 20 | 120 |
Eden catchment | Xia et al., 2019 | Fluvial | 6276 | 13 | 20 | 132 |
Glasgow urban area | Néelz and Pender, 2013 | Pluvial | 95 | 9 | 2 | 5 |
Cockermouth urban area | Muthusamy et al., 2021 | Fluvial | 2160 | 11 | 1 | 144 |
Step by step instructions on how to download and install the LISFLOOD-FP code, and reproduce the simulations for representative case studies can be found in the following videos links.