Benchmark with known end states2D · free surfaceCandidate

Flooding a cut-off pond

Does a pond behind a ridge fill and settle at the right level?

Test A2C-EA1
Néelz (2013)
Version 1.0.0

Right answer: Known end states · Néelz (2013)
Results: 10 models · closest 0.27 % off · see them ↓
Must: leave the pond at the crest level within 2 cm

Sketch, not to scale.

Terrain
water depth at the end of the run (demo solver) for EA Test 1 — flooding a disconnected water body, with output points and the inflow line in red

Gaps are times when the cell at that point is dry.

What happens

Rising water spills over a 10.25 m ridge into a hollow, then falls away again. The trapped pond must end level with the ridge crest.

Why it matters

Floodplains are full of hollows that fill and stay wet. Models must not lose or invent water as it is trapped.

A good model must

leave the pond at the crest level within 2 cm
reach the right peak level

Exact answer and models

Water level at gauge P1 (400 m, 50 m)

The pond must settle at the level of the sill once the boundary falls (dashed).

Point at the chart to read every model's value; click a name to hide or show it.

How models did

In rank order: by each model's percent difference from the right answer, the largest over the test's accuracy checks (lower is better; results within 10 % of each other share a rank). Mass error, timing and NSE are shown beside it, not folded in. Each model runs the same inputs. Compare them in the results viewer (depth maps and animation) →

Rank	Model	Difference	Largest difference in	Run time
1	LISFLOOD-FP 8.3 · FV1	0.27 %	Pond level, point 1	4.8 s
2	Demo 2D suite example	0.44 %	Peak level	14.3 s
3	TELEMAC-2D openTELEMAC 9.1	0.56 %	Pond level, point 1	59.5 s
4	LISFLOOD-FP 8.3 · DG2	1.7 %	Pond level, point 1	18.1 s
5=	ANUGA 4.0.1	1.9 %	Pond level, point 2	1.7 min
5=	LISFLOOD-FP 8.3 · ACC	2.1 %	Pond level, point 1	3.4 s
7=	HEC-RAS 7.0 2D · SWE-EM	5.1 %	Pond level, point 1	23.5 s
7=	HEC-RAS 6.6 previous release · 2D SWE-EM	5.1 %	Pond level, point 1	26.0 s
7=	HEC-RAS 7.0 1D · 2D SWE-ELM	5.1 %	Pond level, point 1	19.3 s
7=	HEC-RAS 6.6 previous release	5.1 %	Pond level, point 1	37.7 s

LISFLOOD-FP FV1

LISFLOOD-FP 8.3, first-order finite-volume solver (full shallow-water equations)

#1 0.27 % off

Run time, finest grid: 4.8 s · AMD EPYC 7763 64-Core Processor, 2 cores, 15.6 GB, Linux 6.17.0-1022-azure (GitHub Actions (github-hosted, ubuntu24))

Settings: lisflood (fv1 solver, defaults; CPU, double precision)

Pond level, point 1

• 0.66 mm off

0.27 % of the 0.25 m pond depth at P1

Pond level, point 2

• 0.66 mm off

0.26 % of the 0.25 m pond depth at P2

Peak level

• 0.38 mm off

0.11 % of the 0.35 m plateau depth

Water stored

· 0.48 % off

reported, not counted

Scored with method 3.0 · Score card: LISFLOOD-FP 8.3 FV1

Run it yourself

LISFLOOD-FP 8.3 FV1 · runs on Linux · produced by scripts/run_lisflood.py in open-solvers.yml.

git clone https://github.com/scott-jeffers/benchmark1d2d && cd benchmark1d2d
git checkout 71dc10fc07a9
# LISFLOOD-FP 8.3 source (Zenodo, MD5 abaa2e41b58f6c7df4443274bf130d4a), built CPU-only in double precision:
sudo apt-get install -y libnetcdf-dev libnuma-dev
cmake -S <lisflood>/source -B build -DCMAKE_BUILD_TYPE=Release && cmake --build build --target lisflood
python -m pip install -e ".[dev]"
python scripts/run_lisflood.py --exe build/lisflood --solver fv1 A2C-EA1

The model files the suite wrote for this run (.zip, 1.6 KB): the exact inputs the solver read (one folder per grid, where the test has several), with their SHA-256.

The test itself (inputs, exact answer, checks): A2C-EA1.zip. Check the score card with benchmark1d2d verify-card: its signature by the suite's public development key shows the card has not changed since it was written, not who wrote it.

Demo 2D

Worked example that ships with the suite: first-order finite volume

#2 0.44 % off

Run time, finest grid: 14.3 s · AMD EPYC 9V74 80-Core Processor, 2 cores, 15.6 GB, Linux 6.17.0-1022-azure (GitHub Actions (github-hosted, ubuntu24))

Pond level, point 1

• 0.95 mm off

0.38 % of the 0.25 m pond depth at P1

Pond level, point 2

• 0.95 mm off

0.38 % of the 0.25 m pond depth at P2

Peak level

• 1.5 mm off

0.44 % of the 0.35 m plateau depth

Water stored

· 0.53 % off

reported, not counted

Scored with method 3.0 · Score card: demo-swe2d (first-order FV, HLL + hydrostatic reconstruction)

Run it yourself

demo-swe2d (first-order FV, HLL + hydrostatic reconstruction) · version 0.1.0 · runs on any · produced by scripts/run_demo_2d.py in track-a.yml.

git clone https://github.com/scott-jeffers/benchmark1d2d && cd benchmark1d2d
git checkout 71dc10fc07a9
python -m pip install -e ".[dev]"
python scripts/run_demo_2d.py

The model files for this run will be published with its next run.

TELEMAC-2D

openTELEMAC-2D 9.1.1, run with its default finite-volume settings

#3 0.56 % off

Run time, finest grid: 59.5 s · AMD EPYC 7763 64-Core Processor, 2 cores, 15.6 GB, Linux 6.17.0-1022-azure (GitHub Actions (github-hosted, ubuntu24))

Settings: telemac2d (Selafin, nodes at the grid's cell centres)

Pond level, point 1

• 1.4 mm off

0.56 % of the 0.25 m pond depth at P1

Pond level, point 2

• 1.4 mm off

0.56 % of the 0.25 m pond depth at P2

Peak level

• 0.00045 mm off

<0.01 % of the 0.35 m plateau depth

Water stored

· 0.81 % off

reported, not counted

Scored with method 3.0 · Score card: openTELEMAC-2D v9.1.1

Run it yourself

openTELEMAC-2D v9.1.1 · runs on Linux · produced by scripts/run_telemac.py in track-a.yml.

git clone https://github.com/scott-jeffers/benchmark1d2d && cd benchmark1d2d
git checkout 71dc10fc07a9
python -m pip install -e ".[dev]"
conda create -n telemac -c conda-forge opentelemac=v9.1.1 python=3.12
python scripts/run_telemac.py --telemac-prefix "$(conda info --base)/envs/telemac" A2C-EA1

The model files the suite wrote for this run (.zip, 14 KB): the exact inputs the solver read (one folder per grid, where the test has several), with their SHA-256.

LISFLOOD-FP DG2

LISFLOOD-FP 8.3, second-order discontinuous Galerkin solver

#4 1.7 % off

Run time, finest grid: 18.1 s · AMD EPYC 7763 64-Core Processor, 2 cores, 15.6 GB, Linux 6.17.0-1022-azure (GitHub Actions (github-hosted, ubuntu24))

Settings: lisflood (dg2 solver, defaults; CPU, double precision)

Pond level, point 1

• 4.2 mm off

1.7 % of the 0.25 m pond depth at P1

Pond level, point 2

• 4.2 mm off

1.7 % of the 0.25 m pond depth at P2

Peak level

• 0.5 mm off

0.14 % of the 0.35 m plateau depth

Water stored

· 2.5 % off

reported, not counted

Scored with method 3.0 · Score card: LISFLOOD-FP 8.3 DG2

Run it yourself

LISFLOOD-FP 8.3 DG2 · runs on Linux · produced by scripts/run_lisflood.py in open-solvers.yml.

git clone https://github.com/scott-jeffers/benchmark1d2d && cd benchmark1d2d
git checkout 71dc10fc07a9
# LISFLOOD-FP 8.3 source (Zenodo, MD5 abaa2e41b58f6c7df4443274bf130d4a), built CPU-only in double precision:
sudo apt-get install -y libnetcdf-dev libnuma-dev
cmake -S <lisflood>/source -B build -DCMAKE_BUILD_TYPE=Release && cmake --build build --target lisflood
python -m pip install -e ".[dev]"
python scripts/run_lisflood.py --exe build/lisflood --solver dg2 A2C-EA1

The model files the suite wrote for this run (.zip, 2.4 KB): the exact inputs the solver read (one folder per grid, where the test has several), with their SHA-256.

ANUGA

ANUGA 4.0.1 (Geoscience Australia / ANU), default settings on a triangular mesh

#5= 1.9 % off

Run time, finest grid: 1.7 min · AMD EPYC 7763 64-Core Processor, 2 cores, 15.6 GB, Linux 6.17.0-1022-azure (GitHub Actions (github-hosted, ubuntu24))

Settings: anuga (rectangular_cross mesh, defaults, sampled at cell centres)

Pond level, point 1

• 4.8 mm off

1.9 % of the 0.25 m pond depth at P1

Pond level, point 2

• 4.8 mm off

1.9 % of the 0.25 m pond depth at P2

Peak level

• 0.0049 mm off

<0.01 % of the 0.35 m plateau depth

Water stored

· 2.6 % off

reported, not counted

Scored with method 3.0 · Score card: ANUGA 4.0.1

Run it yourself

ANUGA 4.0.1 · runs on Linux · produced by scripts/run_anuga.py in open-solvers.yml.

git clone https://github.com/scott-jeffers/benchmark1d2d && cd benchmark1d2d
git checkout 71dc10fc07a9
conda create -n anuga -c conda-forge anuga=4.0.1 python=3.12 pip scipy
conda activate anuga
python -m pip install -e ".[dev]"
python scripts/run_anuga.py A2C-EA1

The model files for this run will be published with its next run.

ANUGA builds its mesh and boundaries in Python: the script is the model.

LISFLOOD-FP ACC

LISFLOOD-FP 8.3, the local-inertia solver it is best known for; it leaves out the advection term

#5= 2.1 % off

Run time, finest grid: 3.4 s · AMD EPYC 7763 64-Core Processor, 2 cores, 15.6 GB, Linux 6.17.0-1022-azure (GitHub Actions (github-hosted, ubuntu24))

Settings: lisflood (acceleration solver, defaults; CPU, double precision)

Pond level, point 1

• 5.3 mm off

2.1 % of the 0.25 m pond depth at P1

Pond level, point 2

• 5.3 mm off

2.1 % of the 0.25 m pond depth at P2

Peak level

• 0.091 mm off

0.026 % of the 0.35 m plateau depth

Water stored

· 2.7 % off

reported, not counted

The pond settles 5 mm above the sill. The stored volume is 2.7 % above the figure integrated on the EA's 2 m DEM; that check does not gate, because a 10 m grid samples the ground differently.

Scored with method 3.0 · Score card: LISFLOOD-FP 8.3 ACC

Run it yourself

LISFLOOD-FP 8.3 ACC · runs on Linux · produced by scripts/run_lisflood.py in open-solvers.yml.

git clone https://github.com/scott-jeffers/benchmark1d2d && cd benchmark1d2d
git checkout 71dc10fc07a9
# LISFLOOD-FP 8.3 source (Zenodo, MD5 abaa2e41b58f6c7df4443274bf130d4a), built CPU-only in double precision:
sudo apt-get install -y libnetcdf-dev libnuma-dev
cmake -S <lisflood>/source -B build -DCMAKE_BUILD_TYPE=Release && cmake --build build --target lisflood
python -m pip install -e ".[dev]"
python scripts/run_lisflood.py --exe build/lisflood --solver acc A2C-EA1

The model files the suite wrote for this run (.zip, 1.7 KB): the exact inputs the solver read (one folder per grid, where the test has several), with their SHA-256.

HEC-RAS 7.0

HEC-RAS 7.0.1 2D with its Eulerian shallow-water option (SWE-EM), which HEC recommends for dam breaks

#7= 5.1 % off

Run time, finest grid: 23.5 s · AMD EPYC 7763 64-Core Processor, 2 cores, 16 GB, Windows 2025Server (GitHub Actions (github-hosted, win25-vs2026))

Settings: hecras 2D (headless terrain + seeded mesh + boundary lines, SWE-EM; depth = cell volume / area)

Pond level, point 1

• 1.3 cm off

5.1 % of the 0.25 m pond depth at P1

Pond level, point 2

• 1.3 cm off

5.1 % of the 0.25 m pond depth at P2

Peak level

• 0.05 mm off

0.014 % of the 0.35 m plateau depth

Water stored

· 6.2 % off

reported, not counted

Scored with method 3.0 · Score card: HEC-RAS 7.0.1 2D SWE-EM

Run it yourself

HEC-RAS 7.0.1 2D SWE-EM · runs on Windows · produced by scripts/run_hecras_2d_cases.py in hecras.yml.

git clone https://github.com/scott-jeffers/benchmark1d2d && cd benchmark1d2d
git checkout 71dc10fc07a9
# Windows: HEC-RAS 7.0.1 from HEC (HEC-RAS_701_Setup.exe, SHA-256 1FE76297…3CEE73), silent install /S /v/qn
python -m pip install -e ".[dev]" "ras-commander==0.106.1" h5py psutil pywin32 pillow pythonnet tifffile
python scripts/run_hecras_2d_cases.py A2C-EA1 --accept-hec-terms --equations em

The model files the suite wrote for this run (.zip, 161 KB): the exact inputs the solver read (one folder per grid, where the test has several), with their SHA-256.

HEC-RAS 6.6

HEC-RAS 6.6 2D with its Eulerian shallow-water option (SWE-EM), the release before 7.0

#7= 5.1 % off

Run time, finest grid: 26.0 s · AMD EPYC 7763 64-Core Processor, 2 cores, 16 GB, Windows 2025Server (GitHub Actions (github-hosted, win25-vs2026))

Settings: hecras 2D (headless terrain + seeded mesh + boundary lines, SWE-EM; depth = cell volume / area)

Pond level, point 1

• 1.3 cm off

5.1 % of the 0.25 m pond depth at P1

Pond level, point 2

• 1.3 cm off

5.1 % of the 0.25 m pond depth at P2

Peak level

• 0.051 mm off

0.015 % of the 0.35 m plateau depth

Water stored

· 6.2 % off

reported, not counted

Scored with method 3.0 · Score card: HEC-RAS 6.6 2D SWE-EM

Run it yourself

HEC-RAS 6.6 2D SWE-EM · runs on Windows · produced by scripts/run_hecras_2d_cases.py in hecras.yml.

git clone https://github.com/scott-jeffers/benchmark1d2d && cd benchmark1d2d
git checkout 71dc10fc07a9
# Windows: HEC-RAS 6.6 from HEC (HEC-RAS_66_Setup.exe, SHA-256 42A370B1…4715EB), silent install /S /v/qn
python -m pip install -e ".[dev]" "ras-commander==0.105.0" h5py psutil pywin32 pillow pythonnet tifffile
set HECRAS_TAG=66
python scripts/run_hecras_2d_cases.py A2C-EA1 --accept-hec-terms --equations em

The model files the suite wrote for this run (.zip, 139 KB): the exact inputs the solver read (one folder per grid, where the test has several), with their SHA-256.

HEC-RAS 7.0

HEC-RAS 7.0.1 (US Army Corps of Engineers), built and run headless with its default settings; in 2D, its default full shallow-water option (SWE-ELM)

#7= 5.1 % off

Run time, finest grid: 19.3 s · AMD EPYC 9V74 80-Core Processor, 2 cores, 16 GB, Windows 2025Server (GitHub Actions (github-hosted, win25-vs2026))

Settings: hecras 2D (headless terrain + seeded mesh + boundary lines, SWE-ELM; depth = cell volume / area)

Pond level, point 1

• 1.3 cm off

5.1 % of the 0.25 m pond depth at P1

Pond level, point 2

• 1.3 cm off

5.1 % of the 0.25 m pond depth at P2

Peak level

• 0.052 mm off

0.015 % of the 0.35 m plateau depth

Water stored

· 6.2 % off

reported, not counted

Scored with method 3.0 · Score card: HEC-RAS 7.0.1 2D SWE-ELM

Run it yourself

HEC-RAS 7.0.1 2D SWE-ELM · runs on Windows · produced by scripts/run_hecras_2d_cases.py in hecras.yml.

git clone https://github.com/scott-jeffers/benchmark1d2d && cd benchmark1d2d
git checkout 71dc10fc07a9
# Windows: HEC-RAS 7.0.1 from HEC (HEC-RAS_701_Setup.exe, SHA-256 1FE76297…3CEE73), silent install /S /v/qn
python -m pip install -e ".[dev]" "ras-commander==0.106.1" h5py psutil pywin32 pillow pythonnet tifffile
python scripts/run_hecras_2d_cases.py A2C-EA1 --accept-hec-terms --equations elm

The model files the suite wrote for this run (.zip, 161 KB): the exact inputs the solver read (one folder per grid, where the test has several), with their SHA-256.

HEC-RAS 6.6

HEC-RAS 6.6, the release before 7.0, run the same way (1D, and 2D with its default SWE-ELM): kept so a change between versions shows

#7= 5.1 % off

Run time, finest grid: 37.7 s · AMD EPYC 7763 64-Core Processor, 2 cores, 16 GB, Windows 2025Server (GitHub Actions (github-hosted, win25-vs2026))

Settings: hecras 2D (headless terrain + seeded mesh + boundary lines, SWE-ELM; depth = cell volume / area)

Pond level, point 1

• 1.3 cm off

5.1 % of the 0.25 m pond depth at P1

Pond level, point 2

• 1.3 cm off

5.1 % of the 0.25 m pond depth at P2

Peak level

• 0.052 mm off

0.015 % of the 0.35 m plateau depth

Water stored

· 6.2 % off

reported, not counted

Run on the EA's own 2 m DEM, which HEC-RAS uses as sub-grid terrain. The pond settles 1.3 cm above the sill.

Scored with method 3.0 · Score card: HEC-RAS 6.6 2D SWE-ELM

Run it yourself

HEC-RAS 6.6 2D SWE-ELM · runs on Windows · produced by scripts/run_hecras_2d_cases.py in hecras.yml.

git clone https://github.com/scott-jeffers/benchmark1d2d && cd benchmark1d2d
git checkout 71dc10fc07a9
# Windows: HEC-RAS 6.6 from HEC (HEC-RAS_66_Setup.exe, SHA-256 42A370B1…4715EB), silent install /S /v/qn
python -m pip install -e ".[dev]" "ras-commander==0.105.0" h5py psutil pywin32 pillow pythonnet tifffile
set HECRAS_TAG=66
python scripts/run_hecras_2d_cases.py A2C-EA1 --accept-hec-terms --equations elm

The model files the suite wrote for this run (.zip, 139 KB): the exact inputs the solver read (one folder per grid, where the test has several), with their SHA-256.

Not run yet: GeoClaw, TUFLOW, MIKE 21, Iber, BASEMENT, Delft3D FM

Run it and add yours →

Status of this test

Candidate. To become frozen it needs: maintainer review recorded.

Download inputs (.zip)Cite this test View on GitHub

Technical details for reviewers Checks, reference, inputs, sources

Checks and why each limit was chosen

Check	Difference measured as a percentage of	Latest	Why this check
final_level_p1 expected_state_error of h · in the score	of the 0.25 m pond depth at P1	–	A solver that conserves mass and handles the sill must leave the pond at the crest level; 2 cm allows for slow drainage over the sill by t = 20 h.
final_level_p2 expected_state_error of h · in the score	of the 0.25 m pond depth at P2	–	Same pond as P1, so it must settle at the same 10.25 m crest level; a second point catches a solver that leaves the pond tilted or partly drained.
peak_level expected_state_error of h · in the score	of the 0.35 m plateau depth	–	Hydrostatic plateau level during the 10 h hold.
final_volume expected_state_error of volume · reported, not counted	already a percentage	–	Informational: depends on how the solver samples the 2 m DEM onto its own grid.

Reference

No exact or measured answer exists. The test is scored on states that follow from the inputs alone; published package results are context only.

Expected state	Value	Why it must hold
pond_final_level_p1 h+z at P1	10.25 m	Specification §2: after the boundary falls the pond becomes horizontal at the sill elevation, 10.25 m (sill crest at x = 300 m in the DEM).
pond_final_level_p2 h+z at P2	10.25 m	As P1; both points lie in the same pond.
peak_level h+z at P1,P2	10.35 m	Boundary holds 10.35 m for 10 h (60–660 min), long enough for the whole domain to become horizontal (specification §2).
final_stored_volume volume	9,954 m3	Pond below 10.25 m (9887.3 m³) plus water below 9.7 m elsewhere (66.9 m³), integrated on the 2 m EA DEM. Solvers on a 10 m grid sample the DEM differently, so this check does not gate.

More figures

Gaps are times when the cell at that point is dry.

Promotion checklist

Only frozen tests have fixed inputs and answers. This list is computed from the manifest and the published score cards; the rules are in the method.

✓Data licence verifiedfor candidateOGL-UK-3.0
✓All inputs availablefor candidateall committed or fetched by SHA-256
✓Reference (truth) availablefor candidateobjective expected states
✓Every tolerance justifiedfor candidateeach gating criterion has a rationale
✓A published run passesfor frozen10 passing score card(s)
✓Order of accuracy shownfor frozennot a verification case
✓Two independent codes passfor frozenpassing codes: ANUGA 4.0.1, HEC-RAS 6.6 2D SWE-ELM, HEC-RAS 6.6 2D SWE-EM, HEC-RAS 7.0.1 2D SWE-ELM, HEC-RAS 7.0.1 2D SWE-EM, LISFLOOD-FP 8.3 ACC, LISFLOOD-FP 8.3 DG2, LISFLOOD-FP 8.3 FV1, demo-swe2d, openTELEMAC-2D v9.1.1
✗Maintainer review recordedfor frozenno maintainer review recorded

Inputs

File	Role	Format	SHA-256	Get it
`inputs/terrain.asc`	terrain	esri_ascii_grid	`96dc6541a3e5…`	Fetched by hash from source
`inputs/boundary_level.csv`	boundary_condition	csv	`c0a001dd8971…`	Download
`inputs/output_points.csv`	probes	csv	`6b89f16db52d…`	Download
`inputs/case.json`	case_parameters	json	`70b96e6d913a…`	Download

About this test

Parameter	Value
Manning's n	0.03
Grid	10 m (DEM 2 m)
Run time	20 h
Initial level	9.7 m
Settled pond volume	9,887 m³

Data and licence

Inputs come from the GOV.UK 'Benchmarking model data' archive, published under the Open Government Licence v3.0 (the page licence; the archive carries no other terms). Attribution: Environment Agency, SC120002 (2013), test specifications May 2010.

Archive: https://assets.publishing.service.gov.uk/media/6033a9bbd3bf7f72182e99ca/Benchmarking_Model_Data.zip (SHA-256 388c2789570e5975fe909033e34bedbe5d7bde5e6d7f9b7d7c1eaf04e58bc732)
Landing page: https://www.gov.uk/flood-and-coastal-erosion-risk-management-research-reports/2d-benchmarking-evaluating-the-latest-generation-of-the-hydraulic-models-for-fcrm
Report: https://assets.publishing.service.gov.uk/media/6033a943d3bf7f721f4b0d49/_SC120002_Benchmarking_2D_hydraulic_models_Report.pdf

Fetch the non-committed inputs with python scripts/fetch_inputs.py A2C-EA1.

Sources

Néelz, S., Pender, G. (2013). Benchmarking the Latest Generation of 2D Hydraulic Modelling Packages. SC120002. www.gov.uk/flood-and-coastal-erosion-risk-management-researc
Néelz, S., Pender, G. (2010). Benchmarking of 2D Hydraulic Modelling Packages. SC080035/SR2. assets.publishing.service.gov.uk/media/5a75765c40f0b6360e474

Test A2C-EA1_disconnected_water_body · version 1.0.0 · data licence OGL-UK-3.0