DSD-INT 2019 Benchmarking Models for River-Sea System Studies-Bellafiore

Benchmarking Models
for River-Sea System Studies
Debora Bellafiore
CNR-ISMAR

08/11/2019Delft Software Days
Rationale
⚫ Overview of the modelling tools for RS systems – Problems and challenges
⚫ Modelling capability of DANUBIUS
⚫ Set up of preliminary criteria for modelling RS systems
⚫ Building a strategy for benchmarking
⚫ Organization
⚫ Benchmark criteria
⚫ Uncertainty estimation and sources of uncertainties
⚫ Quality control

Why River-Sea Systems are so important – why to
model them?
RIVER-ESTUARIES
RIVER-DELTAS
CULTURAL HERITAGE
INDUSTRIAL
INFRASTRUTURE
ENERGY
GEO-HAZARDS
HABITAT PRESSURES
NAVIGATION
DAMS
POLLUTION
RECREATION
FISHING
FLOODING
DROUGHT
CATCHMENT
CHANGE

mountains
Drainage Basin
sea
tributaries
estuary
ground water
Catchment Urban
area
Towards a transboundary and transdisciplinary approach
Covering the whole geographical domain, from source to transitional areas and sea.
River-sea systems comprise whole river basins and coastal seas and can be understood only
by considering them as complex but integrated systems.
The system as a continuum
Overview on the modelling tools for RS
systems – problems and challenges

Modelling capability of DANUBIUS
The community is composed by:
• Model developers
• Contributors
• Users
• Possible stakeholders
We made a survey to define the full range of
skills, the possible available tools, the open
issues connected with benchmarking and
some draft guidelines
to be elaborated more but
that can lead to the delivery
of commons connected with
Modelling

Models used by the community

10

Suite of modules, full model, not just highly specialized modules

SHYFEM Model
3D Finite element hydrodynamic model, staggered for the spatial integration.
3D shallow water hydrodynamic model, coupled with a wind wave model and with both
an Eulerian and a Lagrangian module, for simulating active tracers transport and
diffusion.
External modules:
Sediment Transport SEDTRANS
Ecological module EUTRO-WASP
Biogeochemical module BFM
Wave module WWMII
Turbulence closure module GOTM
been already and successfully applied
to several transitional and coastal environments

SCHISMSemi-implicit Cross-scale Hydroscience Integrated System Model for
creek-lake-river-estuary-shelf-ocean
simulations
⚫ Open-source community-supported modeling system
⚫ Using unstructured grids, designed for seamless
simulation of 3D baroclinic circulation
⚫ semi-implicit finite-element/finite-volume method with
Eulerian-Lagrangian algorithm
⚫ Hybrid SZ coordinates or new LSC2 in the vertical
dimension
⚫ Natural treatment of wetting and drying suitable for
inundation studies
⚫ Mass conservative, monotone, higher-order transport
solver: TVD2; WENO

Delft3D Flexible Mesh Suite
- Integrated 1D-2D-3D computational core for hydrodynamics on the basis of
flexible meshes
- Modules for waves, morphology, water quality
- Worldwide applications:
- Rhine river and delta
- North Sea, Wadden Sea, San Francisco Bay, …
- Global Storm Surge Model
https://www.deltares.nl/en/software/delft3d-flexible-mesh-suite/

TELEMAC-MASCARET (in a nutshell)
• Integrated “solver suite” for free surface flow,
unstructured triangular mesh finite element or finite
volume model.
• Open source, managed and developed by the
European Telemac-Mascaret Consortium (Artelia (F),
BAW (D), CEREMA (F), CETMEF (F), Daresbury (UK),
EDF (F), HRW (UK)) (opentelemac.org).
MASCARET: One-dimensional flows
TELEMAC-2D: Two-dimensional flows - Saint-Venant
equations (including transport of a diluted tracer)
TELEMAC-3D: Three-dimensional flows - Navier-Stokes
equations (including transport of active or passive tracers
and suspended sediment transport)
TOMAWAC: Wave propagation in the coastal zone
ARTEMIS: Wave agitation in harbours
SISYPHE and GAIA: 2D suspended and bed load sediment
transport, NESTOR: Simulation of dredging operations,
WAQTEL: water quality modelling, KHIONE: ice modelling
⚫ Telemac-3D simulation of scalar velocity in the River Rhine,
Jungferngrund (Rhine-km 548,5 - 556,5)
BAW
SISYPHE: 2D simulation of bed-load discharge in the River Rhine,
Düsseldorfer Bögen (Rhine-km 741-745)

Set up of preliminary criteria for modelling RS
systems
Codes must be open source:
⚫ Models that are a suite of modules are privileged, because of their modularity, wide
range of interdisciplinary implementations, degree of standardization.
⚫ Core model software developers should be part of DANUBIUS-RI, providing the
opportunity to directly act on the codes for development, updates, upgrades.
⚫ The models that are well-known, widely applied and that collect large groups of users
should be privileged, since they increase the critical mass, introducing internal practice
of benchmarking and large and shared knowledge about implementations in RSS.
⚫ The morphological complexity of RSS systems requires modelling tools able to resolve
properly both large and small scale structures/features, therefore unstructured grid
models are privileged.

Building a strategy for benchmarking
Organization
⚫ The success of a benchmark initiative depends on the collection of information that is
needed for the purpose of the benchmark.
⚫ The benchmark criteria and the methodology should be clear and accepted by the
parties involved.
⚫ The information about each model should be as complete as possible, in a format that
makes comparison between the models easy.
⚫ If software documentation is insufficient, the information should be collected from or
confirmed by the original developers.
⚫ Functional and non-functional performance criteria should be well defined and applied
consequently for all models in the benchmark.
⚫ Developers of the modelling systems should get ample time to respond to the findings of
the benchmark.
⚫ For sake of transparency, the outcome of the benchmark should be communicated with a
wide audience.

Example Inundation Modelling (NL)
⚫ Pluvial flooding events in The Netherlands urged the regional water
authorities to analyse the bottlenecks in the drainage systems.
⚫ In 2017, a benchmark study was carried out with ten different model codes.
⚫ In the process, water authorities, engineering firms, modellers and software
developers were involved

⚫ Completeness of the model code, which was determined by making an
extensive inventory of the functionalities of the model codes.
⚫ Accuracy of the model code, determined by the simulation of seven
representative situations with each model code.

⚫ The benchmark focused on:
• Surface water (1D or 2D)
• Sewer systems (1D)
• 2D overland flow (inundation and/or rainfall runoff)

Benchmark criteria
Define the
objectives of the
model study
Clarify the
spatial and
temporal
scale
Framework of the modelling
implementation components
Classify the model
confidence level
Benchmark
tests
Methodology
for quantifying
models’
uncertainties
Answer the
question:
uncertainties
quantified are
acceptable?
• Available data
• Cal procedures
• Cal-Implementation consistency
• Model setup
• Cal/val approaches
• Sensitivity and uncertainty analyses

Benchmark criteria
Theme Modelling Tool Test Relevant input Target variables
Storm surge 2D hydrodynamic model -reproduce tide gauge data
corresponding to a surge event;
-wind and atmospheric pressure
(frequency > 3h);
-tidal signal (frequency > 3h);
bathymetry
Water level
Flooding/
Drought/
Compound
floods
2D hydrodynamic model -mass conservation in box with
bathymetry comprising wet and
dry areas;
- Reproduce water levels and
spatial flooding patterns
Bathymetry;
Freshwater + lateral water sources;
Meteomarine forcings;
Surface water exchange (mass –
precipitation-evaporation)
-water levels;
-flooded
areas/volumes
(spatial, temporal
evolution);
-water volumes;
Salt Water
Intrusion/
transport
3D hydrodynamic
baroclinic model
reproduce salinity concentrations
in 3D
-cross-sectional volume flux
-river discharge
-salinity and temperature (sea-river)
-bathymetry
-3D salinity (halocline)
Navigation
(inland)
2D / 3D hydrodynamic
model
-reproduce longitudinal and
transversal flow velocities
-river discharge -flow velocity
River training 2D / 3D hydrodynamic
model
-reproduce longitudinal water
level fixing
-reproduce cross-section velocity
profiles
-river discharge -water level
-flow velocity

Benchmark criteria
Theme Modelling Tool Test Relevant input Target variables
Sediment Balance/
Transport/Erosion-
Deposition
(rivers)
-2D / 3D hydrodynamic
model
-morphodynamic model
-reproduce transport
rates
-reproduce bottom
evolution
-river discharge
-sediment transport
-bathymetry
-Bathymetry
-Bottom evolution
-erosion/deposition
patterns
Morphological evolution
(rivers)
-2D / 3D hydrodynamic
model
-morphodynamic model
-secondary currents
-reproduce
meandering
-river discharge
-sediment transport
-bathymetry
-Bathymetry
-Bottom evolution
-erosion/deposition
patterns
Pollutants -2D/3D coupled pollutants-
hydrodynamic model
-standalone pollutant
model
--reproduce pollutant
concentrations
-river, atmospheric, industrial,
urban, direct point discharges
-pollutant concentration,
pollutant transformation
fluxes
Nutrients 2D/3D coupled pollutants-
hydrodynamic model
-standalone pollutant
model
--reproduce nutrient
concentrations
-river, atmospheric, industrial,
urban, direct point discharges
-nutrient concentration,
pollutant transformation
fluxes
Oil Spill offline coupling to 2D-3D
hydrodynamic fields
-reproduce weathering
curves and transport
patterns
2D-3D hydrodynamic fields, 2D
wind fields
-oil thickness, oil volume
Connectivity offline coupling to 2D-3D
hydrodynamic fields
-reproduce transport
patterns, comparison
with genetic variability
(for biological species)
2D-3D hydrodynamic fields, 2D
wind fields
-convergence or
dispersal density

Uncertainty estimation and sources of uncertainties
Performance Measures
Sensitivity Analysis
Acceptance range
Quantify the impact of uncertainties
on decision makingon performance measures
Define the most relevant variables
describing the object of the study
Quantify the relative impact on model outputs due to model
setup, in terms of parameter tuning.
Identify a range for the setup of the identified
parameters, in order to obtain acceptable model results
Provide an empirical probability
distribution based on the above-
mentioned protocol, for each relevant
parameter
Define how much relevant these
uncertainties are in the use of model
results for decision making actions.

Sources of uncertainties can be connected to:
⚫ Input data uncertainties, in boundary and initial conditions.
⚫ Structural uncertainties in physical representation in model codes.
⚫ Numerical errors in model algorithms, approximations in the numerical
schemes used.
⚫ Errors in the choice of parameterizations.

⚫ Model performances are evaluated through statistics on goodness of fit
(GFI), computing:
⚫ The root mean square error (RMSE).
⚫ The bias.
⚫ The Pearson product-moment correlation coefficient.
⚫ The slope, γ, providing evaluation of model over- or under-estimation.

Building a strategy for benchmarking Quality
control
⚫ Quality control procedures through DANUBIUS Data Centre Portal for
modelled data flows.
⚫ Use of artificial intelligence algorithms for quality check
⚫ increase the autonomy of automatic procedures over time, ensuring the
consistency and regularity of the data to be stored.
⚫ Quality control for data and metadata (data-related information)
⚫ e-signature to assure quality control

How to proceed?
⚫ Increasing the critical mass dealing with modelling activities in RSS is the
way to enforce benchmark initiatives and identify the major aspects of
interest for these specific environments.
⚫ The DANUBIUS Modelling Node can be the room for interaction.
www.danubius-pp.eu
www.danubius-ri.eu

DSD-INT 2019 Benchmarking Models for River-Sea System Studies-Bellafiore

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