Presentation by Melissa Latella, Polytechnic University of Turin, Italy, at the Delft3D - User Days (Day 4: Water quality and ecology), during Delft Software Days - Edition 2019. Thursday, 14 November 2019, Delft.

1. Delft, November 14th 2019
Ecomorphodynamic applications
of Delft3D Flexible Mesh
Melissa Latella, Fabio Sola, Carlo Camporeale
Envirofluidgroup - Department of Environment, Land and Infrastructure Engineering - Polytechnic of Turin, Italy
melissa.latella@polito.it

2. Ecomorphodynamics
How different processes shape the riparian environment
Latella, Sola, & Camporeale Delft, November 14th 2019 1
Flow variability
Sediment
transport
Vegetation
dynamics

3. Delft3D Flexible Mesh for morphodynamic applications
Key functionalities and potential uses
Latella, Sola, & Camporeale Delft, November 14th 2019 2
• Flexibile mesh to describe river sinuosity and obstacles in the floodplain
• Trachytopes to simulate the contribution of vegetation to local roughness
• Simulation over both steady and evolving morphology
➢ Calibration of theoretical models (Case Study 1)
➢ Design of interventions for river restoration (Case Study 2)

4. Case Study 1
Study site & field activities
Latella, Sola, & Camporeale Delft, November 14th 2019 3
Sediment sampling
Tree measurements

5. Case Study 1
Study site & field activities
Latella, Sola, & Camporeale Delft, November 14th 2019 4
Allometric relations & vegetation biomass
Phase 1: Processing LiDAR data for vegetation height statistics
Phase 2-3: Field-based measurements and biomass computation
Phase 1: Wolman Pebble Count
Phase 3: d50, d90 computation
Δpi = (weight of fraction i)/(weight of
total sample);
Δqi = (number of pebbles in fraction
i)/(total amount of pebbles);
dmi = mean diameter of fraction i.
Phase 4: Manning computation
Phase 2: BaseGrain processing
Grain distribution & Manning coefficient

6. Flexible mesh:
- High resolution curvilinear grid for the main channel
good representation of the bathymetry
- Triangular grid with varying resolution for bars
resolution can be increased on the most relevant
areas and coarsened elsewhere
lower computational time
Latella, Sola, & Camporeale Delft, November 14th 2019 5
Grid generation
Traditional grid:
- Similar grid resolution throughout the whole domain
- Cells not always aligned with flow direction
- Not realistic representation of boundaries
Case Study 1
Delft3D FM for the computation of the site-dependent probability of inundation

7. Latella, Sola, & Camporeale Delft, November 14th 2019 6
Trachytopes
Phase 2: Areas with homogenous vegetation (QGIS)
Bed and bare soil
Phase 1: Vegetation height from LiDAR data (FUSION/LDV)
Phase 3: Definition of .arl and .ttd input file for Delft3D
Vegetated areas
Case Study 1
Delft3D FM for the computation of the site-dependent probability of inundation

8. Latella, Sola, & Camporeale Delft, November 14th 2019 7
Hydrodynamic simulations and Probability of inundation
Case Study 1
Delft3D FM for the computation of the site-dependent probability of inundation

9. Case Study 1
Calibration of a stochastic model for riparian vegetation dynamics
Latella, Sola, & Camporeale Delft, November 14th 2019 8
Stochastic model and calibration strategy
𝑑ν
𝑑𝑡
= 𝜈 𝑚
(𝛽 − 𝜈) 𝑝
, ℎ < η
𝑑ν
𝑑𝑡
= −𝛼𝜈 𝑛
, ℎ ≥ η
η topographic level
N normalization constant
τ integral scale of the process
Pi probability of inundation
Camporeale & Ridolfi, 2006
ν vegetation biomass
α decay factor
β carrying capacity
m,n,p vegetation parameters
h water level
𝑝 ν =
𝑁
α
ν
𝛽 1−ατ − 𝛼+𝛽 𝑃 𝐼
αβτ 𝛽 − 𝜈
𝑃 𝐼
βτ
−1
(α + β − ν)
Biomass estimation LiDAR
and field-based relationships
Delft3D FM
Calibration through least square minimization
between real and computed pdfs

10. Case Study 1
Calibration of a stochastic model for riparian vegetation dynamics
Latella, Sola, & Camporeale Delft, November 14th 2019 9
Stochastic model and calibration strategy
ν vegetation biomass
η topographic level
Pi probability of inundation
k decay rate
β carrying capacity
Optimised pdfs Calibrated parameters

11. Case Study 1
Calibration of a stochastic model for riparian vegetation dynamics
Latella, Sola, & Camporeale Delft, November 14th 2019 10
Results and uses
Real biomass first moment Computed first moment
First moment for a
40% flow rate reduction

12. Case Study 2
Study site & intervention areas
Latella, Sola, & Camporeale Delft, November 14th 2019 11
1
2

13. Latella, Sola, & Camporeale Delft, November 14th 2019 12
Curvilinear
~ 20x30 m
Curvilinear
~ 2x5 m
Triangular
Case Study 2
Flexible mesh

14. Latella, Sola, & Camporeale Delft, November 14th 2019 13
River surveyor boat
Drone
Rectangularization
Rectangularization
Case Study 2
LiDAR ground points & bathymetry

15. Latella, Sola, & Camporeale Delft, November 14th 2019 14
Cloud Raster
Case Study 2
Vegetation & Trachytopes

16. Case Study 2
Delft3D - Vegetation
Latella, Sola, & Camporeale Delft, November 14th 2019 15

17. Latella, Sola, & Camporeale Delft, November 14th 2019 16
Flow rate: 582 m³/s
Return time: 2 years
Highway
Intense bank
erosion
Case Study 2
Intervention area 1

18. Latella, Sola, & Camporeale Delft, November 14th 2019 17
Depth Velocity
Case Study 2
Intervention area 1: Flow rate 582 m³/s , Return time 2 years

19. Latella, Sola, & Camporeale Delft, November 14th 2019 18
Bank
erosion
Case Study 2
Intervention area 2
Flow rate: 582 m³/s
Return time: 2 years

20. Latella, Sola, & Camporeale Delft, November 14th 2019 19
Case Study 2
Intervention area 2: Flow rate 582 m³/s , Return time 2 years
Depth Velocity

21. Delft3D Flexible Mesh for morphodynamic applications
Conclusions & Future steps
Latella, Sola, & Camporeale Delft, November 14th 2019 20
• Delft3D FM can be a useful tool to study ecomorphodynamic processes
• It can be applied to the calibration of theoretical models
• It can be applied to the design of real interventions
➢ Adding of morphological evolution for the Case Study 2
➢ Implementation of the dynamic vegetation module

22. Delft, November 14th 2019
Thanks for your attention
Melissa Latella, Fabio Sola, Carlo Camporeale
Envirofluidgroup - Department of Environment, Land and Infrastructure Engineering - Polytechnic of Turin, Italy
melissa.latella@polito.it