Master's Thesis Presentation Presented by: Alireza Babaee Maryam Izadifar Presented for MSc "Civil Engineering for Risk Mitigation" in Dec. 2015 Supervisors: Prof. Alessio Radice Prof. Scira Menoni

1. Maryam Izadifar, Alireza Babaee
M.Sc. Civil Engineering for Risk Mitigation
Dec. 2015
Hazard Modelling and Risk Assessment for
Urban Flood Scenario
Supervisor:
Professor Alessio Radice
Co-supervisor:
Professor Scira Menoni

2. Introduction
Flood Event in 1987:
• Sondrio was not flooded
• River channel was almost full (sediment aggradation)
• Peak discharge in river = 500 m3/ s
• Aggradation of up to 5 m at the Garibaldi Bridge
Garibaldi Bridge
• Return period = 60 years
• Flood duration = 60 hours

3. Methodology (Integrated Study)
Geological
Assessment
Hydrology
River
Modelling
(1D)
Sediment yield Urban Flood
Modelling
(2D)
Outflow
hydrograph
River flood hydrograph
Risk
Assessment
Flood extension,
depth, velocity
Modelling Validation
“Idealised City”
Experimental Test Data vs 2D Modelling
Case Study: Town Sondrio
Flood Scenario:
• Peak discharge in river = 640 m3/s
• Return period = 100 years

4. Idealised City (Experimental Test)
• Université Catholique de Louvain (Belgium)
• Part of the European FLOODsite project
• Sudden transient flow of the dam-break wave
• A square city layout of 5 × 5 buildings aligned
with the approach of flow. Impervious blocks of
0.30 × 0.30 m; the streets were 0.10 m wide
• Validation of Modelling Procedure and
Parameters (Mesh size, Roughness,
Groundwater parameters)
• Validation of the Software (River2D)
• Uncertainties (Sensitivity Analyses in: Mesh
size, groundwater parameters and roughness)
What is Idealised City? Why We Used Idealised City Data?

5. Idealised City (Experimental Data)
4 sec
5 sec
6 sec
10 sec
Water Depth Water Velocity Recordings in 16 points along the
second longitudinal street
Data were recorded using water-level gauges and digital-imaging technique

6. Idealised City (Modelling Procedure)
River2D package:
1- Geometry Development in R2D_Bed
2- Mesh Generation in R2D_Mesh
3- Hydraulic Modelling in River2D
Model geometry
Adding Blocks
R2D_Bed:
R2D_Mesh:
4 Sizes  Sensitivity Analysis
River2D:
16 Monitoring Points
River2D:
• Two-dimensional modelling
• Depth averaged SWE

7. Idealised City (Sensitivity Analysis for Mesh Size)
Two strategies:
1) Fine mesh everywhere in the model
2) Coarse mesh in the model with refinement in building block position
3.6 m
8 m
1 m
Mesh size 70 cm with refinement in blocks

8. Sensitivity Analysis for the Mesh Size:
4 sec
5 sec
6 sec
10 sec
6 sec
10 sec
Graphical results for mesh size 70 cm with refinement in blocks
- The Most Compatible Results
- Fastest Wave Front
The Largest Mesh Size:
Idealised City (Sensitivity Analysis for Mesh Size)

9. Groundwater Parameters in River2D:
 Storativity (related to the volume needed to saturate the ground)
 Tranmissivity (related to permeability and the ability to convey discharge)
Model 1: Storativity = 1, Transmissivity = 1;
Model 2: Storativity = 0.001, Transmissivity = 1;
Model 3: Storativity = 1, Transmissivity = 0.1;
Model 4: Storativity = 0.001, Transmissivity = 0.1.
Graphical results after 10 seconds of modelling
Model 1
Model 2
Model 3
Model 4 Fastest Wave Front
Idealised City (Sensitivity Analysis for Groundwater Parameters)

10. Faster Wave Front
Idealised City (Sensitivity Analysis for Roughness)

11. Idealised City (Conclusion)
Validation of River2D modelling procedure:
 we can trust its results with approximation in the case study (Sondrio)
 difference is the size of two models affecting the size of mesh
Mesh size:
 the larger the mesh size, the more accurate the results  there is a limit for mesh size
 rational ratio between the mesh size and the size of blocks and streets
Groundwater parameters:
 the smaller the values, the more compatible the results
 no groundwater interaction in Idealised City (flume was sealed)
Roughness:
 the lower the roughness, the higher the water velocity and the lower the water depth
 expectable results

12. Hazard Modelling for the Scenario
Input Data (100-year Flood Scenario)
Inflow Hydrograph – 8 hours
Mallero basin and its position in Italy and Lombardia region
Inflow Hydrograph – 34 hours
adapted from previous studies (2014)
Mallero river in Sondrio
Flood Scenario:
Return period =
100 years
Peak discharge =
117 m3/ s

13. Hazard Modelling for the Scenario
Input Data (Bed Generation)
Aerial view of Sondrio including buildings
Ground
level
(a.s.l)
Garibaldi
Bridge
36 Monitoring Points
Simplified geometry for
urban blocks and streets
Sondrio River2D model including building blocks
Model dimensions and bed elevation variation

14. Hazard Modelling for the Scenario
Input Data (Monitoring Routes)
Three monitoring routes in order to better understanding of water propagation
Via Alessi
Via Parolo
Via Parolo
Via Caimi
Via Caimi
Via Caimi
Corso Vittorio Veneto
Corso Vittorio Veneto
Piazzale Giovanni Bertacchi

15. Hazard Modelling for the Scenario
Sensitivity Analyses (Mesh Size)
Sensitivity Analysis for Mesh Size: 20-40-60-80-100-120 (Q=117 m3/s , Ks=0.3 m)
slow water propagation
not realistic water propagation
acceptable result
acceptable result
acceptable result acceptable result

16. Hazard Modelling for the Scenario
Sensitivity Analyses (Roughness)
(Mesh Size=80 m , Peak Discharge =117 m3/s)
Differences in water depth for roughness height (Ks) 0.3 m
and 2 m in 480 min after flood
Differences in water depth for roughness height (Ks)
0.3 m and 2 m at Point No. 1

17. Hazard Modelling for the Scenario
Hazard Map
Qualitative Results: Quantitative Results:
Max Recorded Water Depth and Velocity in 36 Monitoring Points
Water Depth (m)
Water Velocity (m/s)
Compromise
between
qualitative and
quantitative
results
Hazard Map

18. Hazard Modelling for the Scenario
Hazard Map
ArcGIS  Flood extension
Water depth intervals (m):
(0 ˂ h ≤ 0.5), (0.5 ˂ h ≤ 1.5), (1.5 ˂ h ≤ 2)

19. Flood Risk Assessment
Sondrio Damage Assessment Steps (Buildings)
Steps:
• The depth of flooding is determined using the
flood hazard map
• Simplified USACE damage curve
• Categorize buildings based on the number of
building storey and presence of basement.
(Site visit, Google Street View, previous damage study
for 50 buildings in town Sondrio)
 Estimate the potential damage
(Micro-Scale, Direct, Tangible)
 According to a significant shift from hazard
centered perspective to understanding of risk
there is a need to quantify flood risk in terms
of damage.

20. Flood Risk Assessment
Sondrio Damage Assessment Map (Buildings)
Damage Levels:
• Very High (50 % ≤ Damage rate)
• High (40 % ≤ Damage rate < 50 %)
• Moderate (25 % ≤ Damage rate < 40 %)
• Low (Damage rate < 25 %)
• No expected damage (out of flood extension zone)
Grand Hotel Della Posta in Piazza Garibaldi
Multi-storey with basement
Residential building
Multi-storey without basement
Sport Facility
One- storey without basement
Railway Station
Multi-storey with basement
Damage rate in 4 levels assigned according to building type and the level of hazard

21. Scenario (Limitations, Suggestions)
 Improve geometry of the model
 Scenario of flood in the west part of the city
can be considered
 Explore other kind of software packages
 Detailed study of uncertainties (roughness,
groundwater interaction, upstream
hydrograph, inflow location, etc.)
Hazard Modelling: Damage Assessment:
 Lack of reliable data
 Finding appropriate damage model for case study
 Limited transferability of damage curves designed
for one geographic area to another area
 Uncertainty in damage curve estimation is high
 Flood damage depends, in addition to building type
and water depth, on many other factors (building
age, material, foundation type…, flow velocity,
duration of inundation, contamination…)
 Different urban patterns and building typologies
that are typical of Italy make it difficult to
generalize damage functions or to obtain large
enough data sets

22. Thank You For Yours Attention
Hazard Modelling and Risk Assessment
for Urban Flood Scenario