Presentation by Philip Ward (Deltares and IVM VU Amsterdam) at the Climate Adaptation Symposium 2023, during the Delft Software Days - Edition 2023 (DSD-INT 2023). Wednesday, 29 November 2023, Delft.

1. The MYRIAD-EU project has received funding from the European
Union’s Horizon 2020 research and innovation programme call H2020-
LC-CLA-2018-2019-2020 under grant agreement number 101003276
Approaches for assessing
multi-hazard risk
Philip Ward (Deltares and IVM VU Amsterdam)
Judith Claassen (IVM VU Amsterdam)

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Multi-Hazard Interrelationship
Triggering
Amplification
Compound
Consecutive

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Triggering Amplification Compound Consecutive
Meteorological Climatological Geophysical Hydrological Biological

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Why is This Important?
Consecutive
Triggering
Amplification

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Multiple hazards can have interrelated effects on risk
Triggering Amplifying
Compound Consecutive
How can risk be better managed by considering these
interrelated effects?

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DRM measures for one hazard may increase risk
(asynergies) from other hazards
How can we better account for these dynamic feedbacks
between risk drivers?

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Interrelated effects have impacts across sectors
How can we better account for these trade-offs and
synergies across sectors, regions, and hazards?

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MYRIAD-EU: Vision and aim
● Vision: to catalyse the paradigm shift required to move
towards a multi-risk, multi-sector, systemic approach to
risk assessment and management.
● Aim: by the end of MYRIAD-EU policy-makers, decision-
makers, and practitioners will be able to develop forward-
looking disaster risk management pathways that assess
trade-offs and synergies across sectors, hazards, and
scales

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MYRIAD-EU Pilots

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Framework development

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DAPP-MR (DAPP-Multi-Risks)

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MYRIAD-HESA: global multi-hazard dataset

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Space
Time

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Start day End day
Duration
Hazard
Footprint

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Hazard 4
Start day End day
Hazard 1
Hazard 2
Hazard 3
Hazard 4
Time Longitude
Latitude
Hazard 2
Hazard 3
Event 1
Event 1
Event 2
Event 2
Hazard 1
MYRIAD-HESA: MYRIAD – Hazard Event Sets
Algorithm

19. Earthquake
1. Define the outer
bound where the
MMI is at least five
1. Final polygon:
taken directly from
The Global Flood
Database
Volcanic Eruption
1. Coordinates of
volcanic eruption
and VEI
2. Calculate radius
of influence
𝐿 = 3.0408𝑒0.6956𝑉𝐸𝐼
3. Final polygon
Landslides
1. Does the provided
polygon from the database
have a high accuracy?
yes 2. Final polygon: polygon is
used as provided
no 2. Final polygon: polygon is
estimated based on coordinates
of occurrence and fixed radius
Tropical Cyclone
1. Wind field from WRN-
TC and track from IBTrACS
2. Final polygon: Combine track
and wind field based on tropical
cyclone name and year
Cold-wave & Heat-wave
t1
t2
t3
1. ERA-5 Daily temperature data,
calculate the daily extremes (< 5
percentile for cold wave, > 95
percentile for heat-wave).
2. See where temperatures
are extreme for at least
three consecutive days
3. Final polygon
Extreme Wind
1. ERA-5 Maximum daily wind
gust data, calculate the daily
extremes (> 99 percentile). Max
wind of polygon above 15 ms-1
Tsunami Flood
2. Final polygon
Wildfire
1. Polygon from the global
wildfire dataset. Is the area
of the polygon above 5 km2
and the duration of the
wildfire at least 3 days?
yes
no
2. Final polygon
2. Polygon removed
from dataset
Drought
2. Final polygon
Source
Runup
1. Source and runup data
Global Historic Tsunami
database
2. Final polygon
𝐿
1. GDO SPI-3 (3-month
Standardized Precipitation
Index) monthly data below
1.3
2. Final polygon

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Time-lag
2 days
1 day
3 days

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Recovery rates from nighttime light data
Sophie Buijs (IVM VU Amsterdam)

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Recovery rates from nighttime light data
October 9, 2018 October 13, 2018

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Recovery rates from nighttime light data

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Software development

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Software development

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