Presentation by Umit Taner (Deltares, Netherlands) at the Climate Adaptation Symposium 2023, during the Delft Software Days - Edition 2023 (DSD-INT 2023). Wednesday, 29 November 2023, Delft.

1. Climate Stress Testing Tool
(CST Tool)
Climate Adaptation Symposium
Delft Software Days (DSD-INT 2023)
November 29, 2023
M. Umit Taner, PhD

2. Conventional
approach
(predict → act)
What would the
future be?
(projections)
Seek optimality
How would the
system respond?

3. 3
Emission Scenarios General Circulation Models (GCMs) Downscaling
Water system
model
Plan For these
Scenarios
Impact
Space
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4. Climate models project future climate
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5. But they disagree with each other
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6. … and we
have a lot of
models…
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7. … scenarios
depend on
climate
policies and
socio-
economic
trends…
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8. Conventional
approach
(predict → act)
DMDU
(Bottom-up
approaches)
What would the
future be?
(projections)
Seek optimality
How would the
system respond?
What are
vulnerabilities?
(stress testing)
Seek robustness
How concerned
shall we be?
(climate-informed
likelihoods)

9. Climate stress testing*
Define vulnerability
metrics criteria &
* Brown et al., 2013
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10. Online, open-source toolbox for rapid bottom-up
climate risk assessment
• Developed for general practitioners & analysts (GUI)
• Open-source software on the cloud, no installation necessary
• Readily linked to common climate datasets (CMIP6, ERA5, CHIRPs)
• Initially developed to assess hydrological risks (droughts and/or
floods)
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11. What the tool will do:
1. Create a project virtually at any basin/subbasin and rapidly
build a distributed hydrology model
2. Explore climate uncertainty from historical data & GCM
information
3. Design and execute a climate stress test to explore
hydrological outputs across a wide range of futures
4. Interactively assess vulnerabilities and risk with user-defined
thresholds and GCM information
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12. CST Tool: Some answers we can learn
➢ Discharge sensitivity to
∆temp and ∆precip
➢ Effect of earlier snow melt
on spring flows due to
warming
➢ Understand where low flow
criteria is violated
➢ Plausibility of occurrence
based on climate
projections
Now
GCM projections
(2035-2065)
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13. What it won’t be able to do
• Evaluate non-climatic uncertainties
• Water systems analysis: water use and allocation,
reservoir operations, demand management etc.
• Detailed project-level assessments with customized data
and models
• Adaptation planning: evaluate investments, trade-offs
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14. CST Tool: Software architecture
Request
Response
Web client Web service
Mongo
DB
Open-source python-
based workflow
management system
User input
• Project area
• Hydrological
variables
• Stress test
parameters
• Vulnerability
thresholds
• …
HYDROMT
Open-source python-package to build,
modify, analyze geospatial models
WEATHERGENR
Open-source R-package to simulate
daily, multi-grid, multi-variable series
WFLOW
Open-source spatially-distributed
hydrological modeling framework
Tools
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15. Weather generator
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Produces new weather
series: daily, multiple grids,
multiple variables
Coded in R (control from py)
Works with wflow forcings
(netcdf files)
Steinschneider and Brown 2013
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16. Historical series
Reproduce natural variability with synthetic traces
• Means, variability, extremes
• Temporal correlations
• Spatial correlations between
grids & variables
• Wet & dry spells
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17. 17
1900 1920 1940 1960 1980 2000
-0.5
-0.25
0
0.25
0.5
Time (year)
Temperature(degree
C
)
AMO, 40-50 year cycle
1900 1920 1940 1960 1980 2000
-1.5
-1
-0.5
0
0.5
1
1.5
Time (year)
Temperature(degree
C
)
ENSO, 3-7 year cycle
Preserves low-frequency variability
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Impose desired climatic changes on historical traces
Means conditions
Shifts in intra-annual climate (seasonality)
High-order statistics (variance, extremes, transition probs.)
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19. CST prototype (work-in-progress)
https://cst-toolbox.avi.directory.intra/
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20. Questions?
umit.taner@Deltares.nl