This document discusses approaches for designing critical infrastructure systems under uncertainty from socioeconomic and climate change. It suggests applying safety factors or designing flexible systems to deal with an uncertain future. Quantitative decision models were used to determine the optimal safety factor and measure the value of flexibility. The models showed the safety factor should be higher for inflexible systems and lower for flexible ones. Flexibility is more valuable when there is potential for significant learning and changes over the system's lifetime. The regulatory framework, such as requiring a risk-based versus rule-based approach, also influences design choices. The document concludes with design recommendations based on optimizing safety factors and valuing flexibility under different types and degrees of uncertainty.

1. Olga Špačková, Beatrice Dittes, Daniel Straub
Technische Universität München
Engineering Risk Analysis (ERA) Group
IDRC Davos, 31.8.2016
Critical infrastructure and disaster risk reduction
planning under socioeconomic and climate
change uncertainty

2. 2
Design of infrastructure systems – finding optimal balance
between safety and costs
Flood protection system in Rosenheim,
Germany
Source: WWA Rosenheim
Wellington transport infrastructure, NZ
By Phillip Capper, CC BY 2.0

3. 3
Design of infrastructure systems – finding optimal balance
between safety and costs
Shahu Water Supply Plant in Gao’an City,
Jiangxi Province
by Asian Development Bank/ CC BY-NC-ND
2.0
eAquafin waste water treatment plant of
Antwerpen-Zuid
Source: Wikipedia

4. 4
Uncertain effect of climate change
Source: Congressional Budget Office (Congress of the United States).
2003. The Economics of Climate Change: a Primer.

5. 5
Uncertain socio-economic development
By Lauren Manning, CC BY 2.0

6. 6
Parameter uncertainty due to limited data
Dittes, Spackova & Straub. Managing uncertainty in flood predictions: Flexible protection
strategies vs. safety factors. Under review.

7. • Applying safety factors/margins (reserves)
• Designing flexible (adaptable) systems
7
Design approaches to deal with uncertain future

8. 8Olga Špačková (TUM) | Planning under socioeconomic and climate change uncertainty
How high should be the safety factor?
Does flexibility pay off?
Quantitative decision models

9. 9Olga Špačková (TUM) | Planning under socioeconomic and climate change uncertainty
Measure of flexibility

10. 10Olga Špačková (TUM) | Planning under socioeconomic and climate change uncertainty
Optimal safety factor (reserve)

11. 11Olga Špačková (TUM) | Planning under socioeconomic and climate change uncertainty
Optimal safety factor (reserve)

12. 12
Example: Optimal safety factor of flood protection
under statistical uncertainty
Dittes, Spackova & Straub. Managing uncertainty in flood predictions: Flexible protection
strategies vs. safety factors. Under review.

13. 13Olga Špačková (TUM) | Planning under socioeconomic and climate change uncertainty
Selection between flexible and inflexible systems:
Value of flexibility

14. 14Olga Špačková (TUM) | Planning under socioeconomic and climate change uncertainty
Value of flexibility

15. 15
Examples
Flood protection system under climate change
- low learning effect in near future
Waste water treatment plant under pop.growth
- high learning effect
Spackova & Straub. Long-term adaption decisions via fully and partially observable Markov
decision processes . Under review.

16. 16Olga Špačková (TUM) | Planning under socioeconomic and climate change uncertainty
Rule-based vs. Risk based aproach
Prescribed safety level (rule) Risk based optimization
- e.g. design for a 100-year event

17. 17Olga Špačková (TUM) | Planning under socioeconomic and climate change uncertainty
Value of flexibility

18. • Flexibility of the system
• Lifetime of the system
• Type and degree of uncertainty
• Future learning
• Regulatory framework (risk-based vs. rule based)
18Olga Špačková (TUM) | Planning under socioeconomic and climate change uncertainty
Key factors influencing the design

19. Based on quantitative decision models, design recommendations were derived on
how to account for uncertainties:
• Optimal safety factor/reserve
• High for inflexible, low for flexible systems
• Increases with degree of uncertainty
• Value of Flexibility
• High when significant learning effect and thus changes in of the system in the future are expected
• Higher in the rule-based regulatory framework than in risk-based
• In risk-based framework, conservative design is a no-regret strategy
19Olga Špačková (TUM) | Planning under socioeconomic and climate change uncertainty
Summary

20. Olga Špačková
Engineering Risk Analysis Group, TU München
olga.spackova@tum.de
AdaptRisk Project: http://www.era.bgu.tum.de/research/adaptrisk/
Thank you for your attention!
Questions?