Goal of the Project
The total life cycle cost of flood defense infrastructure, such as dikes, is influenced by various factors. When infrastructure is already in place, all costs fall under Operational Expenditures (OPEX). OPEX includes reinforcement projects followed by regular maintenance until the next reinforcement. This period is an “increment” in the life cycle of flood defense infrastructure. This PhD will examine events within a single increment and across multiple increments into an uncertain future.
During one increment, various events can occur: storms may damage dikes, repairs may be needed, burrowing holes may be found, or safety standards and assessment methods may change. What factors influence the life cycle of an increment? How effective are current maintenance strategies, and can they be optimized? How can we balance reinforcement projects and maintenance?
Over multiple increments, current practice in the Netherlands involves designing a dike for 50 years with a 50cm sea level rise. This design is optimized for these conditions, but does not consider expendability and adaptability. Is this approach justified? Future increments will follow. What do these choices mean for the life cycle over multiple increments? How can designs be optimized over time to account for future increments? Is a 50-year design with 50cm sea level rise the best starting point? Can we design smarter for long-term cost savings?
I aim to create a Life Cycle simulator to assess optimal and robust designs and strategies, leading to least-regret outcomes. I will also explore how to define optimal, robust, and least-regret strategies.
Scientific Motivation
Currently, the life cycle of one increment is not well figured out. We simply do not know how for instance storm events influence the flood probability of flood protection infrastructure, or what burrowing holes do. With the latest knowledge on failure mechanisms, I will attempt to find out including how maintenance strategies and design choices during reinforcement projects impact them.
For multiple increment over time, the current strategy is to take fixed intervals. However, there is no solid foundation for these intervals. The scientific challenge is to find solid foundation that can be used for various types of structures on the technical lifetime, climate change scenario, expendability and adaptability. What robust choices can be made today that are optimized and will lead to least-regret with a deeply uncertain future?
And with that comes the last very important scientific challenge: how do we even define “optimal”,
“robust” and “least-regret”? Do these have a pure economical definition or are other performance indicators included? The definition of these terms have a strong influence on the outcome, and they are strongly influenced by the choices of policy makers as well. What influence do these choices have on what can be considered “optimal” flood risk reduction strategies over multiple increments?
Case Study
I will assess the LCC framework for several case studies:
- The Singapore climate adaptation project
- Dike improvement project “Zak van Zuid-Beveland” along the Western Scheldt as part of Waterboard Scheldestromen (Province of Zeeland)
- Hollandsche IJssel including interaction with the storm surge barrier
- River case / developing country case / possibly Galveston, TX case
Expected Outcomes
- Stochastic & synthetic storm simulator
- Dike damage model with latest literature on progressive damages
- LCC assessment framework per increment
- LCC assessment framework over multiple increments
- Definition of “optimal, robust and least regret”
- Advice on optimal lifetime per structural element
Involved Endusers
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Last modified: 29/08/2024
Contributing researchers
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Maarten Schoemaker
TU Delft
Project outputs
FRM in focus: video
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The Future FRM Tech programme develops flood resilient landscapes for rivers and estuaries as well as technical solutions for water barriers. Watch the video to get to know more about the project
29/04/2021 by Prof. dr. ir. Bas Jonkman
Bevat: Video & Audio