Decision Making under Deep Uncertainty

Marchau, V.A.W.J.; Walker, Warren E.; Bloemen, Pieter J. T. M.; Popper, Steven W.

doi:10.1007/978-3-030-05252-2

Cited by 303 publications

(101 citation statements)

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“…Under the high-emission scenario RCP8.5 A , leading to an increase of global mean temperature of 3.2°C-5.4°C, sea level could rise up to 3 m in 2100 (median value 1.95 m). 7 The 1st Delta Committee was established in 1953 after the storm surge and extensive flooding of the southwestern Netherlands in which over 1800 people were killed. This 1st Delta Committee advised on the measures to improve the flood protection of this area, predominantly by shortening of the coastline by a comprehensive system of sluices, dams and a storm surge barrier, the so called 'Delta works'.…”

Section: Slr Scenariosmentioning

confidence: 99%

“…The large range of potential future sea levels poses, however, the question: 'When and how much to adapt? ' To deal with uncertainties about the future and to minimize regret of investment decisions as the future unfolds, decision makers are urged to take an adaptive approach [6][7][8][9]. Over the last years several frameworks have been put forward to design adaptive strategies, including robust decision making [10,11], adaptive policy making [12,13], dynamic adaptive policy pathways [9,14] and engineering options analysis [15,16].…”

Section: Introductionmentioning

confidence: 99%

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Adaptation to uncertain sea-level rise; how uncertainty in Antarctic mass-loss impacts the coastal adaptation strategy of the Netherlands

Haasnoot

Kwadijk

Alphen³

et al. 2020

Environ. Res. Lett.

111

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Uncertainties in the rate and magnitude of sea-level rise (SLR) complicate decision making on coastal adaptation. Large uncertainty arises from potential ice mass-loss from Antarctica that could rapidly increase SLR in the second half of this century. The implications of SLR may be existential for a lowlying country like the Netherlands and warrant exploration of high-impact low-likelihood scenarios. To deal with uncertain SLR, the Netherlands has adopted an adaptive pathways plan. This paper analyzes the implications of storylines leading to extreme SLR for the current adaptive plan in the Netherlands, focusing on flood risk, fresh water resources, and coastline management. It further discusses implications for coastal adaptation in low-lying coastal zones considering timescales of adaptation including the decisions lifetime and lead-in time for preparation and implementation. We find that as sea levels rise faster and higher, sand nourishment volumes to maintain the Dutch coast may need to be up to 20 times larger than to date in 2100, storm surge barriers will need to close at increasing frequency until closed permanently, and intensified saltwater intrusion will reduce freshwater availability while the demand is rising. The expected lifetime of investments will reduce drastically. Consequently, step-wise adaptation needs to occur at an increasing frequency or with larger increments while there is still large SLR uncertainty with the risk of under-or overinvesting. Anticipating deeply uncertain, high SLR scenarios helps to enable timely adaptation and to appreciate the value of emission reduction and monitoring of the Antarctica contribution to SLR.

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Section: Slr Scenariosmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Adaptation to uncertain sea-level rise; how uncertainty in Antarctic mass-loss impacts the coastal adaptation strategy of the Netherlands

Haasnoot

Kwadijk

Alphen³

et al. 2020

Environ. Res. Lett.

111

View full text Add to dashboard Cite

show abstract

“…They are made up of multiple interacting components, both physical and institutional, and have hundreds of decision variables that managers can assign values to when attempting to satisfy the multitude of objectives people want from the system. They must make their decisions under all the uncertainties of future water supplies and demands [44,45].…”

Section: Challengesmentioning

confidence: 99%

From Analyses to Implementation and Innovation

Loucks

2020

Water

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Reviews of the water resource systems planning and management literature show considerable interest in methodological issues and less so in implementation experiences. This paper offers some thoughts on the use of our analysis tools in the political environment where water management decisions are typically made. This paper also addresses the challenge of going beyond analysis and synthesis to innovation. How can we extend our modeling methods so as to help ourselves become more creative in the identification of potentially improved infrastructure design and/or operating policies, and even of institutional changes, that we have otherwise not considered or thought of?

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“…First, human and environmental spheres are complex systems: path dependencies in both require the consideration of large time frames, and their non-linear interactions induce dynamic behavior that is difficult to anticipate and characterize. Second, deep uncertainty affects both spheres as experts and stakeholders often disagree on the causal representation of these systems, the value of key parameters for analysis, and the relevance of different metrics for describing sustainability (Lempert, 2003;Marchau et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

“…On the one hand, the use of simplistic models for analysis can result in omissions relevant for determining long-term outcomes. On the other hand, if the scope of an analysis is too narrow, it is difficult to make the analysis relevant to a wide range of stakeholders (Lempert, 2003;Marchau et al, 2019). Thus, a key emerging question in sustainability sciences is how to design robust policy interventions that explicitly account for complexity and deep uncertainty and which can inform in practical detail public policy discussions of sustainability challenges that affect a wide range of actors.…”

Section: Introductionmentioning

confidence: 99%

Computational Intelligence for Studying Sustainability Challenges: Tools and Methods for Dealing With Deep Uncertainty and Complexity

2020

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The study of sustainability challenges requires the consideration of multiple coupled systems that are often complex and deeply uncertain. As a result, traditional analytical methods offer limited insights with respect to how to best address such challenges. By analyzing the case of global climate change mitigation, this paper shows that the combination of high-performance computing, mathematical modeling, and computational intelligence tools, such as optimization and clustering algorithms, leads to richer analytical insights. The paper concludes by proposing an analytical hierarchy of computational tools that can be applied to other sustainability challenges.

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Decision Making under Deep Uncertainty

Cited by 303 publications

References 0 publications

Adaptation to uncertain sea-level rise; how uncertainty in Antarctic mass-loss impacts the coastal adaptation strategy of the Netherlands

Adaptation to uncertain sea-level rise; how uncertainty in Antarctic mass-loss impacts the coastal adaptation strategy of the Netherlands

From Analyses to Implementation and Innovation

Computational Intelligence for Studying Sustainability Challenges: Tools and Methods for Dealing With Deep Uncertainty and Complexity

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