Classifying and communicating uncertainties in model-based policy analysis

Kwakkel, Jan H.; Walker, Warren E.; Marchau, V.A.W.J.

doi:10.1504/ijtpm.2010.036918

Cited by 168 publications

(153 citation statements)

References 37 publications

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“…These would probably classify as 'deep uncertainty' according to the classification of Kwakkel et al (2010). One of the few possible approaches in such a case is asking 'What, if…?…”

Section: Discussionmentioning

confidence: 99%

Assessment of the Netherlands’ Flood Risk Management Policy Under Global Change

Klijn

Bruijn

Knoop

et al. 2011

AMBIO

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Climate change and sea level rise urge lowlying countries to draft adaption policies. In this context, we assessed whether, to what extent and when the Netherlands' current flood risk management policy may require a revision. By applying scenarios on climate change and socio-economic development and performing flood simulations, we established the past and future changes in flood probabilities, exposure and consequences until about 2050. We also questioned whether the present policy may be extended much longer, applying the concept of 'policy tipping points'. Climate change was found to cause a significant increase of flood risk, but less than economic development does. We also established that the current flood risk management policy in the Netherlands can be continued for centuries when the sea level rise rate does not exceed 1.5 m per century. However, we also conclude that the present policy may not be the most attractive strategy, as it has some obvious flaws.

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“…These would probably classify as 'deep uncertainty' according to the classification of Kwakkel et al (2010). One of the few possible approaches in such a case is asking 'What, if…?…”

Section: Discussionmentioning

confidence: 99%

Assessment of the Netherlands’ Flood Risk Management Policy Under Global Change

Klijn

Bruijn

Knoop

et al. 2011

AMBIO

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“…sets of model inputs, alternative relationships inside a model, etc. ), without ranking these possibilities in terms of perceived likelihood or assigning probabilities to the different possibilities [5].…”

Section: Scenario Discovery: a Model Based Approach To Scenario Develmentioning

confidence: 99%

“…A second reason why preparing a port for possible future developments is important, is that the future is deeply uncertain [4,5]. Since there are many actors with different objectives involved in the global logistic system, it is virtually impossible to predict how changes in any given component of the system will affect the system as a whole.…”

Section: Introductionmentioning

confidence: 99%

A scenario discovery study of the impact of uncertainties in the global container transport system on European ports

Halim

Kwakkel

Tavasszy

2016

Futures

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The global container transport system is changing quickly. Ports can be severely affected by these changes; therefore ports need insight into how the system might change and what the impact of this will be on their competitive position. Given the intrinsic complexity of the container transport system and the presence of a wide range of deeply uncertain factors affecting the system, we use an exploratory modeling approach to study future scenarios for the global container network. Using scenario discovery and worst-case discovery, we assess the implications of various uncertain factors on the competitive position of the port of Rotterdam. It is found that overall the competitive position of Rotterdam is quite robust with respect to the various uncertain factors. The main vulnerability is the quality of the hinterland connections. A modest deterioration of the quality of the hinterland connections, resulting in increased travel time, will result in a loss of throughput for Rotterdam.Keywords: scenario discovery, deep uncertainty, container shipping, global freight logistics IntroductionIn the past couple of decades, changes in the global container transport system have happened very rapidly. These changes have affected virtually all actors in the system, but the biggest impact has been on maritime ports. Ports have to be adaptive and resilient in responding to the changes in the global container shipping system. In today's globalized economy, ports need to ensure that they can function robustly, both as a transshipment node and as a gateway node for global trade flows. A failure to respond to changes in a timely manner often results in negative consequences for the port itself, as well as the economy of the region or country to which the port belongs. For example, the recent congestion at ports on the west coast of the US resulted in estimated damages for the economy of roughly 7 billion US dollar [1].Preparing a port for a wide range of possible future developments is a profound challenge. The global container shipping system is composed of many elements, with strong interdependencies. Often, small changes cascade quickly through the system, potentially resulting in substantial changes somewhere quite far removed from the initial small change. For example, recently Ultra Large Carrier Vessels have entered the market. Liner shipping companies have started to form alliances to pursue economies of scale. This in turn affects the frequency of port calls, the port rotation schedule, and the container volumes loaded and unloaded at each port. Changes not only take place on the seaside. Developments in the hinterland, such as the construction of new infrastructures such as road, railways, and intermodal facilities affect transport cost.The ongoing changes on both the seaside and the land size of seaports change the spatial flow of containers globally. The operation of the Trans-Siberian railways is an example of the importance of hinterland infrastructure on global container flows through ports [2]. A similar © 2016 Man...

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“…However, it has also been addressed using terms such as value uncertainty (Morgan and Henrion 1990), volitional uncertainty (Bedford and Cooke 2001), decision-making uncertainty , human uncertainty , or human decision uncertainty (Kujala et al 2013). This type of uncertainty was also termed ambiguity by Kwakkel et al (2010), following the terminology introduced by Brugnach et al (2008) when addressing the fact that different individuals may use different frames of reference to interpret the same data. The term ambiguity in this context must not be mistaken with the same term being used to define one of the components of linguistic uncertainty, following the terminology of Regan et al (2002).…”

Section: Uncertainty: What Is It?mentioning

confidence: 99%

“…Another example can be found in the domain of decision support and policy making for which Walker et al (2003) proposed a framework to express the uncertainty in a model for decision makers. Following some concerns expressed by Norton et al (2006) about this framework, Kwakkel et al (2010) proposed a revised and extended version of this uncertainty classification system. With respect to attempts to express uncertainty in a common way across several domains, reference is made to the taxonomy proposed by Smithson (1989), and later reviewed by Bammer and Smithson (2008).…”

Section: Existing Framework To Classify Uncertaintymentioning

confidence: 99%

A framework to assess quality and uncertainty in disaster loss data

Romão

Paupério

2016

Nat Hazards

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There is a growing interest in the systematic and consistent collection of disaster loss data for different applications. Therefore, the collected data must follow a set of technical requirements to guarantee its usefulness. One of those requirements is the availability of a measure of the uncertainty in the collected data to express its quality for a given purpose. Many of the existing disaster loss databases do not provide such uncertainty/quality measures due to the lack of a simple and consistent approach to express uncertainty. After reviewing existing literature on the subject, a framework to express the uncertainty in disaster loss data is proposed. This framework builds on an existing uncertainty classification that was updated and combined with an existing method for data characterization. The proposed approach is able to establish a global score that reflects the overall uncertainty in a certain loss indicator and provides a measure of its quality.

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Classifying and communicating uncertainties in model-based policy analysis

Cited by 168 publications

References 37 publications

Assessment of the Netherlands’ Flood Risk Management Policy Under Global Change

Assessment of the Netherlands’ Flood Risk Management Policy Under Global Change

A scenario discovery study of the impact of uncertainties in the global container transport system on European ports

A framework to assess quality and uncertainty in disaster loss data

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