MCDA stakeholder workshops

Duranova, T.; Asselt, Esther van; Müller, Tim; Bohunova, J.; Twenhöfel, C.; Smetsers, R.C.G.M.

doi:10.1051/radiopro/2020032

Cited by 4 publications

(2 citation statements)

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“…The evaluations were performed by means of moderated exercises using different scenarios, and involving stakeholders with different backgrounds, who may be involved in decision making during a real nuclear emergency. The scenarios, data used for evaluation and evaluation results from the final workshop of CONFIDENCE are presented in other articles of this special issue (Charnock et al, 2020;Duranova et al, 2020aDuranova et al, , 2020b.…”

Section: Discussionmentioning

confidence: 99%

MCDA handling uncertainties

2020

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Work package 6 (WP) of the European project CONFIDENCE focussed on decision support for stakeholders in nuclear emergencies especially considering uncertainties in such scenarios. A well-suited method for collaborative decision support is the Multi Criteria Decision Analysis (MCDA). It provides a transparent approach for choosing a suitable strategy from a pool of strategies taking into account the different preferences of the involved stakeholders. One goal of WP 6 was to provide this method as a software tool to the nuclear emergency management community. However a default MCDA is not capable of handling uncertainties as input parameters. We embedded an existing MCDA tool in an ensemble evaluation framework to overcome this limitation and to process probabilistic input parameters. Within this framework random deterministic MCDAs are generated from the probabilistic MCDA and their results are combined into a single result reflecting this uncertainty. The enhanced MCDA tool provides user interfaces for defining probabilistic input parameters for impact values and criteria weights, as well as graphical components to communicate the results to the stakeholders. The tool was presented in several workshops to the potential stakeholders where it was applied to fictitious scenarios. The feedback was used to improve the tool in several iterations.

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Section: Discussionmentioning

confidence: 99%

MCDA handling uncertainties

2020

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“…Similarly, probability is the accepted way of modelling natural variation in a population, for instance when estimating cancer risk from radiation exposure (Keil and Richardson, 2018). Examples of such types of uncertainties can be found throughout the CONFIDENCE project, including meteorological conditions and dispersion models, impact of soil parameters on food-chain transfer, as well as the use of probability models within scenario based assessments (Duranova et al, 2020a(Duranova et al, , 2020bBeresford et al, 2020).…”

Section: Stochastic or Aleatory Uncertaintymentioning

confidence: 99%

Different types of uncertainty in nuclear emergency management

et al. 2020

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The objective of the CONFIDENCE project has been to identify, assess and communicate the uncertainties that arise in managing and recovering from a nuclear accident. To do that, it is important to be clear on what uncertainty means, how it arises and how we might analyse it. In fact, there are many forms of uncertainty, some of which we can assess with current tools, but some of which are more nebulous and difficult to deal with. Nonetheless, all need to be communicated to the emergency managers. Starting with a review of different categories of uncertainties, and using examples from the CONFIDENCE project, this paper discusses how the various uncertainties are manifested in nuclear emergency management. It concludes with a simple framework for categorising and analysing them. The overall intention is that such a framework could contribute to a broader discussion on identifying and handling uncertainties with nuclear emergency management actors

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Editorial: the main results of the European CONFIDENCE project

Raskob

Duranova

2020

Radioprotection

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In nuclear emergency management and long-term rehabilitation, dealing with uncertain information on the current situation, or predicted evolution of the situation, is an intrinsic problem for decision making. Uncertain information related to, for instance, incomplete information on the source term and the prevailing weather can result in dose assessments that differ dramatically from reality. Uncertainty is also an intrinsic part of model parameters. In the presence of uncertainty, ineffective decisions are often taken (e.g. too conservative or optimistic predictions, inadequately accounting of non-radiological risks), which may result in more overall harm than good due to secondary causalities as observed following the Chernobyl and Fukushima accidents. Therefore, the reduction of uncertainty, and how to deal with uncertain information, is essential to improve decision making for the protection of the affected population and to minimise disruption of normal living conditions.Decisions on early countermeasures (e.g. evacuation, sheltering, and provision of iodine tablets) are often taken based on deterministic calculations considering the best available source term information and the state of the art numerical weather prediction data as inputs. The source term uncertainty is large and quantification difficult. Uncertainty in meteorological forecasts is routinely quantified by "ensemble predictions". However, these predictions are not used in emergency management. One reason for this is the effort and time required to process 30 to 100 different weather sequences within atmospheric dispersion models.At present, decision making in the early phase is mainly based on modelling followed by a period where monitoring has made enough progress to provide a robust contamination and dose map. However, in between some monitoring data will be available; however, no operational tool exists to combine simulated dose estimations with monitoring data to obtain a more consolidated picture of the radiological situation.The key endpoint for all decision making is the dose and associated risk to affected population groups. However, in the case of the Fukushima accident, only order-of-magnitude dose bands were estimated from (local) contamination and model predictions, with no accounting for individual human behaviour patterns or location. Individual dose measurements could greatly reduce this uncertainty but are limited by capacity.Completely missing from emergency management is the assessments of risk in the early and the transition phases. However, this is important for decision making on the need for medical surveys and long-term support of the affected population.Operational decisions concerning land and food chain management rely on radioecological models that are mostly based on simple, but highly uncertain, transfer ratios to predict contamination in foodstuffs (though such data are few for some climatic areas, (e.g. Mediterranean) and foodstuff-radionuclide combinations). Process-based models might provide an approach to red...

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MCDA stakeholder workshops

Cited by 4 publications

References 8 publications

MCDA handling uncertainties

MCDA handling uncertainties

Different types of uncertainty in nuclear emergency management

Editorial: the main results of the European CONFIDENCE project

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