Risk and Uncertainty Analysis Procedures for the Evaluation of Environmental Outputs,

Yoe, Charles; Skaggs, Leigh

doi:10.21236/ada343651

Cited by 6 publications

(5 citation statements)

References 1 publication

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“…Almost all decision analysis methodologies share similar steps of organization in the construction of the decision matrix. Each MCDA methodology synthesizes the matrix information and ranks the alternatives by different means (Yoe 2002). Different methods require diverse types of value information and follow various optimization algorithms.…”

Section: Approaches To Mcdamentioning

confidence: 99%

Application of multicriteria decision analysis in environmental decision making

Kiker

Bridges

Varghese

et al. 2005

Integr Envir Assess & Manag

774

435

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Decision making in environmental projects can be complex and seemingly intractable, principally because of the inherent trade-offs between sociopolitical, environmental, ecological, and economic factors. The selection of appropriate remedial and abatement strategies for contaminated sites, land use planning, and regulatory processes often involves multiple additional criteria such as the distribution of costs and benefits, environmental impacts for different populations, safety, ecological risk, or human values. Some of these criteria cannot be easily condensed into a monetary value, partly because environmental concerns often involve ethical and moral principles that may not be related to any economic use or value. Furthermore, even if it were possible to aggregate multiple criteria rankings into a common unit, this approach would not always be desirable because the ability to track conflicting stakeholder preferences may be lost in the process. Consequently, selecting from among many different alternatives often involves making trade-offs that fail to satisfy 1 or more stakeholder groups. Nevertheless, considerable research in the area of multicriteria decision analysis (MCDA) has made available practical methods for applying scientific decision theoretical approaches to complex multicriteria problems. This paper presents a review of the available literature and provides recommendations for applying MCDA techniques in environmental projects. A generalized framework for decision analysis is proposed to highlight the fundamental ingredients for more structured and tractable environmental decision making.

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Section: Approaches To Mcdamentioning

confidence: 99%

Application of multicriteria decision analysis in environmental decision making

Kiker

Bridges

Varghese

et al. 2005

Integr Envir Assess & Manag

774

435

View full text Add to dashboard Cite

show abstract

“… Yoe and Skaggs [1997] suggest that there cannot be a one‐size‐fits‐all uncertainty analysis. Although, their argument has been restricted to ecosystem restoration projects it can be applied to modeling exercises in general.…”

Section: Uncertainty Analysis Is Too Difficult To Performmentioning

confidence: 99%

Ignorance is bliss: Or seven reasons not to use uncertainty analysis

Pappenberger

Beven

2006

Water Resources Research

464

359

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[1] Uncertainty analysis of models has received increasing attention over the last two decades in water resources research. However, a significant part of the community is still reluctant to embrace the estimation of uncertainty in hydrological and hydraulic modeling. In this paper, we summarize and explore seven common arguments: uncertainty analysis is not necessary given physically realistic models; uncertainty analysis cannot be used in hydrological and hydraulic hypothesis testing; uncertainty (probability) distributions cannot be understood by policy makers and the public; uncertainty analysis cannot be incorporated into the decision-making process; uncertainty analysis is too subjective; uncertainty analysis is too difficult to perform; uncertainty does not really matter in making the final decision. We will argue that none of the arguments against uncertainty analysis rehearsed are, in the end, tenable. Moreover, we suggest that one reason why the application of uncertainty analysis is not normal and expected part of modeling practice is that mature guidance on methods and applications does not exist. The paper concludes with suggesting that a Code of Practice is needed as a way of formalizing such guidance.Citation: Pappenberger, F., and K. J. Beven (2006), Ignorance is bliss: Or seven reasons not to use uncertainty analysis, Water Resour. Res., 42, W05302,

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“…Saltelli et al (2000) mention the influence of the model setting on the sources that drive output variations. Conversely, Yoe and Skaggs (1997) note that once the important sources of uncertainty have been identified, this knowledge is relevant for any future study using that model. Either way, in practical applications a sensitivity analysis is usually not performed for every model application at every scale.…”

Section: Resultsmentioning

confidence: 99%

“…Over recent decades, guidelines, methods and overviews of methods have been published for dealing with uncertainties, in particular input data and parameter uncertainties (e.g. Yoe and Skaggs, 1997;van der Sluijs et al, 2003;Floodrisknet, 2007). However, translating these methods to the level of practical application is still a challenge in environmental science and other fields.…”

Section: Introductionmentioning

confidence: 99%

Uncertainty analysis at large scales: limitations and subjectivity of current practices - a water quality case study

Bijlsma

Groenendijk

Blind

2007

Water Science and Technology

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Uncertainty analysis for large-scale model studies is a challenging activity that requires a different approach to uncertainty analysis at a smaller scale. However, in river basin studies, the practice of uncertainty analysis at a large scale is mostly derived from practice at a small scale. The limitations and inherent subjectivity of some current practices and assumptions are identified, based on the results of a quantitative uncertainty analysis exploring the effects of input data and parameter uncertainty on surface water nutrient concentration. We show that: (i) although the results from small- scale sensitivity analysis are often applied at larger scales, this is not always valid; (ii) the current restriction of the uncertainty assessment to uncertainty types with a strong evidence base gives structurally conservative estimates; (iii) uncertainty due to bias is usually not assessed, but it may easily outweigh the effects of variability; (iv) the uncertainty bandwidth may increase for higher aggregation levels, although the opposite is the standard assumption.

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Risk and Uncertainty Analysis Procedures for the Evaluation of Environmental Outputs,

Cited by 6 publications

References 1 publication

Application of multicriteria decision analysis in environmental decision making

Application of multicriteria decision analysis in environmental decision making

Ignorance is bliss: Or seven reasons not to use uncertainty analysis

Uncertainty analysis at large scales: limitations and subjectivity of current practices - a water quality case study

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