es500717t_si_001.pdf (425.92 kB)
The Value of Information for Managing Contaminated Sediments
journal contribution
posted on 2014-08-19, 00:00 authored by Matthew E. Bates, Magnus Sparrevik, Nicolas de Lichy, Igor LinkovEffective management of contaminated
sediments is important for
long-term human and environmental health, but site-management decisions
are often made under high uncertainty and without the help of structured
decision support tools. Potential trade-offs between remedial costs,
environmental effects, human health risks, and societal benefits,
as well as fundamental differences in stakeholder priorities, complicate
decision making. Formal decision-analytic tools such as multicriteria
decision analysis (MCDA) move beyond ad hoc decision support to quantitatively
and holistically rank management alternatives and add transparency
and replicability to the evaluation process. However, even the best
decisions made under uncertainty may be found suboptimal in hindsight,
once additional scientific, social, economic, or other details become
known. Value of information (VoI) analysis extends MCDA by systematically
evaluating the impact of uncertainty on a decision. VoI prioritizes
future research in terms of expected decision relevance by helping
decision makers estimate the likelihood that additional information
will improve decision confidence or change their selection of a management
plan. In this study, VoI analysis evaluates uncertainty, estimates
decision confidence, and prioritizes research to inform selection
of a sediment capping strategy for the dibenzo-p-dioxin
and -furan contaminated Grenland fjord system in southern Norway.
The VoI model extends stochastic MCDA to model decisions with and
without simulated new information and compares decision confidence
across scenarios with different degrees of remaining uncertainty.
Results highlight opportunities for decision makers to benefit from
additional information by anticipating the improved decision confidence
(or lack thereof) expected from reducing uncertainties for each criterion
or combination of criteria. This case study demonstrates the usefulness
of VoI analysis for environmental decisions by predicting when decisions
can be made confidently, for prioritizing areas of research to pursue
to improve decision confidence, and for differentiating between decision-relevant
and decision-irrelevant differences in evaluation perspectives, all
of which help guide meaningful deliberation toward effective consensus
solutions.