Elsevier

Environment International

Volume 32, Issue 8, December 2006, Pages 1072-1093
Environment International

From comparative risk assessment to multi-criteria decision analysis and adaptive management: Recent developments and applications

https://doi.org/10.1016/j.envint.2006.06.013Get rights and content

Abstract

Environmental risk assessment and decision-making strategies over the last several decades have become increasingly more sophisticated, information-intensive, and complex, including such approaches as expert judgment, cost–benefit analysis, and toxicological risk assessment. One tool that has been used to support environmental decision-making is comparative risk assessment (CRA), but CRA lacks a structured method for arriving at an optimal project alternative. Multi-criteria decision analysis (MCDA) provides better-supported techniques for the comparison of project alternatives based on decision matrices, and it also provides structured methods for the incorporation of project stakeholders' opinions in the ranking of alternatives. We argue that the inherent uncertainty in our ability to predict ecosystem evolution and response to different management policies requires shifting from optimization-based management to an adaptive management paradigm. This paper brings together a multidisciplinary review of existing decision-making approaches at regulatory agencies in the United States and Europe and synthesizes state-of-the-art research in CRA, MCDA, and adaptive management methods applicable to environmental remediation and restoration projects. We propose a basic decision analytic framework that couples MCDA with adaptive management and its public participation and stakeholder value elicitation methods, and we demonstrate application of the framework to a realistic case study based on contaminated sediment management issues in the New York/New Jersey Harbor.

Section snippets

Introduction: comparative risk assessment and evolving decision analysis methodologies

Risk management of environmental projects requires balancing scientific findings with multi-faceted input from many stakeholders with different values and objectives. In such instances, systematic decision analysis tools are an appropriate method to solve complex technical and behavioral issues (McDaniels, 1999). Regardless of the specific project, risk managers typically have four types of information that are used to make decisions: 1) the results of modeling and monitoring studies, 2) risk

Comparative risk assessment application to New York/New Jersey Harbor

We have taken the New York/New Jersey Harbor as a case study to illustrate an environmental management problem that could benefit from combined MCDA/adaptive management application. A decision scenario for the harbor is presented in Fig. 2. The harbor faces contaminated sediment management issues — several million cubic meters of sediments must be dredged each year to maintain navigation channels for harbor access (Wakeman and Themelis, 2001). Due to long-term human use of the harbor area,

MCDA methods and tools

In contrast to CRA, MCDA provides a more fully developed approach to environmental management (Table 1). Whereas a decision matrix marks the endpoint for CRA, it is only an intermediate product of MCDA. After matrix generation, different MCDA methods require different types of value information and follow various optimization algorithms. A detailed analysis of the theoretical foundations of these methods and their comparative strengths and weaknesses is presented in Belton and Stewart (2002).

MCDA applications in environmental management

Our non-exhaustive review of recent literature (Table 3) shows that MCDA has been used to support decision-making in contaminated site management and related areas. In this section we summarize decision analysis applications published in English language journals over the last 10 years that were located through Internet and library database searches (for greater detail, see Linkov et al., 2004, 2003). MCDA techniques have been applied to optimize policy selection in the remediation of

Adaptive management and environmental decision-making

The MCDA methods and tools discussed above can be used to support environmental decisions in traditional management schemes, but we see their strength when coupled with adaptive management. In traditional management (Fig. 3a), goals are set and different management strategies are considered. One management strategy is selected as the optimal one, and once it is implemented, its performance may not be monitored closely. At some point, the strategy will likely be evaluated, and if it is perceived

Emergence of adaptive management in regulatory agencies

Regulatory agencies in the United States and around the world recommend adaptive management, but agencies often implement or emphasize only specific elements of the process. The EPA, for instance, has implemented adaptive management in many projects. Among the most notable are the Mississippi River Basin project, which utilizes models and monitoring quite heavily as it attempts to reduce the uncertainties surrounding the biochemical mechanisms of hypoxia (EPA, 1999a, EPA, 2001b), and the Lake

Integration of adaptive management with multi-criteria decision analysis

As we have stated in our review, unlike traditional management schemes designed to find and follow the optimal remedial strategy, adaptive management acknowledges our inability to predict system evolution in response to changing physical environments and social pressures. Our review indicates that the concept of adaptive management is well respected in academia, and many government agencies have recommended it for application. Yet even though many papers acknowledge that effective environmental

Application of MCDA/adaptive management framework to New York/New Jersey Harbor

The New York/New Jersey Harbor case study is a good example application of the combined multi-criteria decision analysis and adaptive management framework. The comparative risk assessment presented above covered the first three steps of the process identified in Fig. 4 (that is, problem formulation and alternative generation, criteria identification, and evaluating performance of alternatives on the criteria). As we noted earlier, the fourth step (gathering value judgments on the relative

Discussion/conclusion

We are not the first to propose an integration of decision analysis methods with adaptive management. For example, Rauscher et al. (2000) propose a combination of the analytical hierarchy process and adaptive management. Pastorok et al. (1997) develop a decision-making framework combined with monitoring and adaptive management. Additionally, Nudds et al. (2003) with the University of Guelph Decision Analysis and Adaptive Management Project are applying a combination of methods to the management

Acknowledgements

The authors are grateful to Drs. Seager, Ganoulis, Cooke, Small, Valverde, Yoe, Sullivan, and Gardner for useful suggestions. Support for this study was provided by the USACE Dredging Operations and Environmental Research (DOER) (GAK, IL, FKS, CB, TSB) and NOAA through the Cooperative Institute for Coastal and Estuarine Environmental Technology (IL). Permission was granted by the Chief of Engineers to publish this material.

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