Importance of scientific uncertainty in decision making

Uncertainty in environmental decision making should not be thought of as a problem that is best ignored. In fact, as is illustrated in a simple example, we often informally make use of awareness of uncertainty by hedging decisions away from large losses. This hedging can be made explicit and formalized using the methods of decision analysis. While scientific uncertainty is undesirable, it can still be useful in environmental management as it provides a basis for the need to fund additional monitoring, experimentation, or information acquisition to improve the scientific basis for decisions.     

A Multiattribute Index for Assessing Environmental Impacts of Regional Development Projects: A Case Study of Korea

Evaluating environmental impacts has become an increasingly vital part of environmental management. In the present study, a methodological procedure based on multiattribute utility theory (MAUT) has been applied to obtain a decision-maker's value index on assessment of the environmental impacts. The paper begins with an overview of MAUT. Next, we elicited strategic objectives and several important attributes, and then structured them into a hierarchy, with the aim of structuring and quantifying the basic values for the assessment. An environmental multiattribute index is constructed as a multiattribute utility function, based on value judgements provided by a decision-maker at the Korean Ministry of Environment (MOE). The implications of the results are useful for many aspects of MOE's environmental policies; identifying the strategic objectives and basic values; facilitating communication about the organization's priorities; and recognizing decision opportunities that face decision-makers of Korea.     

Decision making: With applications for environmental management

The two major processes of decision making, behavioral interactions and decision analysis, are discussed. Comparisons are made between the Delphi and NGT methods of behavioral interaction. Three different types of decision analysis are compared, including the Goals Achievement Matrix, Concordance Analysis, and the Simple Multi-Attribute Rating Technique. Decision making problems characteristic of environmental studies are reviewed. A method of decision making that combines the best qualities of other methods is suggested. The overall purpose of this paper is to make the technical knowledge of decision making useful to environmentalists, businessmen, citizens, and politicians, and to improve the process of policy making in environmental studies.     

Five propositions for improving decision making about the environment in developing communities: insights from the decision sciences

Decisions focused on managing natural resources in developing areas present some of the most imposing challenges to policy makers, scientists, and stakeholders alike. The response of policy makers and the technical community in the face of these challenges has been significant. However, our experiences as researchers and facilitators of group planning and decision-making processes have left us concerned about the lack of attention devoted to supporting the underlying processes used to make these complex decisions. To this end, we present five propositions based on work in the decision sciences that we believe stand out as essential for improving decision-making processes in developing communities.     

Towards Participatory Geographic Information Systems for community-based environmental decision making

This article discusses the potential of Geographic Information Systems (GIS) to become an information technology enabling groups of people to participate in decisions shaping their communities and promoting sustainable use of natural resources. It explains the concept of participation in the context of planning and decision making. In this context Participatory GIS (PGIS) offers tools that can be used to help the public become meaningfully involved in decision making processes affecting their communities. Following an overview of research on PGIS and its current status the article presents two recent studies of PGIS in water resource planning; one involving the use of computer generated maps representing simple information structures and the other involving the use of more sophisticated information tools. The synthesis of both studies provides the bases for discussing the prospects of PGIS to empower citizens in making decisions about their communities and resources.     

The role of analytical science in natural resource decision making

There is a continuing debate about the proper role of analytical (positivist) science in natural resource decision making. Two diametrically opposed views are evident, arguing for and against a more extended role for scientific information. The debate takes on a different complexion if one recognizes that certain kinds of problem, referred to here as “wicked” or “trans-science” problems, may not be amenable to the analytical process. Indeed, the mistaken application of analytical methods to trans-science problems may not only be a waste of time and money but also serve to hinder policy development. Since many environmental issues are trans-science in nature, then it follows that alternatives to analytical science need to be developed. In this article, the issues involved in the debate are clarified by examining the impact of the use of analytical methods in a particular case, the spruce budworm controversy in New Brunswick. The article ends with some suggestions about a “holistic” approach to the problem.     

A distance-based uncertainty analysis approach to multi-criteria decision analysis for water resource decision making

The choice among alternative water supply sources is generally based on the fundamental objective of maximising the ratio of benefits to costs. There is, however, a need to consider sustainability, the environment and social implications in regional water resources planning, in addition to economics. In order to achieve this, multi-criteria decision analysis (MCDA) techniques can be used. Various sources of uncertainty exist in the application of MCDA methods, including the selection of the MCDA method, elicitation of criteria weights and assignment of criteria performance values. The focus of this paper is on the uncertainty in the criteria weights. Sensitivity analysis can be used to analyse the effects of uncertainties associated with the criteria weights. Two existing sensitivity methods are described in this paper and a new distance-based approach is proposed which overcomes limitations of these methods. The benefits of the proposed approach are the concurrent alteration of the criteria weights, the applicability of the method to a range of MCDA techniques and the identification of the most critical criteria weights. The existing and proposed methods are applied to three case studies and the results indicate that simultaneous consideration of the uncertainty in the criteria weights should be an integral part of the decision making process.     

Systematic regional planning for multiple objective natural resource management

On-ground natural resource management actions such as revegetation and remnant vegetation management can simultaneously affect multiple objectives including land, water and biodiversity resources. Hence, planning for the sustainable management of natural resources requires consideration of these multiple objectives. However, planning the location of management actions in the landscape often treats these objectives individually to reduce the process and spatial complexity inherent in human-modified and natural landscapes. This can be inefficient and potentially counterproductive given the linkages and trade-offs involved. We develop and apply a systematic regional planning approach to identify geographic priorities for on-ground natural resource management actions that most cost-effectively meet multiple natural resource management objectives. Our systematic regional planning approach utilises integer programming within a structured multi-criteria decision analysis framework. Intelligent siting can capitalise on the multiple benefits of on-ground actions and achieve natural resource management objectives more efficiently. The focus of this study is the human-modified landscape of the River Murray, South Australia. However, the methodology and analyses presented here can be adapted to other regions requiring more efficient and integrated planning for the management of natural resources.     

Adaptive management on the central Platte River--science, engineering, and decision analysis to assist in the recovery of four species

Active adaptive management is the centerpiece of a major species recovery program now underway on the central Platte River in Nebraska. The Platte River Recovery Implementation Program initiated on January 1, 2007 and is a joint effort between the states of Colorado, Wyoming, and Nebraska; the U.S. Department of the Interior; waters users; and conservation groups. This program is intended to address issues related to endangered species and loss of habitat along the Platte River in central Nebraska by managing land and water resources and using adaptive management as its science framework. The adaptive management plan provides a systematic process to test hypotheses and apply the information learned to improve management on the ground, and is centered on conceptual models and priority hypotheses that reflect different interpretations of how river processes work and the best approach to meeting key objectives. This framework reveals a shared attempt to use the best available science to implement experiments, learn, and revise management actions accordingly on the Platte River. This paper focuses on the status of adaptive management implementation on the Platte, experimental and habitat design issues, and the use of decision analysis tools to help set objectives and guide decisions.     

Multiattribute Utility Analysis as a Framework for Public Participation in Siting a Hazardous Waste Management Facility

This paper describes a public participation exercise in which stakeholders used an approach based on multiattribute utility analysis to select a site for a hazardous waste management facility. The key to success was the ability to separate and address two types of judgments inherent in environmental decisions—technical judgments regarding the likely consequences of alternative choices and value judgments regarding the importance or seriousness of those consequences. The approach enabled technical specialists to communicate the essential technical considerations and allowed stakeholders to establish the value judgments for the decision. Although rarely used in public participation, the multiattribute utility approach appears to provide a useful framework for the collaborative resolution of complex environmental decision problems.     

Integrating conflict analysis and consensus reaching in a decision support system for water resource management

The importance of shared decision processes in water management derives from the awareness of the inadequacy of traditional--i.e. engineering--approaches in dealing with complex and ill-structured problems. It is becoming increasingly obvious that traditional problem solving and decision support techniques, based on optimisation and factual knowledge, have to be combined with stakeholder based policy design and implementation. The aim of our research is the definition of an integrated decision support system for consensus achievement (IDSS-C) able to support a participative decision-making process in all its phases: problem definition and structuring, identification of the possible alternatives, formulation of participants' judgments, and consensus achievement. Furthermore, the IDSS-C aims at structuring, i.e. systematising the knowledge which has emerged during the participative process in order to make it comprehensible for the decision-makers and functional for the decision process. Problem structuring methods (PSM) and multi-group evaluation methods (MEM) have been integrated in the IDSS-C. PSM are used to support the stakeholders in providing their perspective of the problem and to elicit their interests and preferences, while MEM are used to define not only the degree of consensus for each alternative, highlighting those where the agreement is high, but also the consensus label for each alternative and the behaviour of individuals during the participative decision-making. The IDSS-C is applied experimentally to a decision process regarding the use of treated wastewater for agricultural irrigation in the Apulia Region (southern Italy).     

Choice of stakeholder groups and members in multicriteria decision models

Simplistic economic objectives such as maximisation of producer profits are of little relevance in generating information to assist in the management of natural resources beyond the individual firm level. To provide data and information to support decision-making in natural resource management, it is necessary to take into account the views of various stakeholder groups and the multiple objectives of each group, through the use of some form of multicriteria analysis (MCA). Important decisions arise in the choice of stakeholder, since this will influence the management advice generated. Many groups and individuals can be affected by resource management decisions, but it would be impractical to attempt to identify the objectives and estimate their importance for each group. Also, questions arise concerning whether or not to include government agencies (which represent the broader community) and researchers as stakeholders. A further issue concerns choosing representative samples of stakeholder groups, from which to obtain preference data. Discussions with modellers and a reading of the literature would suggest that the choice of stakeholder groups and representatives is conducted haphazardly and is perhaps biased, and that a more systematic approach is needed. This article explores the above issues with reference to a number of multicriteria analyses, including local studies.     

Multi-criteria decision analysis for the optimal management of nitrate contamination of aquifers

We present an integrated methodology for the optimal management of nitrate contamination of ground water combining environmental assessment and economic cost evaluation through multi-criteria decision analysis. The proposed methodology incorporates an integrated physical modeling framework accounting for on-ground nitrogen loading and losses, soil nitrogen dynamics, and fate and transport of nitrate in ground water to compute the sustainable on-ground nitrogen loading such that the maximum contaminant level is not violated. A number of protection alternatives to stipulate the predicted sustainable on-ground nitrogen loading are evaluated using the decision analysis that employs the importance order of criteria approach for ranking and selection of the protection alternatives. The methodology was successfully demonstrated for the Sumas-Blaine aquifer in Washington State. The results showed the importance of using this integrated approach which predicts the sustainable on-ground nitrogen loadings and provides an insight into the economic consequences generated in satisfying the environmental constraints. The results also show that the proposed decision analysis framework, within certain limitations, is effective when selecting alternatives with competing demands.     

Evaluating water quality investments using cost utility analysis

This study borrows concepts from healthcare economics and uses cost utility analysis (CUA) to select an optimum portfolio of water quality enhancement projects in Perth, Western Australia. In CUA, costs are handled via standard discounted cash flow analysis, but the benefits, being intangible, are measured with a utility score. Our novel methodology combines CUA with a binary combinatorial optimisation solver, known as a 'knapsack algorithm', to identify the optimum portfolio of projects. We show how water quality projects can be selected to maximise an aggregate utility score while not exceeding a budget constraint. Our CUA model applies compromise programming (CP) to measure utility over multiple attributes in different units. CUA is shown to provide a transparent and analytically robust method to maximise benefits from water quality remediation investments under a constrained budget.     

Initial decision analysis (IDA): a participatory approach for developing resource policies

Initial decision analysis (IDA) is a microcomputer based decision-making technique that is organized so that a rational, step-by-step, procedure can be followed to use existing knowledge to develop resource policies. The IDA process provides a systematic way for participants to define their own problem and to explore jointly alternative solutions. IDA is particularly suited to resolving complex problems involving many groups with conflicting interests. IDA is illustrated with data from the US Forest Service's Draft Environmental Impact Statement for the 1985 to 2030 Resource Planning Act Program for the United States. Four policy options are evaluated: maximization of timber production, of grazing, and of wilderness, and a dominant use policy that concentrates timber management on productive sites. Policies were evaluated using a new mathematical satisficing procedure. Mathematical satisficing of simulated policy consequences showed that, for selected performance standards, current RPA policies are superior to the four alternative policies examined.     

Farmer decision making and spatial variables in northern Thailand

This research has two interrelated objectives. The first is to determine the extent to which a relationship exists between farmer characteristics and farming practices in three villages in northern Thailand. The second is to use standard statistical methods for incorporating spatial variables into the analysis and to assess the effects of these variables on farmer decision making. The data base includes information on the location and size of villages, roads, streams, and fields; a digital elevation model with information on elevation, slope, and aspect; and information keyed to individual fields on crops and cropping methods and the ethnicity, income, and religion of farmers. The map data (517 plots) were entered into a computerized geographic information systems (GIS). Results suggest several hypotheses about the relationships between land use and owner characteristics. More significantly, the study concludes that spatial analysis appears to be most useful when the dependent variable is either continuous or ordinal. The outlook is not quite as optimistic when the dependent variable is a nonordinal categorical variable. Before spatial analysis can be applied regularly to social science data, better computational tools need to be developed.     

Uncertainty and risk in wildland fire management: a review

Wildland fire management is subject to manifold sources of uncertainty. Beyond the unpredictability of wildfire behavior, uncertainty stems from inaccurate/missing data, limited resource value measures to guide prioritization across fires and resources at risk, and an incomplete scientific understanding of ecological response to fire, of fire behavior response to treatments, and of spatiotemporal dynamics involving disturbance regimes and climate change. This work attempts to systematically align sources of uncertainty with the most appropriate decision support methodologies, in order to facilitate cost-effective, risk-based wildfire planning efforts. We review the state of wildfire risk assessment and management, with a specific focus on uncertainties challenging implementation of integrated risk assessments that consider a suite of human and ecological values. Recent advances in wildfire simulation and geospatial mapping of highly valued resources have enabled robust risk-based analyses to inform planning across a variety of scales, although improvements are needed in fire behavior and ignition occurrence models. A key remaining challenge is a better characterization of non-market resources at risk, both in terms of their response to fire and how society values those resources. Our findings echo earlier literature identifying wildfire effects analysis and value uncertainty as the primary challenges to integrated wildfire risk assessment and wildfire management. We stress the importance of identifying and characterizing uncertainties in order to better quantify and manage them. Leveraging the most appropriate decision support tools can facilitate wildfire risk assessment and ideally improve decision-making.     

Development of a decision support system for Prioritization of multimedia dischargers

In 1990 the Environmental Protection Agency (EPA) began sponsoring several pilot projects in its regional offices to examine the potential benefits of adopting a multimedia approach to facility management. This approach differs from traditional practices at EPA in that facilities (dischargers regulated under permits issued by the agency) are managed based upon their cumulative impacts to all media: air, water, and land. Currently, facilities are managed by separate programs at EPA that evaluate environmental impacts from a single-media perspective. One aspect of discharger management is the necessity to allocate limited financial resources in a way that will minimize risk to human health and the environment. A careful, risk-based prioritization of facilities is one means of providing insight to the most effective strategy of allocating monitoring, inspection, and enforcement resources. Prioritization from a multimedia perspective is particularly difficult, however, since it requires translation and integration of medium-specific facility performances, management objectives, and perceptions of risk into a cumulative rating. A computerized decision support system (DSS) designed to guide management through the prioritization process from a multimedia perspective was identified as a potentially valuable tool for use in the pilot projects. This article describes the development of such a prototype, outlines the features of the completed system, and discusses its potential for use at EPA.     

Public reaction to the risks of energy technology

Implicit in every government decision on energy technology is a trade-off of a certain amount of risk in return for societal benefits. As a result of growing public concern over such risks, environmental analysts are increasingly being requested not only to describe potential adverse consequences but also to quantify their probability. However, this task is frustrated not only by inadequate experience with, and incomplete knowledge of, the causality of environmental impacts, but also by a disparity between individual and societal views of risk. While the societal view is based on objective risk functions andnet societal benefit, individuals tend to rely on subjective judgment, and consider the distribution as well as the amount of benefit. Thus, environmental risk assessments, produced by analysts on behalf of society as a whole, are likely to be quite speculative, and are unlikely to be reliable indicators of the acceptability of risk to the public.