Collaborative Environmental Decision-Making: An Integrative Approach

Dr. Steven P. Frysinger
AT&T Bell Laboratories

As the complexity of our environmental management problems has increased, so has the need to apply the information management potential of computing technology to help environmental decision makers with the difficult choices facing them. Environmental information systems have already taken many forms, with most based upon a relational database foundation. Such systems have helped greatly with the day-to-day operations of environmental management, such as chemical and hazardous waste tracking and reporting, but they have two critical shortcomings which have prevented them from significantly improving the lot of environmental scientists and planners tackling more strategic decisions.

Traditional environmental information systems (1) ignore the crucial spatial context of virtually all environmental management problems, and (2) offer little or no support for the dynamics of environmental systems. Fortunately, a relatively new category of system, called an Environmental Decision Support System (EDSS), shows real promise in both of these areas.

Environmental Decision Support Systems are computer systems which help humans make environmental management decisions. They facilitate "Natural Intelligence" by making information available to the human in a form which maximizes the effectiveness of their cognitive decision processes.

The most effective EDSSs are focused on specific problems and decision makers. This sharp contrast with the general purpose character of such software systems as Geographic Information Systems (GIS) is essential if we are to put and keep EDSSs in the hands of real decision makers who have neither the time nor inclination to master the operational complexities of general purpose systems. Indeed, it can be argued that most environmental specialists are in need of computer support which provides everything that they need, but only what they need.

The development of environmental policies and generation of environmental management decisions is currently, to a large extent, an "over the counter" operation. Technical specialists are consulted by policy and decision makers (who may or may not have a technical background), to assist in gathering information and exploring scenarios. Because of the inaccessibility of data and modeling tools, decision makers must consult with their technical support personnel with each new question, a time-consuming and inefficient process. Since environmental decisions typically involve at least two parties (e.g. the regulator and the regulated), this process is further degraded by traditional non-interactive technical negotiating methods.

If the data and analytical tools could be placed within reach of the decision makers, they would be able to consult them more readily, and would therefore be more likely to base their decisions upon a technical foundation. Negotiating parties could collaborate on the refinement of modeling assumptions and approaches, encouraging the development of a mutually-agreeable compromise among technical alternatives. This is the premier reason why Environmental Decision Support Systems, of a sort described in part herein, are necessary if we are to achieve a higher quality in our environmental management decisions and obtain more protection with our finite resources.

The focused nature of EDSSs dictates a software architecture which facilitates the development of sibling systems embracing different decision problems with an essentially common user and data interface. Environmental Decision Support Systems address a problem domain of remarkable breadth. The character of environmental decisions, and the fundamental issues surrounding them, are central to the design of a successful EDSS.

To understand environmental management decisions, we must first identify the decision makers. The stereotypical image of an environmental manager is a technically trained agent of a governmental regulatory body, and many decision makers indeed fit this description. However, these individuals also have their counterparts in the regulated arena (such as industrial environmental engineers). Furthermore, critical environmental decisions are made in the context of policy formation, and therefore involve both elected and appointed officials, as well as the members of the public whom they represent. Naturally, the level of expertise these individuals possess in any given technical area is highly variable. Nonetheless, all of them can and do make critical environmental decisions; it is therefore incumbent upon the toolbuilders - including EDSS architects - to craft systems and processes which help to bridge the gap between technical expertise and the decision maker, so that the benefits of this expertise may be realized.

Environmental decision makers are clearly a diverse group of people faced with a diverse group of problems. The breadth of their problem domain, in fact, defines the need for eclectic individuals with tools to match. The diversity of these characteristics of the problem domain make effective environmental decision support extremely challenging.

Because of these factors, it is not practical to contemplate a generic decision framework for environmental management. Even if it were possible to capture all of the elements necessary to consider the great variety of decisions to be undertaken, the system so built would be virtually unusable. The environmental manager is already confronted with a vastly complex problem space; one of the first jobs of the decision support system is to simplify this space, offering them everything that they need to make the decision at hand - but only those things.

Therefore, while our definition of EDSS includes the integration of multiple supporting technologies (such as modeling and GIS), we further restrict this definition to stipulate that EDSSs are focused on a particular decision problem and decision maker. Thus, they are not general purpose tools with which anything can be done (if only you knew how to do it). Rather, they are particularly tailored to the problem facing the analyst, and offer a user interface which is optimized for this problem.

The focused nature of such EDSSs improves the user's interface to the computer system, allowing the user to concentrate on the problem at hand and the information and tools needed to solve it. It also dictates a software architecture that facilitates the development of sibling systems embracing different decision problems with an essentially common user and data interface (Frysinger et al 1993a, Frysinger et al 1993b, Frysinger 1995). Such a family of focused EDSS siblings offers user interface simplicity, in that the siblings share interaction style, organization, and fundamental approaches (where appropriate), while maintaining the focus each sibling has on its particular decision problem.

Environmental management is fundamentally about risk. Risk, in turn, may be regarded as the probability that an adverse outcome will occur in persons exposed to a hazard (Paustenbach 1989). The hazards in question may relate to the threat of loss or perturbation of portions of our natural environment - ecological risk - or to (more direct) threats to human health and quality of life. Risks may be described in terms of several other properties or characteristics besides the human/ecological dichotomy. Risks may be occupational or visited upon the population at large, and they may be voluntary or involuntary. They may be short-term or long-lasting, and may occur frequently or rarely. They may arise from natural causes or as a result of human actions, and their consequences may include injury, illness, or death, to name a few. Naturally, such categories only represent points on a continuum; some risks are more voluntary than others, for example. Many environmental management actions are taken without explicit consideration of risk.

For example, efforts to preserve open space in the course of land use planning rarely involve explicit discussion of the health or ecological risks associated with development. But the very fact that these actions are elected implies some concern for the consequences of not acting. The individuals exerting themselves toward such ends may not have an understanding of the currency of risk assessment, and may be ill-prepared to discuss, much less quantify, the particular variables of the issue. Nonetheless, they are acting in response to an intuitive sense that there is some risk which ought to be mitigated. Environmental Decision Support Systems have considerable potential to help these decision makers to more rigorously account for the risks associated with the decision problem at hand by providing them with tools and information, as well as expertise integrated into the design of the system.

The focused approach to EDSS design advocated here dictates the use of a human factors engineering technique, called task analysis, to support the specification of a particular EDSS for a particular problem.

As defined in the human factors community, "...task analysis breaks down and evaluates a human function in terms of the abilities, skills, knowledge and attitudes required for performance of the function" (Bailey 1982). The EDSS designer must endeavor to understand the decision problem, and all of the factors which must be considered in solving it. In addition, the "social history" of the problem must be understood, since there will (in general) already be a number of different approaches to solving a given environmental management problem. For a system to support an analyst in arriving at a credible decision, the various competing approaches must be considered, and possibly accommodated.

A major stumbling block in task analysis is the fact that very few individuals can accurately explain the way in which they actually arrive at a particular decision. They can tell you how they think they should do it, and they can often develop a post hoc analytical rationale for their decision, but people are generally unaware of the actual process by which they make decisions. Thus, other instruments must be used to understand the decision process, ranging from observation and interview up through controlled experimentation to determine the influence of different variables on decisions.

In the environmental area, this is further complicated by the fact that there are often guidelines or regulations dictating the way in which decisions are supposed to be made about a particular problem. These do indeed dictate certain aspects of the process, but often leave a great deal unspecified. For example, the United States' Resource Conservation and Recovery Act (RCRA) requires that a waste facility be monitored by a network including at least one upgradient and three downgradient wells in order to assure that no hazard to the public health results from the facility. However, though the legislature was specific about this detail, they made little effort to assist the manager in deciding where or how many (above four) wells are to be installed. Furthermore, the language of the act would suggest that certainty is required with respect to the detection of leaks, though no reasonable person would argue that this is either theoretically or economically achievable. Considerable interest has been shown in computer-based quantitative decision support for this problem (Frysinger et al 1992, Frysinger and Parsons 1992).

Biographical Sketch:
Steven P. Frysinger

Research Interests:

Environmental decision support systems and information systems, Environmental modeling, Environmental systems engineering, Exposure risk assessment, Remote sensing for environmental analysis, Risk perception and communication, Scientific audification and visualization of spatial and time-series data.


Research and Development Experience:

Other Relevant Experience:

Selected Publications and Presentations:

Environmental Decision Support Systems and GRASS: A Sandia Monitor Well Case Study. S.P. Frysinger, R. Cox, P. Davis, and A. Parsons. In G.S. Waggoner (Ed.) Geographic Information Systems: Proceedings of the Seventh Annual GRASS User's Conference;, National Park Service NPS/NRGISD/NRTR-93/13, March 1992, pp. 117-121.

A Decision Support System for Evaluating the Performance of a Monitor Well Network.S.P. Frysinger and A.M. Parsons. In Environmental Geotech Symposium (American Society of Civil Engineers) , September 1992.

Treatment of Human-Computer Interface in a Decision Support System. A.S. Heger, F.A. Duran, S.P. Frysinger, and R.G. Cox. In IEEE International Conference on Systems, Man, and Cybernetics , October 1992.

Hydrological Modeling and GIS: the Sandia Environmental Decision Support System. S.P. Frysinger, R.P. Thomas, and A.M. Parsons. In K. Kovar and H.P. Nachtnebel (editors), Applications of Geographic Information Systems in Hydrology and Water Resources Management - Proceedings of HydroGIS 93 , IAHS Press, April 1993.

Auditory Data Representation: A Review with Applications to Spatial Information Processing. S.P. Frysinger. An invited presentation in J. Dorn (Chair), Summer Workshop of the Society of Exploration Geophysicists, August 1993.

Environmental Decision Support Systems: An Open Architecture Integrating Modeling and GIS. S.P Frysinger, D.A. Copperman, and J.P. Levantino. In Proceedings of the Second International Conference on Integrating Geographic Information Systems and Environmental Modeling , NCGIA, September 1993.

An Environmental Decision Support System for Local Wellhead Protection. S.P Frysinger and C.G. Uchrin. In Proceedings of Decision Support 2001 , September 1994.

An Open Architecture for Environmental Decision Support. S.P. Frysinger. International Journal of Microcomputers in Civil Engineering , Vol. 10, No. 2, 1995.