Abstract
The ultimate goal of environmental impact assessment is to guarantee that benefits generated by a development project will not cause highly negative effects on the environment or public health. The fulfillment of this goal depends on the willingness of proponents and society to cooperate. The information management, its accessibility to community and the educational level of participants are of great relevancy too. Cooperation is not always attainable due to conflicts between individual and community interests. Conflict leads to a variety of cooperative and non-cooperative responses, depending on the information available to the actors. In order to capture the tendency in which a community perceives the proposals, we introduced an information index. We prove that computer models have a direct impact on this information index. This computer-based approach, leads the EIA to the paradigm of adaptive environmental assessment and management. To implement this, a system based on artificial intelligence and game theory was used to resolve a study case of conflict in groundwater management.
Highlights
Societies have become more participate and aware of the effects that the environment suffers as a consequence of development projects
That is a second benefit of Pareto solutions, for having a wider range of solutions provides a great opportunity to negotiate in case some users show themselves reluctant to cooperate with the optimal solutions
In each case EIAs are regulated under norms and rules enforced by a central authority who decides whether the implementation of a project is suitable or not, based on environmental, economic and social terms
Summary
Societies have become more participate and aware of the effects that the environment suffers as a consequence of development projects. Given the intrinsic quality of EIA as a forum for public participation, and as a consensus tool for decision making, it is regarded as a valuable route to sustainability (Lawrence, 1997) It is considered the best control option for projects that cannot be regulated through legal standards or land use plans (Pérez-Maqueo, 2004). In the IA of very complex systems, such as climate change or groundwater, computer models are the dominant means of scientific knowledge production They have demonstrated suitability to accomplish a common understanding of environmental-social problems, analyze the causes and impacts of the problems, explore and examine management options and support the formulation of objectives and restricttions (Tuinstra et al, 1999; Hisschemller et al, 2001). Even in more simple systems, compared to human experts, computer models are often reckoned as more comprehensive and reliable, which usually improve the perception that society has of a project (Siebenhner, 2004)
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