Sustainable approach to environmental resource management requires comprehensive assessment of ecosystems state and its changes that may occur as a result of anthropogenic impact. Environmental assessment always deals with observation data. Models transform these data into information which forms a basis for sustainable decision making. Selection of representative data sets and appropriate models is always a concern for researchers and practitioners in the area of anthropogenic impact assessment. Data and models are interrelated. Their interdependence determines model utilization for a particular application and the quality of information generated by the model. Models impose specific requirements on data sets. In many cases, criteria of environmental assessment are formulated based on available observation data, but not from the needs of the decision makers. Thus, environmental data become a limiting factor of the selection of a model appropriate for sustainable decision making. The paper examines data-model interdependence and demonstrates how model properties can be used to suggest a feasible approach to acquire representative data sets for environmental impact assessment.
|Keywords:||Environmental Resource Assessment, Decision Making, Environmental Models, Model Uncertainty, Monitoring Design|
Assistant Professor, Atkinson Faculty of Liberal and Professional Studies, York University, Toronto, Canada
Atkinson Faculty of Liberal and Professional Studies, York University, Canada
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