GMEG - Mineral Resources
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This project uses complex systems modeling as a unifying concept to undertake a spectrum of geoscience related problems including geologic factors of non-point source pollution; human and animal diseases controlled by geologic factors; genesis, life cycle, environmental, and socio-economic factors of ore deposits; and factors controlling the distribution of physical and chemical transport properties. The project goals are to create a general framework for solving problems that can include political, economic, social, and ecological factors in addition to traditional factors from the physical sciences (e.g. temperature, stress field, depth of burial) and to apply the framework to several geoscience problems.
We will attack several problems using complex systems theory organized into five tasks. The tasks are:
Scientists from Water Resources and Biological Resources Disciplines will participate in some project tasks. The tasks cover a diverse suite of subjects but are related to each other in multiple ways. Geographically, the project will focus on a zone around the margin of selected basins. This zone includes some bedrock of the bounding ranges and the shallower parts of the basin (generally, fill depth of 1 km or less). These areas are termed basin marginal zones (basin margins for short) and include the lithologies and structures of interest, as the central part of the basins are generally too deep to be resolved and the cores of the ranges are usually devoid of deposits. In most cases the important structures geologically are those associated with the basin margin.
Modern complex modeling theory combined with the significant advances in computer capacity to process large amounts of data and produce complex visualizations in two and three dimensions provides an opportunity to explore new models of geoscientific processes and their connections to the ecosystem. By integrating fuzzy logic theory with that of complex systems modeling, it is now possible to include links in the models to related or constraining processes such as economic factors, social attitudes, and urbanization effects and to evaluate the impact of these links and their effects over time on the model. Once such a model is produced and validated, it can be used to make forward projections and predictions based on various scenarios. The model may evolve dynamically with changing or newly added links or effects. It should be possible to include and evaluate the effects of factors which have been traditionally difficult to evaluate such as environmental impact.
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