Dynamic, Multi-Perspective and Multi-Scale Risk Assessment of Mining Projects under Tropical Climate, in both their Geoscientific and Social Dimension
Résumé
Mining activities in tropical regions might be the source and the target of multiple risks. The peculiar climatic conditions are the main reasons of their complexity and their interactions with the human and natural environment need to be considered carefully. Risk factors vary according to internal and external conditions of mining projects and can have different nature (geotechnical, environmental, socioeconomic , etc.). Since they are interdependent, they can't be treated separately. Despite the availability of many tools for risk assessment, none of them is specific enough to be applied to mining projects. Thus, the development of an adapted methodology is a priority for land planning and major decision-making processes. The intent of this paper is to develop a methodology for a dynamic, multi-perspective, and multi-scale risk assessment of mining projects under tropical climate. French Guyana has been chosen as the study area, because of the variety of mining exploitations and the multiple challenges at stake. In a first step, a database of common risk factors of mining projects is developed thanks to interviews, literature reviews and expert feedbacks. The identified risk events are then categorized based on their nature and their corresponding project phases. Regarding the specificities of our case study, geotechnical, environmental and social risks have been selected for a detailed assessment based on the available data and those obtained through satellite images, remote-sensing and other techniques. The development of such a methodology consent to analyze the interaction between the risk events and their spatio-temporal variability in the studied context. Thence, the adaptability of this tool assures an efficient support to decision-making processes. In a further step, the obtained results will be mapped through GIS tools and coupled with land-use and demographic data so to assess risk levels by considering the potential consequences and vulnerability of the elements at risk.