川西甲基卡大型锂资源基地绿色调查及环境评价指标体系的建立
1. 自然资源部成矿作用与资源评价重点实验室, 中国地质科学院矿产资源研究所, 北京 100037; |
2. 中国地质大学(北京)地球科学与资源学院, 北京 100083; |
3. 四川省地质矿产勘查开发局地质矿产科学研究所, 四川 成都 610036; |
4. 四川省地质调查院, 四川 成都 610081 |
Study on the Index System of Green Investigation and Environmental Evaluation for the Jiajika Large Lithium Mineral Resource Base, Western Sichuan, China
1. Key Laboratory of Metallogeny and Mineral Resource Assessment, Ministry of Natural Resources;Institute of Mineral Resources, Chinese Academy of Geological Sciences, Beijing 100037, China; |
2. School of Earth Science and Resources, China University of Geosciences(Beijing), Beijing 100083, China; |
3. Geology and Mineral Resources Scientific Institute, Sichuan Exploration Bureau of Geology and Mineral Resources, Chengdu 610036, China; |
4. Sichuan Institute of Geological Survey, Chengdu 610081, China |
摘要：在资源、环境和经济协调发展的大背景下，发展绿色矿业已成为国家战略重点推进并得到广泛认同。大型资源基地绿色调查及环境评价指标体系的建立、模型的技术实现将为解决生态脆弱区找矿部署与环境保护瓶颈问题发挥重要作用。本文将绿色调查与环境评价两方面工作有机结合，分四个层次构建指标框架，通过3S技术提取生态环境现状及变化信息，结合连续3年的地表水、土壤等多环境介质野外调查取样分析数据，对经过验证的、成熟的评价方法进行优化，运用更兼容、可扩展的Python语言编程建立了基于支持向量机的大型锂资源基地环境评价模型。运用该模型，将大型基地环境现状划分为环境较差区、环境一般区、环境较好区、环境好区4类区域，总体准确率达97.77%。结果表明本文建立的这套有针对性的评价指标体系能够有效地对川西大型锂资源基地的环境现状作出较为客观的评价，通过技术创新实现了大型锂资源基地环境现状"像元级"可视化分级，较客观地反映甲基卡矿区及周边资源开发环境问题与影响范围，在一定程度上可辅助规范大型基地矿产资源开发利用的管理及决策。
Study on the Index System of Green Investigation and Environmental Evaluation for the Jiajika Large Lithium Mineral Resource Base, Western Sichuan, China
ABSTRACT BACKGROUND:Under the background of coordinated development of resources, environment and economy, the development of green mining has become a national strategic focus and has been widely recognized. Environmental investigation and evaluation is one of the main content in investigation and assessment of large lithium metallic mineral bases in Sichuan Province, which will play an important role in solving the bottleneck problems, such as prospecting deployment and environmental protection in the ecologically fragile district of the Western Sichuan Plateau.
OBJECTIVES:To put forward the green investigation method and to establish an index system of environmental evaluation and demonstration of typical mining areas.
METHODS:Green investigation and environmental assessment were combined, an indicator framework in four levels was constructed, and the status quo and change information of the ecological environment through 3S technology were extracted. Based on three years of surface water, soil and other multi-environmental media field survey and analysis data, a mature evaluation method has been optimized, and a large-scale lithium resource base environment evaluation model based on support vector machine was established by using a more compatible and scalable Python language programming.
RESULTS:Using this model, the current status of large-scale bases was divided into four categories:environmentally poor areas, general environmental areas, better environmental areas, and good environmental areas. The overall accuracy rate was 97.77%.
CONCLUSIONS:The set of a targeted evaluation index system established and reported on in this paper effectively evaluates the environmental status of large-scale lithium resource bases in Western Sichuan, and realizes the visual level of ‘pixel-level’ environmental status of large-scale lithium resource bases through technological innovation. The method objectively reflects the development and environmental impacts of the Jiajika mining area and surrounding resources, and to a certain extent, can assist in regulating the management and decision-making of the development and utilization of large-scale mineral resources.
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