野外砾石统计方法的应用与对比

砾石对于研究构造活动和气候变化具有重要意义，而砾石粒径是其中的重要参数，如何准确地获取粒径数据则是砾石统计分析中的基础性工作。为了能更全面地了解和使用砾石统计方法，对地表砾石统计和地层砾石统计这2种方法从操作流程、抽样过程、样本容量、误差分析和适用条件等方面进行了分析和总结。地表砾石统计，主要有沃尔曼法和面积样本法，前者强调抽样的随机性，多适用于对粒径>2 mm砾石的统计，常用于研究砾质河床的砾石粒径顺流变化趋势；后者适用的粒径范围更广，可达细砂级沉积物，多用于探索河床砾-砂转换带和生物栖息环境划分等领域。地层砾石统计，大多使用体积样本法，强调砾石的成层性，可根据研究目的确定相应的网格筛，粒径范围也可达细砂级别，多用于沉积地层粒度对气候与构造的响应、河床监测和泥沙运移等方面。砾石统计方法的选择很大程度上取决于研究目的及野外工作条件，可根据实际情况灵活选择。

Application and comparison of field gravel statistical methods

Studies about natural gravels are significant for understanding of regional tectonics and climate change, and especially the gravel size is an important parameter in geology. To provide users with a more comprehensive understanding and application background of gravel statistical methods, we summarize two types of gravel statistical methods (surface gravel statistics methods and stratigraphic gravel statistics methods) with the operation of gravel statistical methods, sampling process, sample size, error analysis, and applicable conditions. The surface gravel statistics methods usually include the Wolman pebble count and area sampling. The Wolman pebble count emphasizes random sampling and is more suitable for gravel diameter larger than 2 mm to study the downstream fining of sediment in gravel-bed rivers. The area sampling is mostly used to explore natural phenomena of the gravel-sand transition in rivers and the characteristic of aquatic habitats due to its suitable gravel size range up to fine-grained sand. In contrast, the stratigraphic gravel statistics methods emphasize the stratification of gravel and apply the volumetric sampling. Previous researchers developed several kinds of mesh sieves based on corresponding research purposes. And the gravel size range can also reach to fine sand, which is most suitable for studying the response of gravel grain sizes to climate and tectonics, streambed monitoring and sediment transport analysis. This comprehensive study of the gravel statistical methods indicates that the choice of different methods largely depends on the research purpose and field working conditions which suggests us to make flexible selection based on specific situations.