| 摘要: |
| 土壤重金属合理采样数目确定和空间变异特征分析是进行土壤重金属相关研究工作的前提和基础，为评估土壤重金属混合样采样数目和空间变异研究进展，通过广泛查阅国内外相关文献，对土壤重金属混合样本数、混合样分样点数目、组间及组内误差与空间变异耦合规律现状及未来研究方向进行了评述。结果表明：目前，已有研究只关注于已知变异单元内正态分布下混合样采样数目的确定，对于已提出的偏态分布下合理采样数目确定方法，均存在着采样数目高估或者低估现象，而且只关注于混合样点合理采样数目确定方法研究；针对不同的误差控制需求、正态或偏态分布、已知或未知变异单元，确定土壤重金属混合样本数及混合样分样点数目方法研究尚未开展；对于采样数据符合偏态或正态分布下，增加土壤混合样、混合样分样点数目与组间误差、组内误差降低趋势关系拐点尚不清楚；土壤重金属混合样本及混合样分样点数目与空间变异耦合规律也尚不明确。因此，识别增加土壤混合样、混合样分样点数目与组间误差、组内误差降低趋势关系的拐点，优化土壤重金属混合样本数、混合样分样点数与土壤重金属总体采样数目的关系，结合空间变异预测模型，构建样本量计算和空间变异识别的耦合模型，揭示土壤重金属混合样本数及混合样分点数与空间变异耦合规律是未来土壤重金属采样数据质量提高及田间采样决策的关键。 |
| 关键词: 土壤重金属 空间变异 采样数目 耦合规律 模型 |
| DOI：10.11841/j.issn.1007-4333.2024.02.05 |
| 投稿时间：2023-07-03 |
| 基金项目:生态环境部环境发展中心科技发展基金项目（RZXJJ-20227） |
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| Research progress on coupling regularity between composite sampling numbers and spatial variations of soil heavy metals |
|
HUANG Yajie, CUI Yanzhi, ZHOU Yan, LI Junchao, BIAN Huafeng, LIU Haidong*
|
| (Environmental Development Center of the Ministry of Ecology and Environment， Beijing 100029， China) |
| Abstract: |
| Determining the optimum sampling numbers and analyzing spatial variation characteristics of heavy metals in soil are the premise and foundation for the survey of heavy metals in soil. This study aims to assess the research of sampling numbers and spatial variation of heavy metals in soil. Based on extensive search of relevant literature published in recent years， the current situations of the coupling regularity among the sampling number （i.e. increments and composite samples）， errors （i.e. within-errors and between-errors）， and spatial variation for the survey of soil heavy metals are reviewed and future research issues are discussed in the this study. The results showed that： Previous researches were more focused on determining the numbers of composite samples by statistics under a normal distribution in the units with known variations. The methods under the log-normal distribution always overestimated or underestimated the optimum sampling numbers， and only estimated the number of composite samples. Based on different scenarios， such as different errors， normal or skewed distributions， known or unknown variations， it was not clear how to determine the optimum numbers of increments and composite samples. The trend inflection points of the relationship between increasing the number of increments and composite samples， and the decreasing of within-errors and between-errors were not clear. The coupling regularity among the number of increments， composite samples， and spatial variation of heavy metals in soil were not clear. It was concluded that exploring the aforementioned trend inflection point， and thus optimizing the relationship among increments， composite samples and overall sampling numbers of soil heavy metals were crucially important. Combined with the prediction models of spatial variation， establishing the coupled model of sampling numbers and spatial variation to reveal the coupling regularity of increments， composite samples and spatial variation could provide theoretical support to improving the data quality and making field sampling decisions of soil heavy metal. |
| Key words: soil heavy metals spatial variation sampling numbers coupling regularity model |
