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一种多变量统计方法和水质指数用于评估塞拉利昂罗克尔河的水质
A Barrie1, S K Agodzo2, R Frazer-Williams3
1Regional Water and Environmental Sanitation Centre Kumasi (RWESCK), Department of Civil Engineering, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana.
Heliyon
|July 24, 2023
概括
这项研究使用多变量统计分析了水质,揭示了季节性变化,并确定了超出安全饮用水准则的和化物等参数. 这些发现表明,尽管特定污染物的含量较高,但一些水源在处理后适合供应.
科学领域:
- 环境科学 环境科学
- 评估水质水质的评估.
- 多变量统计学 多变量统计学
背景情况:
- 水质对于公众健康和生态系统稳定至关重要.
- 了解季节性变化和参数相关性是有效水资源管理的关键.
- 多变量统计方法为复杂的水质数据分析提供了可靠的方法.
研究的目的:
- 应用多变量统计方法来评估水质.
- 确定影响雨季和干季水质的因素.
- 为了分组和解释生理化学和微生物水质参数.
主要方法:
- 收集两个季节 (2019年6月至8月,2019年2月至4月) 的生理化学和微生物数据.
- 使用主要成分分析 (PCA),水质指数 (WQI),集群分析和差异分析 (ANOVA) 的分析.
- 使用凯泽-梅耶-奥尔金和巴特利特测试测试了采样充分性.
主要成果:
- 五个主要组成部分解释了总差异的82.628%.
- 最大WQI表示等级A,适合供应的水.
- ,铁,度,酸盐和化物超过了世卫组织饮用水准则.
- 度,TDS,TSS,铁,酸盐,化物和硫酸盐显示出显著的季节性变化 (p < 0.05).
结论:
- 多变量分析提供了水质来源和参数相关性的详细描述.
- 季节性变化对几个关键的水质参数产生重大影响.
- 虽然一些水是可处理的供应,高污染物水平需要仔细管理和监测.
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