...
首页> 外文期刊>Environmental Monitoring and Assessment >Characterization of spatial and temporal patterns in surface water quality: a case study of four major Lebanese rivers
【24h】

Characterization of spatial and temporal patterns in surface water quality: a case study of four major Lebanese rivers

机译:地表水水质的时空分布特征:以黎巴嫩四大河流为例

获取原文
获取原文并翻译 | 示例
           

摘要

In this work, four major Lebanese rivers were investigated, the Damour, Ibrahim, Kadisha, and Orontes, which are located in South, Central, and North Lebanon and Bekaa Valley, respectively. Five sampling sites were considered from upstream to downstream, and 12 sampling campaigns over four seasons were conducted during 2010-2011. Thirty-seven physicochemical parameters and five microbial tests were evaluated. A principal component analysis (PCA) was used for data evaluation. The first PCA, applied to the matrix-containing data that was acquired on all four rivers, showed that each river was distinct in terms of trophic state and pollution sources. The Ibrahim River was more likely to be polluted with industrial and human discharges, while the Kadisha River was severely polluted with anthropogenic human wastes. The Orontes and Damour rivers seemed to have the lowest rates of water pollution, especially the Orontes, which had the best water quality. PCA was also performed on individual data matrices for each river. In all cases, the results showed that the springs of each river have good water quality and are free from severe contamination. The other monitoring sites on each river were likely exposed to human activities and showed important spatial evolution. Through this work, a spatiotemporal fingerprint was obtained for each studied river, defining a "water mass reference" for each one. This model could be used as a monitoring tool for subsequent water quality surveys to highlight any temporal evolution of water quality.
机译:在这项工作中,调查了黎巴嫩的四个主要河流,达莫尔河,易卜拉欣河,卡迪沙河和奥龙特斯河,它们分别位于黎巴嫩南部,中部和北部以及贝卡谷地。从上游到下游考虑了五个采样点,并且在2010-2011年期间进行了四个季节的12个采样活动。评估了37个理化参数和5个微生物测试。主成分分析(PCA)用于数据评估。将第一条PCA应用于在所有四条河流中获取的包含矩阵的数据,结果表明,每条河流在营养状态和污染源方面都是不同的。易卜拉欣河更容易受到工业和人类排污的污染,而卡迪沙河则受到人为污染的严重污染。奥龙特斯河和达莫尔河的水污染率似乎最低,尤其是奥龙特斯河的水质最好。 PCA还在每个河流的单独数据矩阵上执行。在所有情况下,结果都表明,每条河流的泉水水质都很好,没有严重的污染。每条河上的其他监测点都可能受到人类活动的影响,并显示出重要的空间演变。通过这项工作,获得了每条研究河流的时空指纹,为每条河流定义了“水质参考”。该模型可以用作后续水质调查的监测工具,以突出显示水质的任何时间变化。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号