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

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.

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