dc.contributor.author |
El Nakib, Sania Khaled |
dc.date.accessioned |
2018-10-11T11:43:15Z |
dc.date.available |
2018-10-11T11:43:15Z |
dc.date.copyright |
2021-05 |
dc.date.issued |
2018 |
dc.date.submitted |
2018 |
dc.identifier.other |
b21173874 |
dc.identifier.uri |
http://hdl.handle.net/10938/21462 |
dc.description |
Thesis. M.S.E.S. American University of Beirut. Interfaculty Graduate Environmental Sciences Program, (Environmental Technology), 2018. ET:6833$Advisor : Dr. Ibrahim Alameddine, Assistant Professor, Civil and Environmental Engineering ; Members of Committee : Dr. May Massoud, Associate Professor, Environmental Health ; Dr. Majdi Abou Najm, Assistant Professor, Civil and Environmental Engineering. |
dc.description |
Includes bibliographical references (leaves 55-59) |
dc.description.abstract |
Rivers are increasingly being subjected to increased anthropogenic pollution stresses that undermine their designated-uses and negatively affect sensitive coastal regions. The degradation of river water quality can be attributed either to point or non-point sources of pollution. While most developed countries have successfully reduced their point source loads and are now focused on managing their non-point sources, developing countries are still struggling with both types of pollution. In this study, we determine the relative contribution of point and non-point pollutant loads in the Beirut River basin, a poorly monitored seasonal Mediterranean river. Water quality samples were collected over two consecutive years (2016 and 2017) from four sampling sites that represent a gradient of increased urbanization. The spatio-temporal variability of the physio-chemical and biological pollution levels were analyzed in an effort to better understand the relative contribution of point and non-point pollution sources. Flow-concentration statistical models were then developed to estimate the total nutrient and sediment loads reaching the different river segments. Loads were also estimated using the Beale’s ratio method and compared with the loads generated from the regression-based models. Non-point source loads were also quantified using the Geographic Information System (GIS) enabled Open Nonpoint Source Pollution and Erosion Comparison Tool (OpenNSPECT). The model accounts for the landuse-landcover, overland flow, soil types, and adopted land-management practices in the river basin. Results showed significant seasonal variability in pollution levels across the river basin and a high correlation between the measured pollution loads and the measured river flows. Spatially, pollution levels appeared to correlate well with the urbanization levels observed all along the Beirut River watershed. Model results showed that point sources were the main cause of water quality impairment across the entire basin. The adopted model |
dc.format.extent |
1 online resource (x, 59 leaves) : illustrations (some color) |
dc.language.iso |
eng |
dc.subject.classification |
ET:006833 |
dc.subject.lcsh |
Water -- Pollution -- Lebanon -- Beirut.$Water quality -- Lebanon -- Beirut.$Water -- Environmental aspects -- Lebanon -- Beirut |
dc.subject.lcsh |
Beirut River (Lebanon) |
dc.title |
Pollutant load estimation for river management strategies : a case study of Beirut River |
dc.type |
Thesis |
dc.contributor.department |
Interfaculty Graduate Environmental Sciences Program, (Environmental Technology) |
dc.contributor.faculty |
Faculty of Engineering and Architecture |
dc.contributor.institution |
American University of Beirut |