Multivariate Analyses of the Effects of Land Use Change on River Water Quality: Case Study of Manawatu River Watershed, New Zealand
dc.contributor.advisor | Ikehata, Keisuke | |
dc.contributor.advisor | Jason, Julian | |
dc.contributor.author | Tenebe, Imokhai Theophilus | |
dc.contributor.committeeMember | Wang, Feng | |
dc.date.accessioned | 2022-08-01T21:04:48Z | |
dc.date.available | 2022-08-01T21:04:48Z | |
dc.date.issued | 2020-08 | |
dc.description.abstract | Various land use land cover (LULC) properties can be very informative about pollution signatures or fingerprints in rivers. In addition, determining the quantity of pollution contributed to river water quality by different LULC is important to determine best management practices (BMPs) to adopt for effective water resource management. This study was initiated to identify pollution sources over spatiotemporal scales by using a combination of univariate trend analyses, multivariate statistical methods, and a receptor model. The multivariate method applied was principal component and factor analyses (PCA/FA). Thereafter, a positive matrix factorization (PMF) method, a receptor model was applied to apportion pollutants found within the Manawatu River Catchment in New Zealand. To achieve this, a 25-year (1989 – 2014) dataset comprising of 12 water quality variables from three different sites was used. LULC identified high-producing grassland (HG) as the most dominant class in all three sub-catchments, and was observed to be a major source of pollution at the three river monitoring sites. Univariate analyses and a Dunn-Bonferroni test conducted on categorized temporal values of pollutants revealed that nutrients and sediments were statistically significantly higher for the three sites when compared to initial monitoring years. There were multiple lines of evidence from both PCA/FA and PMF analyses that showed natural, domestic, and agricultural sources contributed to the water quality in the Manawatu river. The PMF analysis further revealed specific pollutants causing impairment and requiring attention by waste managers. Overall, the PMF model revealed point, natural, and agricultural sources contributed close to 86%, 32%, and 75%, respectively in the downstream section of the river. At the intermediate sub-catchment, point, and agricultural sources contributed up to 100%, and 78% respectively, while soil erosion contributed 84%. For the upstream section of sub-catchment, agricultural pollution, and soil erosion were both 84% each. In addition, a combination of pollutant trends and these multivariate methods was significant in revealing the presence of point source pollution at the downstream site because of likely wastewater discharges. This study suggests that BMPs such as riparian buffers and constructed wetlands with high retention capacity are needed to filter the high concentrations of pollutants generated within the Manawatu Catchment. | |
dc.description.department | Engineering | |
dc.format | Text | |
dc.format.extent | 134 pages | |
dc.format.medium | 1 file (.pdf) | |
dc.identifier.citation | Tenebe, I. T. (2020). Multivariate analyses of the effects of land use change on river water quality: Case study of Manawatu River Watershed, New Zealand (Unpublished thesis). Texas State University, San Marcos, Texas. | |
dc.identifier.uri | https://hdl.handle.net/10877/16013 | |
dc.language.iso | en | |
dc.subject | water quality | |
dc.subject | pollution | |
dc.subject | Manawatu | |
dc.subject | New Zealand | |
dc.title | Multivariate Analyses of the Effects of Land Use Change on River Water Quality: Case Study of Manawatu River Watershed, New Zealand | |
dc.type | Thesis | |
thesis.degree.department | Engineering | |
thesis.degree.discipline | Engineering | |
thesis.degree.grantor | Texas State University | |
thesis.degree.level | Masters | |
thesis.degree.name | Master of Science |