- Title
- Spatial assessment of riparian vegetation condition in relation to water quality: a case of the Keiskamma River, Eastern Cape Province, South Africa
- Creator
- Teyise, Anda
- Subject
- Water quality
- Subject
- Riparian plants
- Subject
- Stream health
- Date Issued
- 2022-11
- Date
- 2022-11
- Type
- Master's theses
- Type
- text
- Identifier
- http://hdl.handle.net/10353/27679
- Identifier
- vital:69393
- Description
- Riparian vegetation plays several roles in ecological functioning, such as improving water quality because it can filtrate the sediments and provides stability on the floodplain. The condition of riparian vegetation can serve to provide information regarding river condition. The main purpose of this study was to investigate the extent to which water quality level of the Keiskamma River can be explained by the riparian vegetation density patterns. This study used Sentinel-2 Multi-Spectral Instrument (MSI) satellite image to assess spatial patterns in riparian vegetation condition. The Normalized Difference Vegetation Index (NDVI) was generated from the Sentinel-2 imagery and was used as the base from which riparian vegetation density classes were obtained through the supervised image classification technique. The image classification accuracy assessment was caried out to verify and validate the accuracy of riparian vegetation density classes. This technique produced the overall accuracy (OA) classification of 83.72 percent. The riverine water quality parameters were measured on the randomly surveyed sites using the Premium Series PC60 5-in-1 Water Quality Tester. High density of riparian vegetation were found in the upper course of the river. The low-density riparian vegetation dominates the middle course of the river while the lower part of the river contains a mixture of the three riparian vegetation conditions. The one-sample t-test statistical technique was carried out to determine the spatial pattern of water quality parameters. The t-test results revealed the significant variation in water pH, with the p-value of 0.00. However, t-test results also showed insignificant variations in water Total Dissolved Solids (TDS) and electrical conductivity (EC), with p-values of 0.117 0.059 and 0.059 respectively. The linear regression was used to determine the relationship between riparian vegetation and water quality. In this case, the NDVI values were used as surrogate for riparian vegetation condition. The results showed insignificant relationships between NDVI and water pH (r2 = 0.00), NDVI and water TDS (r2 = 0.09), and NDVI and water EC (r2 = 0.09) along the Keiskamma River. In view of the findings obtained from this study “spatial differences in riparian vegetation along the lateral and longitudinal dimensions of the Keiskamma River denote spatial variations in water quality levels”, is rejected.
- Description
- Thesis (MSci) -- Faculty of Science and Agriculture, 2022
- Format
- computer
- Format
- online resource
- Format
- application/pdf
- Format
- 1 online resource (viii, 130 leaves)
- Format
- Publisher
- University of Fort Hare
- Publisher
- Faculty of Science and Agriculture
- Language
- English
- Rights
- University of Fort Hare
- Rights
- All Rights Reserved
- Rights
- Open Access
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UFH Department of GIS & Remote Sensing
| Thumbnail | File | Description | Size | Format | |||
|---|---|---|---|---|---|---|---|
| View Details Download | SOURCE1 | MSc Anda Teyise Dissertation - Final.pdf | 2 MB | Adobe Acrobat PDF | View Details Download |