Electronic Theses and Dissertations (Masters)

Permanent URI for this collectionhttps://hdl.handle.net/10539/38009

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    Modelling for Rainwater Harvesting Structures Using Geospatial Techniques
    (University of the Witwatersrand, Johannesburg, 2024-10) Makaringe, Precious Nkhensani; Atif, Iqra
    Climate change poses a significant threat, leading to droughts, floods, and hindering sustainable development. Water scarcity is a growing concern, particularly in developing countries like South Africa, where limited freshwater resources are further strained by climate variability. This research explores the potential of rainwater harvesting (RWH) as a strategy to address water scarcity in such regions. This study aims to model potential rainwater harvesting sites in Lynwood Park, Pretoria, South Africa, utilising geospatial techniques. Object-Based Image Classification (OBIC) was employed to extract building footprints from high-resolution satellite imagery. Microsoft and Google building footprints were utilised to determine the suitable automated building footprints for Lynnwood Park. ArcGIS Pro software served as the primary platform for spatial data analysis and mapping potential RWH sites. Data integration included high-resolution satellite imagery, a Digital Elevation Model (DEM), building footprints, and rainfall data. Additionally, questionnaires were distributed to estimate population and water demand within the study area. The research demonstrates the efficacy of geospatial tools in identifying suitable locations for RWH systems. Indicating that steeper slopes in the southern region of Lynnwood Park have limited collection from large rooftops, while the flatter north offered greater potential. Rainfall graphs and PRWH results suggest that over half of Lynwood Park's annual water demand could be met through rooftop rainwater collection. However, factors such as system losses due to evaporation, inefficiencies in collection and storage, and variability in rooftop sizes across different buildings would need to be incorporated into more detailed models, as well as water quality analysis for rooftop harvested water in future studies. This study highlights the potential of RWH as a viable water security strategy in water-scarce regions. The findings contribute to the development of geospatial approaches for RWH implementation, promoting water security and sustainability in a changing climate.
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    Climate change and heritage tourism: threats to Makgabeng in a regional context, Limpopo South Africa
    (2020-11) Mcpherson, Fazlin Ahdielah
    The Makgabeng area is situated in the north-west corner of the Limpopo province in South Africa. The Makgabeng area is an emerging tourist destination with a variety of activities to offer. The area is rich in ancient rock art sites and, as a result, has great potential for the development of heritage tourism. Extensive research has been conducted on the rock art in this region. However, the impact of climate change on heritage tourism has not yet been explored. The local community of the Makgabeng area is developing a heritage tourism destination within the region and it is important to determine whether the initiative will be sustainable, especially in the context of climate change threats to the region. In a region such as Makgabeng where the primary attraction is natural heritage tourism rather than cultural, this then poses a severe threat to tourism within the region, especially since most of these attractions are outdoors. Hence, this research project is primarily aimed at determining climate change threats to heritage tourism in the Makgabeng region, South Africa. The research has employed a mixed-method approach consisting of interviews done with various stakeholders within the tourism industry and community members in the Makgabeng region. The other methods used are hard-copy and online questionnaires, TripAdvisor reviews, and the Tourism Climatic Index (TCI). What the research has found is that people do not know that Makgabeng exists, and for those who are aware of its existence they have never visited the region. this is because the area is not being marketed effectively. The TCI scores show that winter is the best time of the year for tourism. Consequently, stakeholders and community members should market the area with this in mind. However, tourists have said they enjoy the weather in the region all year round.