School of Geography, Archaeology and Environmental Studies (ETDs)

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A geographical analysis of the impacts of construction and demolition waste on wetland functionality in South Africa: a study of Gauteng province
(University of the Witwatersrand, Johannesburg, 2024-09) Mangoro, Ngonidzashe; Kubanza, Nzalalemba Serge; Mulala, Danny Simatele
The purpose of this study was to investigate construction and demolition waste management processes in sub-Saharan Africa and how they affect wetland ecosystems, using South Africa as a case study. Construction and demolition (CDW) waste has become a massive urban environmental challenge on a global scale, but more so in developing countries found in sub-Saharan Africa. In the context of South Africa, construction and demolition waste is not a waste stream taken seriously by local and national authorities because it is ‘general waste that does not pose an immediate threat to the environment. This position is premised on the idea that construction and demolition waste is generally inert (chemically inactive) and therefore cannot cause an immediate environmental risk. In this study, it is argued that the environmental risk of waste goes beyond the embedded chemical constituencies because some waste streams can cause immediate environmental risk through their physical properties depending on the location of disposal. It is further argued that although CDW is generally inert, disposal in wetlands immediately disrupts the way wetland ecosystem’s function, causing several environmental risks. To mitigate the environmental threats posed by construction and demolition waste, this study proposes a change in the methodological approaches and strategies deployed to manage the waste stream, such as by introducing a hybrid of circular economy and industrial ecology to minimize or eliminate waste production. This study involved several data collection and analysis methods. Using a combination of qualitative and quantitative studies methods, data was collected with the goal to understand the perceptions of experts on how construction and demolition waste management in South Africa affects wetland ecosystems and what can be done to effectively manage the waste stream in the context of a developing country. Data informing this study were collected through semi-structured interviews and surveys in the province of Gauteng, specifically in the City of Johannesburg and City of Ekurhuleni Municipalities, where there is massive illegal dumping in wetlands for various reasons. Furthermore, apart from the use of semi-structured interviews and surveys, a digital elevation model was generated in ArcGIS Pro 10.1 software to measure the effects of construction and demolition waste on wetlands in the study area. The approach to this study using both qualitative and quantitative methods was crucial because it provided human perceptions which were accurately corroborated by GIS software. The study found that construction and demolition waste management in South Africa is affected by several challenges that lead to massive illegal dumping in critical ecological ecosystems such as wetlands. In a broad sense, the major challenge to sustainable construction and demolition waste management in South Africa is institutional failure at both the local and national levels. Local authorities such as municipalities are characterized by massive corruption, poor funding, and lack of strategic technologies among other things, while at the national level, there is massive interference with municipal affairs through bureaucratic delays in the disbursement of municipal funds. A combination of these and other factors leads to illegal dumping of construction and demolition waste across the Gauteng Province, particularly in wetlands in low-income areas. The data informing this study reveals that dumping construction and demolition waste in wetlands causes an immediate threat to the existence of wetlands through massive sedimentation with insoluble materials. It is ultimately found that construction and demolition waste destroy the ability of wetlands to offer ecosystem services such as flood attenuation, carbon sequestration, water filtration, and habitat provision, among other functions, leading to environmental events such as flooding. A combination of circular economy and industrial ecology can be one of the ways that can be deployed to effectively and sustainably manage construction and demolition waste in South Africa. The circular economy and its three principles of ‘reduce’, ‘recycle’, and ‘reuse’ has been successfully deployed in developed countries in the European Union, where recycling has topped 70% of the total construction waste generated. Industrial ecology with its analogy of industrial ecoparks has been deployed in the European Union with immense success, until more attention was directed to circular economy. With an increase in municipal funding and introduction of a construction waste information system, a combination of ‘circular economy’ and ‘industrial ecology’ can significantly help to reduce pressure on wetlands and the environment at large. Even though the methodological improvements suggested above could significantly reduce pressure on wetlands, the implementation could be faced with institutional challenges. Therefore, it is argued that urgent institutional transformation is required to make tangible changes in the field of construction and demolition waste management. It is recommended that there should be increased law enforcement to curb widespread illegal dumping in South Africa’s major cities. It is also recommended that, like in Europe, South Africa must introduce tailor-made legislation of policies for construction and demolition waste alone. Promulgation of dedicated legislation provides clear direction on how the waste stream is managed and who is responsible for specific roles. Furthermore, dedicated legislation can be a crucial tool to deliver sustainable construction and demolition waste management in South Africa because it can be used to encourage the use of recycled aggregates and limit the amount of illegal dumping or extraction of materials from the environment. Finally, dedicated construction and demolition waste legislation can be used to shift from the traditional view of pollution or contamination through toxicity, and so the value of this study is immediately apparent.
A Geospatial Approach to Mapping Jacaranda Tree Distribution in Johannesburg, South Africa
(University of the Witwatersrand, Johannesburg, 2023-11) Reddy, Rohini Chelsea; Fitchett, Jennifer
Accurate mapping of the spatial distribution of invasive species is vital for the implementation of effective monitoring and management strategies. In countries where resources are scarce and costly, citizen science provides a cost-effective and accurate alternative for large-scale data collection. Citizen’s familiarity with their environment contributes to aspects such as accurate identification of features on the landscape. Advances in a geographic information system (GIS) together with open-sourced photography from Google Street View, provide accurate methods for in-field and remote validation of citizen science data for invasive mapping and assists with the creation and compilation of maps to visualize the spatial distribution of invasive plants upon the landscape. In this study, the first spatial distribution maps for invasive tree species, Jacaranda mimosofolia (common name: Jacaranda), are created for the City of Johannesburg (CoJ). Jacaranda trees are well-known by citizens in the CoJ for their district purple flowers which blanket the landscape during springtime. A combination approach using citizen science, GIS, and Google Street View for data collection, analysis, and creation of the first spatial distribution map of exact location and prevalence of Jacaranda trees within certain suburbs of the CoJ, is produced. A total of 8,931 ground-truthing geopoints together with extensive Google Street View validation for Jacaranda tree presence, formed the basis of accurate spatial distribution maps. The first research question of this study focused on the spatial distribution of Jacaranda trees in the CoJ and was answered as a total of 54 suburbs were confirmed as having a large presence of Jacaranda trees in the CoJ. Citizen science data collected a total of 488 geotags for possible Jacaranda tree presence in the CoJ, over a 75-day online survey collection period. Although citizen science data provided a lower spatial resolution compared to successful fieldwork and Google Street View approaches, citizen science data provided very high accuracy for the identification and geolocation of Jacaranda tree presence in the CoJ which answers the second research question based on the effectiveness of the geospatial approach towards citizen science, ground-truthing and Google Street View as data collection methods. Since the accuracy of citizen science resulted in 66% of collected geotags within the categories of ‘very high’, ‘high’ and ‘moderate’ accuracy ranges of between <7-24m from a confirmed Jacaranda tree, together with the accuracy of 8,931 in-field collected geolocation of Jacaranda trees and Google Street View’s accuracy and capability of collecting street view imagery – it is concluded that the combined approach of ground-truthing, citizen science and Google Street View contribute not only to effective data collection, but also towards the successful mapping of Jacaranda tree presence in the CoJ.
A GIS framework for the integrated conceptualisation, analysis and visualisation of Gauteng's complex historic and contemporary post-mining urban landscape
(University of the Witwatersrand, Johannesburg, 2023) Khanyile, Samkelisiwe; Esterhuysen, Amanda; Kelso, Clare
This research study applies assemblage theory as a philosophical lens. It proposes a framework for integrating contemporary and historical landscape characteristics of post-mining and urban landscapes for an integrated conceptualisation, mapping, and analysis of Gauteng, South Africa. The study utilises a mixed methods approach, incorporating spatial and non-spatial (literature and survey) data of varying formats to identify landscape characteristics. Additionally, it applies three multicriteria decision analysis (MCDA) and GIS mapping techniques, employing a simplified rationale to keep its complexity low. Descriptive and inferential statistics were used to analyse the quantitative data, while the qualitative data was analysed using a thematic analysis. The literature and survey analysis findings were used to inform the development of a framework demonstrating the integration of Gauteng's post-mining and urban landscape characteristics using a fuzzy overlay, weighted overlay and random forest classification, along with an accuracy assessment of the mapped results. Based on the proposed framework, the mapped results' performance was evaluated through four methods: confusion error matrix, cross-evaluation, areal coverage comparison, and an image differencing assessment. The literature and survey analysis findings, used to inform the framework, reveal that the two landscapes consist of an assemblage of characteristics and highlight differences in the characterisation of post- mining and urban landscapes. Distinctions were also apparent between literature-derived characteristics and those identified from local experts. The local expert-derived characteristics demonstrate context- specific characteristics of Gauteng's post-mining and urban landscape. At the same time, those based on the literature emphasise a more distinct and separate portrayal of post-mining and urban landscape characteristics (pages 115-116). The characteristics identified from local experts were less conservative (pages 117-118). They included urban-related characteristics in the description of post-mining landscapes and mining-related characteristics in the description of urban landscapes, presenting some similarities in the characterisation of these two landscapes in Gauteng. Moreover, the findings from local experts also revealed that literature and other written or mapped work informed most definitions of post-mining and urban landscapes. The framework for integrating landscape characteristics (pages 121-123) was spatially represented through the three mapping methods, visually demonstrating several findings providing insight into the Gauteng landscape's uniqueness. First, it demonstrates that the differences in the characterisation of these landscapes also impact how they are spatially represented. The maps of post-mining and urban landscape characteristics based on the literature presented a similar pattern to the traditional mapping of mining and urban landscapes in Gauteng. These mapping techniques show the highest values across the mining belt and at the province's core. These findings highlight the influence of literature on the representation of these two landscapes, which is consistent with local experts' reports. In all three mapping methods, the maps generated from local expert characterisations of post-mining and urban landscapes presented a larger spatial footprint than those based on literature-derived characteristics. This distinction was attributed to incorporating additional post-mining and urban landscape characteristics in the maps based on expert input and applying the three mapping techniques - using representation methods not commonly used in mapping these landscapes. Second, the integrated maps of post-mining and urban landscape characteristics suggested a variance in the presence of post-mining and urban landscape characteristics across the province in the maps generated using fuzzy and weighted overlay techniques. This indicates that some parts of the province have a higher or lower presence of post-mining or urban characteristics (pages 125-132). These findings were visible in the maps generated from literature and local experts, indicating the diversity of both landscapes and the co-existence of post-mining and urban landscape characteristics in the local expert maps. This implies an intricate relationship between these landscapes, challenging the idea of them being strictly separate, as indicated in maps presenting characteristics identified from the literature. Furthermore, a closer inspection of the areas showing the intersection between post-mining and urban landscape characteristics also points towards the porosity of boundaries of these two landscapes and alevel of spatial overlap, organisation and arrangement, which are prevalent at varying levels (pages 164- 168). Third, the maps generated using literature-derived characteristics achieved higher accuracy scores, attributed to using reference data traditionally used to map the two landscapes under investigation. This reference data only comprised classes that characterised the physical mining and urban classes, consistent with those identified in the literature. Consequently, it lacked additional factors characterising the post-mining and urban landscape identified from local experts. The fuzzy overlay maps informed by literature demonstrated an accuracy exceeding 70% for post-mining and urban landscape characteristics. In comparison, those reported by local experts scored 64. The weighted overlay and random forest classification resulted in accuracy rates exceeding 50% for post-mining landscape characteristics maps, regardless of whether literature or expert-derived characteristics were used. Additionally, urban landscape characteristics maps achieved an accuracy of over 76%, regardless of the characteristics used to inform the mapping. These findings were attributed to the different mapping techniques employed, with fuzzy and weighted overlay using a gradual range scale, while random forest classification employed a binary scale. This highlights how different mapping methods affect the representation of space. Additionally, it demonstrates the versatility of these mapping techniques in mapping complex spaces such as post-mining and urban landscapes. In this study, the fuzzy overlay accuracies exceeded 60% for all maps and emerged as the most suitable choice for integrating landscape characteristics due to its ability to represent blurred and porous boundaries between Gauteng's post- mining and urban landscapes. In conclusion, the study challenges the notion of post-mining and urban landscapes as distinct landscapes, emphasising the importance of considering the varying levels of spatial intersection between these two landscapes. With the proposed framework and the alternative representation of these landscapes, including contextual information, this research provides insights into new conceptualisations of urban, post-mining landscapes and mineralised urbanisations as assemblages of different landscapes and characteristics with porous boundaries. This enables a better understanding of Gauteng's post-mining and urban landscapes, which could benefit the representation, communication and management of these landscapes. Recognising the potential applications and limitations of frameworks such as the one developed for this study, the high-level recommendation arising from this study suggests a need for ongoing research into the contextual representation of landscapes and their characteristics. This can be achieved by incorporating input from communities, conducting research on quantifying intangible landscape characteristics and developing tools that facilitate the automation and alignment of such data with development plans.
An Assessment of Beauty Waste Management Practices: A Case Study of Rustenburg Beauty Salons
(University of the Witwatersrand, Johannesburg, 2024) Knight, Jasper; Knight, Jasper
The beauty salon industry is one of the fastest growing industries and is a significant waste generator in South Africa. Waste that results from beauty salons is a thorny environmental issue because it spans from different waste types and sources. Futhermore it requires waste treatment and different disposal methods. In view of this, this study seeks to assess waste management practices of beauty salons in Rustenburg, South Africa, in order to identify the types of waste salons generate and to identify recommendations that can assist beauty salons to be environmentally sustainable by improving their waste management practices. The aim of the research is to understand how beauty salon waste is discarded and to what degree beauty salon personnel understand the impacts of waste on the environment. The objectives of this research are to (1) determine the total amount of waste produced by selected beauty salons in Rustenburg, (2) identify the waste management practices undertaken by the beauty salons, (3) explore the challenges the beauty salons face in relation to waste management, and (4) identify recommendations of how beauty salons in South Africa can further improve their waste management practices. This study employed a mixed methods design through quantifying the amount of waste the selected beauty salons generate over a two month period, and by interviewing salon personell on their views on salon waste and waste management practices. Fifteen salons were surveyed. Results were analyzed using thematic analysis. The results show that the all the beauty salons combined produce a total annual estimated waste of 4732.2 kg. Through interviews, the study identified waste management practices of the beauty salons to be primarily premised on discarding waste in dustbins for municipal collection, burning waste, or dumping waste in unregulated dumping sites when waste service delivery poses challenges. These three practices are the most common modes of waste disposal in the Rustenburg beauty salons. Issues of waste management facing beauty salons includes lack of waste facilities and lack of knowledge about waste management. The major recommendation from beauty salons and civil (professional) organisations was for government to provide beauty salons with better infrastructure for waste sorting, recycling, pick-up and disposal. Promotion of good practice and awareness campaigns were cited as recommendations to improve waste management practices in beauty salons
An integrated approach for detecting and monitoring the Campuloclinium macrocephalum (Less) DC using the MaxEnt and machine learning models in the Cradle Nature Reserve, South Africa
(University of the Witwatersrand, Johannesburg, 2024) Makobe, Benjamin; Mhangara, Paidamoyo
The invasion of ecosystems by invasive plants is considered as one of the major human- induced global environmental change. The uncontrolled expansion of invasive alien plants is gaining international attention, and remote sensing technology is adopted to accurately detect and monitor the spread of invasive plants locally and globally. The Greater Cradle nature reserve is a world heritage site and intense research site for archaeology and paleontology.It was accorded the world status by the United Nations Educational, Scientific and Cultural Organizations (UNESCO) in 1991 due to its variety of biodiversity present and carries information of significance about the evolution of mankind. The invasion of Campuloclinium macrocephalum (pompom weed) at the Cradle nature reserve is downgrading the world status accorded to the site, lowers the grazing capacity for game animals and replaces the native vegetation. This research study explored the capability of Sentinel-2A multispectral imagery in mapping the spatial distribution of pompom weed at the nature reserve between 2019 and 2024. The non-parametric classification models, support vector machine (SVM) and random forests (RF) were evaluated to accurately detect, and discriminate pompom weed against the co-existing land cover types. Additionally, the species distribution modelling MaxEnt Entropy was incorporated to model spatial distribution and pompom weed habitat suitability. The findings indicates that SVM yielded 44% and 50.7% spatial coverage of pompom weed at the nature reserve in 2019 and 2024, respectively. Whereas, the RF model indicates that the spatial coverage of pompom weed was 31.1% and 39.3% in 2019 and 2024, respectively. The MaxEnt model identified both soil and rainfall as the most important environmental factors in fostering the aggressive proliferation of pompom weed at nature reserves. The MaxEnt predictive model obtained an area under curve score of 0.94, indicating outstanding prediction model performance. SVM and RF models had classification accuracy above 75%, indicating that they could distinguish pompom weeds from existing land cover types. The preliminary results of this study call for attention in using predictive models in predicting current and future spatial distribution of invasive weeds, for effective eradication control and environmental management.
Are our Head Teachers okay? Decision-making processes during COVID-19 across South African independent schools
(University of the Witwatersrand, Johannesburg, 2023-10) Pahl, Julia; Evans, Mary
The COVID-19 pandemic significantly affected the education sphere globally and in South Africa. The impact on pupils and teachers has been investigated. However, the impact on Head Teachers in schools, particularly independent schools in South Africa, has received less attention. Head Teachers within independent South African Schools are the decision makers, leaders, and influencers who were placed in a key role during the COVID-19 pandemic. These Head Teachers were asked to lead, make decisions, and positively influence and manage those under their care while the educational landscape shifted. This shifting educational landscape placed Head Teachers within independent schools under increased pressure and stress. This study aimed to understand the technological and financial access and contexts of Head Teachers at independent schools within South Africa and explore their decision-making processes and the impact of their decisions on their well-being. An online survey was sent to independent Head Teachers, and four in-depth, one-on-one interviews were conducted. Head Teachers showed that their financial and technological contexts did not constrain their pandemic responses as the nature of their independent school allowed them to have access to adequate technological resources and alternative financial support sources. Key findings of this research were that Head Teachers were commonly influenced both positively and negatively by the complex communication networks and channels created and used during the pandemic and the complex decision-making drivers they had to navigate while leading during the pandemic. The decision drivers of well-being and shared moral purpose were more dominantly considered than the decision driver of National Government Directives, as Head Teachers had to consider their complex and multi-dimensional environments when deciding which decision driver was to be prioritized. Head Teachers had to navigate two main tensions: would they prioritize outcomes such as assessment and reports during the pandemic or would they prioritize awareness and well-being of staff and learners, and would they make their decisions from a compliance standpoint where full compliance was key or from a standpoint where complying as much as possible or enough for deniability was chosen. These results also associated increased communication networks during the pandemic with increased stress and burn-out levels and therefore a decreased well-being of Head Teachers, and increased numbers of Head Teachers leaving the profession. However, a positive outcome of the pandemic was that schools, staff, learners, and parents were forced to increase their device and/or internet access and technological skills to maintain education during the lockdown and the changing educational environment. When these results were studied across the geographical landscape of independent South African schools it was clear that the findings on access, well-being and decision-making were linked to the context of the Head Teacher and their school and not to their geographic location. Yet using complex, multi-faceted communication networks and the resultant stress was a country-wide experience and that National Government Directives was the country-wide main decision-driver for independent South African Head Teachers. Overall, this study identified six key lessons for education within any future South African pandemics: the need for clear and concise instructions within legislation, standard operating procedures need to consider access and context, blended education should become a norm in schools, consistency within education should be maintained throughout, personal boundaries should be maintained throughout and networking between leaders should be increased.
Assessing and comparing the performance of different machine learning regression algorithms in predicting Chlorophyll-a concentration in the Vaal Dam, Gauteng
(University of the Witwatersrand, Johannesburg, 2024-03) Mahamuza, Phemelo Hope; Adam, Elhadi
The state of Vaal Dam is influenced by various land uses surrounding the Dam, including agricultural activities, mining operations, industrial enterprises, urban settlements, and nature reserves. Mining activities, farming practices, and sewage outflows from nearby villages led to access contamination within the Dam, increasing algal bloom levels. Sentinel-2 MSI data were utilized to forecast and comprehend the spatial pattern of Chlorophyll-a concentration, indicating algal bloom occurrence in the Vaal Dam. Targeting Sentinel-2 Level-1C, the image was preprocessed on the Google Earth Engine (GEE) with acquisition dates from 25 – 26 October 30, 2016, corresponding to the on-site data collection between October 26 and October 28, 2016. Due to limited resources, up-to-date data on the Vaal Dam could not be collected. However, since this study focuses on applying various machine learning regression models to predict chlorophyll-a levels in waterbodies, the dataset is used to test the models rather than reflect the current state of the Vaal Dam. The dataset, comprising 23 samples, was divided into 70% training and 30% test sets, allowing for comprehensive model evaluation. Band ratio reflectance values were extracted from the satellite image and correlated with in-field Chlorophyll-a values. The highest correlation coefficient values were utilized to train five machine-learning models employed in this study: Random Forest (RF), Support Vector Regression (SVR), Least Absolute Shrinkage and Selection Operator (LASSO), Ridge Regression, and Multilinear Regression (MLR). Each model underwent training with ten iterations each; the best learning iteration was then used to generate the final Chlorophyll-a predictive model. The predictive models were validated using the Sentinel-2 MSI satellite data and in-situ measurements using R2, RMSE, and MAPE. Among the five machine learning algorithms trained, RF performed the best, with an R2 of 0.86 and 0.95, an RMSE of 1.38 and 0.8, and MAPE of 15.09% and 10.92% for the training and testing sets, respectively, indicating its ability to handle small, non-linear datasets. SVR also demonstrated a fair performance, particularly in handling multicollinearity in the data points with an R2 of 0.68 and 0.87, an RMSE of 2.37 and 1.56, and MAPE of 18.13% and 19.28% for the training and testing sets, respectively. The spatial pattern of Chlorophyll-a concentrations, mapped from the RF model, indicated that high concentrations of Chlorophyll-a are along the Dam shorelines, suggesting a significant impact of land use activities on pollution levels. This study emphasizes the importance of selecting suitable machine learning algorithms tailored to the dataset's characteristics. RF and SVR demonstrated proficiency in handling nonlinearity, with RF displaying enhanced generalization and resistance to overfitting. Limited field data evenly distributed across the Dam and satellite overpass dates may affect result accuracy. Future research should align satellite pass dates with fieldwork dates and ensure an even distribution of in-field samples across the Dam to represent all land uses and concentration levels.
Assessing livelihood vulnerability and adaptation to climate variability and change among farming households in Plateau State, north-central Nigeria
(University of the Witwatersrand, Johannesburg, 2024) Hassan, Buhari; Knight, Jasper
It has been projected that sub-Saharan Africa would be severely affected by climate change in form of persistent and increasing climate variability. Nigeria’s situation as a developing country coupled with the fact that agricultural activities are primarily rainfed, provides a suitable case study in which to assess the vulnerability of farming households to climate variability and change. Lack of data on the nature and extent of vulnerability to climate variability (particularly annual changes in rainfall and temperature patterns) on food production systems and livelihoods in Nigeria hinders the development of effective policies to mitigate the adverse impacts of climate change and variability. The study aims to improve understanding of the socio-economic, institutional, biological and physical factors that contribute to vulnerability of farming households to climate change and variability in Nigeria. By combining descriptive, participatory and statistical analysis as well as field observations, this research develops a holistic approach to assess the level of exposure, sensitivity and adaptive capacity of farming households. Multistage sampling was used to purposely select communities in Bokkos Local Government Area, Plateau State, for the study, while farming households were randomly selected for the household questionnaire survey within four communities. Purposive sampling was used to identify key informants for interviews. Observation and taking photographs of farmers’ activities were used to complement the other data collection methods. Qualitative data was analysed using descriptive and content analysis, while the quantitative data was analysed using the Statistical Package for Social Sciences (SPSS) (v 27) and Microsoft Excel (v2020). The level of vulnerability of farming households was determined using the Sustainable Livelihood Approach. Results show that farmers are exposed to climate variability in form of changing rainfall patterns which includes late onset of rains, dry spells, and early cessation of rains and crop loss due to pests and disease infestation. Results show that the vulnerability of farming households can be linked to access to household livelihood capital assets and that households are characterised by low levels of financial, social and physical capital. Smallholder farming households adopt a range of on-farm and off-farm adaptation strategies including changing planting time, crop diversification, engaging in irrigation farming, intensifying the use of fertilizers, manure and agro-chemicals to boost crop yield, and planting of disease-resistant and drought-tolerant crop varieties. Farming households experience a number of challenges which include a lack of financial resources which has a strong influence on enhancing other capital assets such as physical and natural capitals; poor access to mechanised agricultural equipment, lack of training on how to deal with climate change and variability, limited access to improved crop varieties as well as a lack of institutional support, which constitute serious barriers to adaptation to climate variability. In applying these results to climate change adaptation it is recommended that policymakers need to institute specific and implementable climate change adaptation policies that will enable farmers to utilize their capital assets on effective adaptation measures and also engage in viable alternative livelihood diversification strategies, enhance agricultural productivity and resilience and improve institutional support including access to information and training
Assessing the effectiveness of wetlands in the Krugersdorp Game Reserve in attenuating pollution from mines on the West Rand, South Africa
(University of the Witwatersrand, Johannesburg, 2023) Sawuka, Noluthando Thulisile; Evans, Mary; Masindi Khuliso
In South Africa, 48% of the country’s wetlands are critically endangered because of anthropogenic activities. Wetlands are an important part of the landscape and play a critical role including but not limited to improving water quality, habitat provision, and water storage. This research aimed to assess the effectiveness of wetland systemsin attenuating pollution from water discharged from abandoned gold mines in the Krugersdorp Game Reserve (KGR), West Rand. Eight (8) water samples were collected in the study site. Physico-chemical parameters were measured in situ, and chemical parameters were measured in the lab. The measured physico–chemical parameters from the majority of the sampled wetlands exceeded at least one of the stipulated water quality legislations, which included the General Authorization Limit Section 21f and h, 2013; Unit for TWQGR; Mine Health and Safety Act; and WUL wastewater in terms of the recorded pH, total dissolved solids, and salinity variables. Overall, a decreasing trend in pH level was observed from wetlands sampled upstream of the KGR to wetlands sampled downstream of the KGR, with the highest recorded pH level (Alkalinity: 8.9) obtained from the sampled wetland that was closest to the adjacent mining site upstream of theKGR whilst the lowest recorded pH level (Acidity: 3.9) obtained from a wetland sampling point that was further from the adjoining mine and downstream in the KGR. A weak and positive correlation (r=0.040) was obtained between the measured total dissolved solids and pH levels from the sampled wetlands, indicating minimal spatial variability. However, a strong positive correlation (r=0.999, Correlation is significant at the 0.01 level) was obtained between the measured total dissolved solids and salinity from the sampled wetlands. At least one of the limits stipulated by the water quality legislation was exceeded in terms of the analysed inorganic constituents from the sampled wetlands. The dominant ions recorded in the wetlands in increasing order are F, K, Cl, Mg, Na, Ca, and SO4. Mn and Si were the dominant metal concentrations recorded in most wetlands, with the former also showing exceedances when compared to the stipulated water quality guidelines. The recorded data from the measured physico–chemical parameters and analysed chemical variables indicated poor water quality in wetlands sampled downstream of the KGR and upstream of the KGR. Stringent measures in water quality monitoring need to be implemented to mitigate the environmental impacts associated with wastewater discharge into the receiving environment.
Assessing the inter-annual and inter-seasonal climate-induced variation in caseload of respiratory diseases
(University of the Witwatersrand, Johannesburg, 2024-06) Motlogeloa, Ogone
In South Africa, acute upper respiratory diseases pose a significant public health challenge, influenced heavily by climatic factors. Recognizing the critical need for detailed seasonal analysis. This thesis delves into the inter-annual and inter-seasonal impacts of climate on disease caseloads, offering four pivotal contributions to health biometeorology. The first contribution refines the understanding of the acute upper respiratory disease season in South Africa, previously recognized as the winter months of May to September. This research provides a more granular analysis by pinpointing specific onset timings and fluctuations within the season that are crucial for optimizing healthcare responses, particularly in vaccination schedules. The second contribution is an in-depth analysis of climatic variables affecting acute upper respiratory disease prevalence. Utilizing Spearman's correlation analyses and the Distributed Lag Non-linear Model across Johannesburg, Cape Town, and Gqeberha, this study identifies negative correlations between temperature and disease cases, pinpointing significant risk thresholds most prevalent during the winter peak. The third contribution investigates the impact of extreme climate events (ECEs) over twelve years, elucidating how, while individual ECEs influence medical aid claims and disease incidence, it is the broader seasonal patterns that predominantly dictate acute upper respiratory disease prevalence. The fourth contribution offers a nuanced exploration of the climate-health nexus, demonstrating that routine weather variations play a more significant role in the peak transmission of acute upper respiratory viruses than extreme events. This thesis elucidates the substantial yet nuanced influence of climate on respiratory health in South Africa. By specifying the disease season with greater precision and clarifying the relationship between temperature variations and disease prevalence, the research provides essential data for health practitioners to plan targeted interventions. This study moves beyond the focus on extreme weather events to expose the subtler, yet more consistent, impact of seasonal climate shifts on health outcomes, enriching our understanding and serving as a vital reference for enhancing disease preparedness in an era marked by climatic uncertainty.
Assessing the Validity of the Exclusion of Night-time Thermal Comfort in Tourism Climate Indices
(University of the Witwatersrand, Johannesburg, 2024-09) Mnguni, Zandizoloyiso; Fitchett, Jennifer
Biometeorological indices are instruments that can be used to streamline complex climatic information for economic and other decision-making. Indices hold inherent assumptions where the use of an index is only reliable and valuable if those assumptions are true. The Holiday Climate Index (HCI) is presented as the improved version of the TCI, with a key difference being the removal of night-time thermal comfort due to the assumption that air conditioning is ubiquitous throughout Europe. This study investigated the validity of this exclusion of night-time thermal comfort in tourism climate indices, particularly for the HCI using the six European cities for which the index was developed – Barcelona, Stockholm, London, Istanbul, Paris and Rome. The assumption of ubiquitous air conditioning was investigated using Booking.com accommodation listings, the night-time economy and prevalence of night-time activities outside of each accommodation establishment, and whether tourists experienced adverse thermal comfort during the night through posted reviews. Without the air conditioning filter applied, the proportion of listings categorized as offering air conditioning ranged from 28.8% for Stockholm to 98.9% for Rome. With the filter applied, the proportions ranged from 96.4% for Stockholm and 99.0% for Paris. A total of 24,252 TripAdvisor reviews were also examined for both accommodation establishments and night-time tourist activities. The reviews were manually examined for the mention of weather, climate, night-time temperature and air conditioning. The findings of this study exhibit a range of night-time activities, many of which are outdoors, where tourists did comment on night-time thermal comfort. The research disproves the claim of the original authors, and it was found that air conditioning is not ubiquitous. Therefore, the assumption that the HCI is based on is problematic, and the index should be used with caution. Moreover, a similar approach in index validity testing should be performed prior to future studies seeking to apply indices.
Assessment of disposal methods of construction and demolition waste: A case study of south-eastern industrial and residential areas in Johannesburg, South Africa
(University of the Witwatersrand, Johannesburg, 2024) Jager, Vasti de; Kubanza, Nzalalemba Serge
In a world where all strive for further development, construction and demolition play alarge role in that process. The waste generated in construction and demolition projects is of great magnitude and needs to be dealt with and disposed of appropriately, however, is this truly the case? Gauteng is a province where landfills are easily accessible and a cheap disposal option. This study set out to assess disposal methods of construction and demolition waste in south-east Johannesburg, South Africa. Landfills and recycling were the prevalent disposal methods, and these were compared to other countries’ disposal methods. Policy and legislation regarding solid waste management were analysed and a gap between written documents and implementation was identified. The question of sustainability also played a role in the synthesis of the study
Assessment of the impact of load shedding on the households of Alexandra, Johannesburg, South Africa
(University of the Witwatersrand, Johannesburg, 2023) Mbatha, Cebolethu; Kubanza, Nzalalemba Serge
In South Africa, persistent challenges in the electricity sector have been noted. This study emphasizes that having access to electricity is insufficient; the reliability of its supply is crucial,especially given prolonged power outages faced by a significant portion of the population. In Alexandra Township at two residential areas, 16th Avenue and East Bank, the research used a mixed-method approach, involving questionnaires for 100 households and 20 local businesses, and semi-structured interviews with representatives from the local city authority. Results indicated substantial disruptions to daily lives and operations. These disruptions adversely affected critical social services, hindering operations in essential infrastructures like water supply systems, hospitals, education institutions, and telecommunication systems. The study identifies illegal electricity connections, infrastructure loss, and political interference as perceived major causes of successive power outages in Alexandra. It highlights the worsening nature of load shedding, making it a significant political issue in South Africa, reflecting hardships households and businesses face. The paper recommends governmental subsidies for alternative energy appliances and more favorable electricity tariff rates for households and small businesses to alleviate demand during peak periods. The findings offer valuable insights for policymakers and the South African electricity utility in analyzing trade-offs between negative welfare effects and costs of reducing power outages
Cartographic History, the Post-Colonial Landscape and the Agricultural Settlement Scheme: A Case Study of Citizen-Based Mapping in Northeastern Ibadan Rural Hinterland
(University of the Witwatersrand, Johannesburg, 2023-10) Ogundiwin, Babatunde Adedayo; Wafer, Alex
Maps of economic imagination provide visual insights into alternative agrarian spatial thought. This thesis examines visual contribution to reconstituting agricultural subjectivity. It explores the potential of citizen-based mapping in consolidating alternative visions of the agricultural settlement scheme. Visualisations are integral in the discursive technologies of post-colonial state policies that produce modern agricultural subjectivity. On one hand, these state cartographic strategies involve othering practices of subaltern agriculture. On the other hand, there are resurgent ideas of community-based agricultural schemes verbalised amongst subaltern groups. Hence, there is an ongoing political-economic struggle of visions mediated by visualisation and verbalisation. Drawing upon theoretical literature in spatiality, postcolonialism and governmentality, the thesis explores taken-for-granted knowledge, sites of economic difference and silenced voices/visions on the post-colonial agricultural landscape. Using Northeastern Ibadan rural hinterland of Oyo State, Southwest Nigeria, as a case study, the thesis argues that visualisation offers insight into counter-narratives and alternative reframing of the agricultural settlement scheme. This study employed a multi-method qualitative approach involving the critical historical reading of state maps, ethnographic analyses and mapmaking techniques to visualise and summarise developmental concerns and aspirations. The thesis demonstrates that state imaginative geographies strive in shaping agricultural identities and subjectivities. Recently, these cartographic legacies of state rationalities seek the active consent of the citizenry in the drive toward state-sanctioned neoliberal imaginary. The study contends that the post-colonial state in Nigeria envisions a large-scale agricultural development rather than supporting smallholder subaltern agriculture. Hence, there is intentional and unintentional involvement in visual disinformation and engagement in anti-political economic imaginations of subaltern agriculture. However, the visualisation of verbalised counter-narratives contesting state developmental visions and alternative imaginations of the agricultural settlement scheme unveil anticipatory spatialities desiring a break from economic decline and stagnation in rural hinterlands. This transformation of imaginaries into visual images emphasises new perspectives and new insights renegotiating the political subjectivity of subalterns. This thesis demonstrates that visual geographies of subaltern aspirations offer alternative visions of the agricultural settlement schemes.
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.
Climate Variability and Asset Adaptation of Small-scale Farmers in Zimbabwe's Gokwe South District:A Search for Knowledge Integration Approach
(University of the Witwatersrand, Johannesburg, 2023-05) Chatsiwa, Jaison; Simatele, Mulala Danny
Globally, climate change and variability threaten food production and security for an unforeseeable future leaving millions of people vulnerable to hunger and malnutrition related diseases. Climatic models are projecting that Zimbabwe’s climate will be hanging drastically with a high possibility of experiencing extreme weather patterns impacting the livelihoods of small-scale farmers who rely on rain-fed agriculture for their livelihoods. This study aims to investigate the role of asset portfolios in reducing the climate vulnerability of small-scale farmers of Gokwe South in Zimbabwe. Zimbabwe’s agricultural production both crop and livestock production has been negatively impacted due to the dwindling rainfall and increase in temperature and climate related risks and disasters. The quality and quantity of asset portfolios determine the adaptive strategies and their success against the challenges of climate variability. Despite these effects, small-scale farmers in the Gokwe South district are using their asset portfolios to increase their adaptive capacity and resilience to fight against the challenges of climate variability. Therefore, this thesis revealed a paradigm shift from asset vulnerability to pro-poor asset adaptation. The paradigm shift crafted the ‘Theory of Change’ which is useful for climate variability adaptation strategies in the Gokwe South district as the small-scale farmers change from asset vulnerability to asset adaptation. The Theory of Change encourages contextual analysis of the area and theme under study. A Theory of Change is a method that explains how a given intervention, or set of interventions, is expected to lead to specific development change, drawing on a causal analysis based on available evidence. This study used the Participatory Climate Change Adaptation Appraisal (PCCAA) as the primary data collection tool and the Participatory Rural Appraisal (PRA) known as the emancipatory methodology, to collect data in rural areas. A mixed methodological approach involving qualitative and quantitative was applied. We used thematic content analysis to analyse qualitative data collected during the data collection exercise. During the study period, computer-Aided Qualitative Data Software was used to store data in a sorted manner. The parametric variables were coded using the Predictive Analytic Software. This enabled to performance of statistical analysis and obtaining descriptive statistical outcomes were obtained. The assessment of the effect of the factors on climate adaptation strategies was done through the Likert scale. Indigenous knowledge remained widely used as a source of climate knowledge in the Gokwe South district. The research results showed that indigenous knowledge (IK) is unpredictable, productive assets and adaptive assets are inadequate, technoscience and institutional support are poor support to implement viable adaptation strategies is lacking, and poor distribution and dissemination of climate and weather information to small-scale farmers in the Gokwe South district is poor and asset portfolios and asset mix is poor. The available asset portfolios determine the adaptation strategies used in the Gokwe South district. Results show that climate vulnerability varies spatially and temporally across the Gokwe South district. The studied five constituencies for the Gokwe district have a mean vulnerability index of 3.04 with the highest index being 5 as being well adapted. Sengwa and Mapfungabutsi are highly vulnerable to the vagaries of climate variability in the Gokwe South district. The researchers recommend strong institutional support from the government. The fact that small-scale farmers should integrate their IK and modern science climate knowledge small-scale farmers in the Gokwe South district should adopt proactive or anticipatory adaptation, government climate-smart agricultural policies, and a bottom-up approach to climate variability. The quality and quantity of asset portfolios are key resources affecting the level of vulnerability to climate variability. The asset mix was seen to be significant in reducing the vulnerability of small-scale farmers in Sengwa and Mapfungabutsi, constituencies worst affected due to poor asset endowment of farmers in the Gokwe South district. The results have shown that the financial asset is the most important asset affecting vulnerability because it can be converted into other assets through buying. Weak institutional intervention renders many small-scale farmers helpless to climate variability, and the government is not fully supporting small-scale farmers to increase their adaptive capacity and resilience.
Commercial maize farmers’ adaptations to climate change in Sannieshof, North West Province, South Africa
(University of the Witwatersrand, Johannesburg, 2024) Dunn, Benjamin Graham; Knight, Jasper
Commercial agriculture is a critical industry for South Africa, both from an economic and a social perspective. Maize forms a vital part of the diet of millions of people across the country and the continent of Africa. It is also an important commercial export crop. It is, therefore, imperative that the industry can adapt to both climate and socioeconomic changes. This study aims to investigate the specific challenges faced by commercial maize farmers in the Sannieshof region, North West Province, South Africa, in relation to climate change and socioeconomic factors. This study undertook questionnaires with 21 commercial maize farmers in the region, followed up by field observations and photographs from one large commercial maize farm. Several socioeconomic factors were identified by participants as having negative impacts on farming operations, including government policies, crime, and load shedding. Climate change adaptation includes several dynamic management practices which vary between seasons, including adjustments in cultivar choice, sowing dates, sowing depth, and plant population density. Adopting conservation agriculture and precision agriculture techniques forms an important element used by the farmers to achieve long-term climate change adaptation. Going forward, farmers need to consider the impacts of both climate change and socioeconomic factors, both of which impact their agricultural operation and which can be conceptualised through a Water-Energy-Food nexus framework. Due to limited financial resources, farmers need to consider which drivers of change need to be prioritised in their decision-making, which ultimately may create differences in adaptation strategies adopted by different farmers
Compost-assisted phytoremediation of mine tailings and footprint areas using chrysopogon zizanioides (l) roberty enhanced with moringa leaf extract biostimulant in the Witwatersrand goldfields of South Africa: a sustainability initiative
(University of the Witwatersrand, Johannesburg, 2024) Mlalazi, Nkanyiso; Chimuka, Luke; Simatele, Mulala Danny
In the Witwatersrand goldfields of South Africa, mine tailings and footprint areas are significant environmental problems because they are major sources of toxic metals. These metals can leach into soils, and both surface and ground water, causing serious risks to human, animal, and plant life. In this study, the compost-assisted phytoremediation of tailing storage facilities (TSFs) and footprint soil using Chrysopogon zizanioides (vetiver grass) enhanced with moringa leaf extract (MLE) was investigated. A greenhouse experiment was conducted to identify the most favorable parameters, and was followed by a field study to test the optimized parameters under real-environment settings. For the greenhouse experiment, a 3×2×2 fully crossed factorial design was used to determine the optimum variables. Vetiver growth was assessed under three compost concentrations (0%, 30% and 60%), two types of MLE (laboratory extracted MLE and commercial MLE) and two application regimens (once a week and twice a week) were used. The biomass and metal concentrations in the vetiver grass roots and leaves were measured after sixteen weeks followed by a two-way ANOVA analysis and the post-hoc tests. All the vetiver that was planted in 0% compost died within four weeks regardless of the MLE treatment. Vetiver grass planted on the 60% compost amendments and sprayed with laboratory extracted MLE had the highest biomass production, followed by plants grown in 30% compost amendments and sprayed with commercial biostimulant. However, the heavy metal removal or uptake data by the plant was inconclusive, as most of the toxic metals were not removed by vetiver grass which was attributed to the effect of compost. Based on biomass data, the 30% compost amendment and commercial bio-stimulant was the ideal treatments for the phytoremediation of gold mine tailings using vetiver grass. Although metal accumulation by plants is one of the attributes considered in phytoremediation, it is not the most significant factor in the phytostabilisation process. Plant growth and biomass production are the most significant, therefore it is concluded that vetiver, MLE and compost can be used in the phytostabilisation of gold mine tailings, however reduction in compost may be considered in future to improve the accumulation of metals in the roots for improved results. Following the conclusion of the greenhouse study, a field study was conducted during the rainy season of 2021. Two field experiments were carried out concurrently at two sites: the footprint area (that was used as a rock dump) and the tailings storage facility (TSF 4). A split-plot design was used in this study. The experiment at each site assumed a 3×1×2 factorial design, with three levels of compost treatment (0%, 15% and 30%), 1 level of vetiver cultivar (Chrysopogon zizanioides), and 2 levels of MLE treatment (commercial MLE and tap water, both sprayed once a week). Three blocks measuring 1 m × 2 m, each with 20 holes filled with equal amounts of soil amended with the different compost levels were prepared in triplicates. A single vetiver grass slip was planted in each hole. The blocks were then divided into 2 sections, each with 10 holes, and commercial MLE was sprayed on one section, while only water was sprayed on the other section once a week. After sixteen weeks, three plants were harvested from each section and the number of leaves, leaf length, number of tillers, biomass for roots and leaves and element concentrations were measured. Data analysis was done using two-way ANOVA
Detecting Disease in Citrus Trees using Multispectral UAV Data and Deep Learning Algorithm
(University of the Witwatersrand, Johannesburg, 2024-06) Woolfson, Logan Stefan; Adam, Elhadi
There is a high prevalence, in South Africa, of fruit tree related diseases infesting lemon trees, subsequently affecting overall crop yield and quality. Ultimately, the income for the farmers is significantly diminished and limits the supply of nutritional food crops for the South African population, who already suffer from a high incidence of malnutrition. Currently, there are various methods utilized to detect diseases in fruit trees, however they pose limitations in terms of efficiency and accuracy. By employing the use of drones and machine learning methods, fruit tree diseases could be detected at an earlier stage of development and with a much higher level of accuracy. Consequently, the chances of remedying the trees before the disease spreads is greatly improved, and the supply of nutritious fruit within South Africa is increased. This research report’s aim is to investigate the effectiveness of a deep learning algorithm for detecting and classifying diseases in lemon orchards using multispectral drone imagery. This entails assessing the performance of a pretrained ResNet-101 model, fine-tuned with additional sample images, in accurately identifying and classifying diseased lemon trees, specifically those affected by Phytophthora root rot. The methodology involves the utilization of a pretrained ResNet-101 model, a deep learning architecture, and the retraining of its layers with an augmented dataset from multispectral aerial drone images of a lemon orchard. The model is fine-tuned to enhance its ability to discern subtle spectral variations indicative of disease presence. The selection of ResNet-101 is grounded in its proven success in image recognition tasks and transfer learning capabilities. The results obtained demonstrated an impressive accuracy of 80%. The deep learning algorithm exhibited notable performance in distinguishing root rot-affected lemon trees from their healthy counterparts. The findings indicate the promise of utilizing advanced deep learning methods for timely and effective disease detection in agricultural farmlands, facilitating orchard management.
Determining the spatial variations of evapotranspiration rates in a semiarid region
(University of the Witwatersrand, Johannesburg, 2024) Sorour, Wendy; Shoko, Cletah
Evapotranspiration (ET) is one of the biggest ways in which water is transferred from water resources into the atmosphere as water vapor and understanding its variations is important for water resource management. This study determined land use land cover (LULC)-based ET and the influence of climatic events in Western Cape. Landsat 8, Surface Energy Balance System, Support Vector Machine, humidity, wind speed, surface pressure, temperature, and sunshine hours were used, during El Nino in 2015-2016, normal year in 2019-2020, and La Nina in 2020-2021. Median ET was calculated for each LULC type to determine their effect on ET. Climatic events increased ET compared to the normal year and increasing temperatures and rainfall during EL Nino and La Nina years respectively were the main drivers. Water had the lowest ET, and agricultural land had the highest. The results of this study can be used to create better water resource management plans