https://ir.unisa.ac.za/handle/10500/2785 2026-05-12T20:56:19Z https://ir.unisa.ac.za/handle/10500/32369 Beach and dune erosion along the coast of Richards Bay, South Africa and implications for the management of shoreline change Alakram, Suvana Sandy beaches are dynamic in nature and are subject to natural and anthropogenic processes that influence its evolution. One of the key drivers of coastal evolution is the erosion of the coastline. Sandy beaches are more susceptible to erosion because its fine sand is easily erodible. Since approximately 80% of South Africa’s coastline consists of sandy beaches, including environmentally sensitive dune systems, the impetus is to improve our knowledge and understanding of processes taking place at the coastal zone to aid in coastal zone management and planning for future hazards. This research integrated the use of geographical information systems (GIS), remote sensing, and modelling techniques to contribute knowledge on the interrelationships between the spatial and temporal dynamics of shoreline changes along the coast of Richards Bay, South Africa. Shoreline change rates were quantified over a 45 year period between 1977 and 2022 using the United States Geological Survey’s Digital Shoreline Analysis System. The historical data was then used to estimate future shoreline positions 10 and 20 years into the future. The results of the shoreline analysis revealed consistent erosion north of the Richards Bay harbour with a net shoreline movement of 167.80 m in some areas. The beaches south of the harbour recorded an accretional trend with a net shoreline movement of 98.90 m in some areas. The study verified that the development of the port breakwaters has caused an interruption the longshore sediment transport pattern, resulting in accretion on the updrift side (South), and erosion on the downdrift (North). The shoreline change rate statistics were used to predict future shoreline positions using the Extrapolated Linear Regression method 10 and 20 years into the future. In the context of climate change and associated sea level rise, model based approaches in ArcGIS Pro were used to assess the vulnerability of the study area to inundations caused by storm surges. The inundation screening was initated for four different surge levels using a high resolution DEM as input. The results indicated that during a 9 and 10 m storm surge, 60 and 68% of the study area respectively was inundated which serves as important baseline information for disaster risk assessments. This dissertation also explored possible pathways to coastal resilience and proposed strategies to mitigate coastal erosion and flooding in a changing environment.; Strande is dinamies en onderhewig aan natuurlike en antropogeniese prosesse wat die evolusie daarvan beïnvloed. Een van die belangrikste dryfkragte van kusevolusie is erosie van die kuslyn. Strande is meer vatbaar vir erosie omdat fyn sand maklik erodeerbaar is. Ongeveer 80% van Suid-Afrika se kuslyn bestaan uit hoofsaaklik sand dominante strande wat omgewings belangrikke duinstelsels behels. Dus is die doel van hierdie projek om ons kennis en begrip van kussoonprosesse te verbeter asook om te help met kussonebestuur en beplanning vir toekomstige gevare. Hierdie navorsing maak gebruik van ‘n metode wat geografiese inligtingstelsels (GIS), afstandswaarneming en modelleringstegnieke behels. Met die doel om die onderliggende verband tussen die ruimtelike en temporale dinamika van kuslynveranderinge langs die kus van Richardsbaai, Suid-Afrika, beter te verstaan. Die kuslynveranderingstempo's is oor 'n tydperk van 45 jaar, tussen 1977 en 2022, gekwantifiseer met behulp van die Verenigde State se Geologiese Opname se Digitale Kuslynanalisestelsel (DSAS). Hierdie historiese data was gebruik om die toekomstige kuslynposisies te skat oor 10 en 20 jaar. In sommige gebiede het die studie erosie noord van die Richardsbaai-hawe uitgewys met 'n totale kuslynbeweging van 167.80 m. Strande suid van die hawe het 'n akkresionele tendens vertoon met 'n netto kuslynbeweging van 98.90 m in sommige gebiede. Met klimaatverandering en stygende seevlaktes ingedagte, was ArcGIS Pro gebruik om die kwesbaarheid van die studiegebied vir stormvloede te modeleer en assesseer. Vier verskillende stormvloed scenarios was getoets met behulp van hoë resolusie DEMs. Die resultate wys dat 60 of 68 persent van die studiegebied sal vloed met ‘n 9 of 10 m stormvloed scenario en dien as ‘n belangrikke basislyn for toekomstige ramp en risikoassesering. Verder, ondersoek hierdie navorsing opsies om kusveerkragtigheid te verbeter en stel strategië voor om die impak van kuserosie en vloede te versag in ‘n area wat klimaatverandering ondervind. Abstracts in English and Afrikaans 2026-01-26T00:00:00Z https://ir.unisa.ac.za/handle/10500/32322 Assessing the impacts of Eyethu coal mining activities on the surrounding communities: A case study of Vosman township, Emalahleni Municipality in Mpumalanga Province. Mugagadeli, Phathutshedzo Mining is economically important. However, the sector often ignores the environmental impacts of mining activites. These impacts can seriously harm the health of local communities and damage water sources and agricultural products. The aim of this study was to investigate the impacts of Eyethu coal mining on the community of Vosman in Emalahleni, in the Mpumalanga Province, South Africa. A mixed research approach was employed, where the use of Remote Sensing to detect land-use and land-cover changes over the years was complemented by a survey (197 respondents) to assess the health impacts of the mine, while water quality assessment and risk assessment were also used to assess the impacts on the nearby river. The key findings suggested that Eyethu coal mining has contributed to the environmental degradation of the study and surrounding area, particularly the destruction of natural vegetation. Inhabitants also reported ground instability (65.9%), health impairment (55.9%, mainly respiratory illnesses), altered air (54.4%) and water quality contamination (55.9%), and this notwithstanding the fact that the people still use the river for domestic and agricultural purposes. These perceptions coincided with objective scientific evaluations of the water quality, which also concluded that the upper river section was highly acidic (pH 3.26), with considerable levels of arsenic (0.024 μg/L) and mercury (0.006 μg/L While formal inferential statistical tests were not conducted, comparative analysis of environmental indicators between the baseline period (T1) and the most recent period (T2) demonstrates a clear increase in land-use disturbance, vegetation loss, and water-quality alteration over time. All heavy metals that were measured were within the threshold of the SANS 241 standards; however, the acidic environment promotes metal solubility and poses a long-term threat to the ecosystem and human health. The Chronic Daily Intake (CDI), Hazard Quotient (HQ) and Hazard Index (HI) were all revealed to be lower than 1, which indicates a low chance of causing non-carcinogenic diseases. In conclusion, the study showed negative impacts attributed by the mine. From changes in land use and land cover, to impacts on human health as well as changes in water quality. Although water quality indices revealed that the impacts of the mine on water quality are not yet severe for assessed heavy metals, this might not be the case with other heavy metals. The study recommends a strong enforcement of environmental regulations, monitoring and rehabilitation, and community engagement in the mining decisions. Moreover, more risk assessments of other heavy metals are encouraged to generalise the quality of the nearby river.; Ngaphandle kokumelana nokubaluleka kwezomnotho wezimayini, lomkhakha uvamise ukukubukela phansi ukuhlolwa komthelela wawo kwezemvelo. Izinhlekelele ezinkulu kwezemvelo zidala ubungozi kwizempilo emiphakathini yasemazweni asafufusa, futhi kuphazamisa izitshalo kanye nemithombo yamanzi ngenxa yemisebenzi yokumba ezimayini. Inhlosonqangi yalesisifundo ukubheka umthelela emphakathini waseVosman eMalahleni, esifundazweni saseMpumalanga, eNinizimu Afrika, umthelela odalwa inkampani emba amalahle i-Eyethu. Indlela yokwenza ucwaningo oluhlanganisile yasetshetshenziswa, lapho kwakusetshenziswa I -remote sensing ukubheka ukusetshenziswa komhlaba,kanye nokuguquguquka komhlaba eminyakeni, (lolucwaningo lwenziwe kubantu abangama-197) ukubheka umthelela yezimayini, khathi kubhekwa futhi isimo samanzi kanye nobungozi emfuleni eseduzane. Imiphumela ebalulekile yaveza ukuthi inkampani yemayini i-Eyethu ibe nomthelela omkhulu ekucekelekeni phansi kwemvelo kulendowo okade kwenziwa kuyo ucwaningo kanye nasezindaweni eziyakhele, ikakhulukazi ukuphazamiseka kwezimila zemvelo. Izakhamizi/ Abahlali baphinda baveza ukungaqini kahle komhlabathi (amaphesenti angama-65.9), okukhubazeka kwezempilo (amaphesenti angama-55.9, ikakhulukazi inkinga yokuphefumula) umoya abawuphefumulayo ongekho ezingeni ngenxa yokungcoliseka (amaphesenti angama-55.4) kanye nokuphazamiseka kwezinga lamanzi ngenxa yokungcoliseka (amaphesenti angama -55.9), ngaphezu kwakho konke lokhu abantu basebenzisa wona umfula ukuthola amanzi okusetshenziswa emakhaya kanye nokuchelela izitshalo. Ngaphandle nje kokuqonda ukuqondana kwezinhloso zokubheka izinga lamanzi ngokwesayensi, okwathola ukuthi amanzi enhla nomfula anesimuncwane(i-acid) eningana (Ph3.26), kanye ne arsenic(ubuthi), obuwu (0.024ug/L) kanye ne-mercury ewu(0.006ug/L), lokkhu kuyinkoba yokuthi indawo la ukungcoliseka kwenzeka khona. Zonke izinsimbi ezisindayo zakalwa kwatholakala ukuthi ziphakathi kombundu ongama-241 SANS, ngokwamazinga, nomakunjalo, imvelo/umhlaba one -acidi kudala ukuncibikala kwensimbi futhi kudala ukuphazamiseka kwimvelo kanye nezimpilo zabantu ekuhambeni kwesikhathi. I- Chronic Daily Intake (CDI), Hazard Quotient (HQ) kanye ne Hazard Index (HI) kwavela ukuthi kungaphansi kuka1, okukhombisa amathuba amancane okuphathwa izifo ezidala umdlavuza. Esiphethweni, lolucwaningo/ lesisifundo sikhombisa umthelela ongemuhle odalwa izimayini, kusukela ekuguqukeni kokusetshenziswa komhlaba kuya ekuphendukeni kwawo, umthelela ezimpilweni zabantu, kanye nokushintsha kwezinga lamanzi. Noma inkomba ivezaukuthi umthelela wezimayini ezingeni lamanzi kawukho mubi kangako ngokocwaningo lwensimbi , lokhu kungenzeka kungafani uma ubheka olunye uhlobo lwensimbi. Lesisifundo siphakamisa kakhulu ukulandelwa kwemithetho elawula ezemvelo, ukuqapha kanye, nokuvuselela kanye,nokuxhumana nemiphakathi kwizinqumo zezimayini. Ngaphezu kwalokho,kugqugquzelwa ukuvamisa ukuhlola ubungozi bezinye izinsimbi ezisindayo emfuleni oseduzane.; Hu sa londwi ndeme ya ikonomi ya migodi, kanzhi sekithara iyi i dzhiela fhasi ṱhoḓisiso ya masiandoitwa ayo kha mupo. Masiandoitwa a mupo a vhaisaho vhukuma na a khombo ane a vhea khomboni mutakalo wa zwitshavha zwapo kha mashango a khou bvelelaho na ane a vhea khomboni zwibveledzwa zwavho zwa vhulimi na zwiko zwa maḓi zwi kolodwa mishumo ya migodi. Ndivho ya ngudo iyi yo vha i ya u sedzulusa masiandoitwa a migodi ya malasha ya Eyethu kha tshitshavha tsha Vosman ngei Emalahleni, kha vunḓu ḽa Mpumalanga, Afrika Tshipembe. Nḓila ya ṱhoḓisiso yo ṱhanganelano yo shumiswaho, hune u shumiswa ha u pfa zwi re kule u itela u vhona tshanduko dza u shumiswa ha mavu na u fukedzwa ha mavu kha miṅwaha zwo ḓadziswa nga tsedzuluso (vhafhinduli vha 197) u itela u ṱola masiandoitwa a mutakalo wa mugodini, ngeno tsedzuluso ya vhuimo ha maḓi na tsedzuluso ya khombo zwo dovha zwa shumiswa u sedzulusa masiandoitwa kha u gonya ha maḓi. Mawanwa a ndeme o sumbedza uri migodi ya malasha ya Eyethu yo shela mulenzhe vhukuma kha u tshinyadza mupo wa ngudo na fhethu ho ṱanganaho na hone, nga maanḓa u tshinyadzwa ha zwimela zwa mvelo. Vhadzulapo vho dovha vha vhiga u sa dzika ha mavu (65.9%), u sa dzika ha mutakalo (55.9%, zwihulusa malwadze a u fema), u shandukiswa ha vhuḓi ha muya (54.4%) na u tshikafhadzwa ha vhuḓi ha maḓi (55.9%), hu sa londwi uri vhathu vha kha ḓi shumisa mulambo kha ndivho dza hayani na dza vhulimi. Hezwi zwine zwa dzhiiwa zwo ṱangana na ṱhoḓisiso dza saintsi dzine dza vha na tshipikwa dza vhuḓi ha maḓi, zwe zwa dovha zwa fhedziswa nga ḽa uri tshipiḓa tsha mulambo wa nṱha tsho vha tshi na dungi nnzhi (pH 3.26), na zwikalo zwihulwane zwa aseniki (0.024 μg/L) na mekhuuri (0.006 μg/L), na uri zwi vhidzwa tshikafhadzo ya u fhisa i khalini. Tsimbi dzoṱhe dzi lemelaho dze dza kaliwa dzo vha dzi nga ngomu ha tshikalo tsha zwilinganyo zwa SANS 241; fhedzi fhethu hune ha vha na dungi zwi ṱuṱuwedza u ṱangana ha tsimbi nahone zwi vhea khombo ya tshifhinga tshilapfu kha fhethu hune zwimela, zwipuka na zwiṅwe zwivhumbiwa, khathihi na mutsho na mbonalo ya shango, zwa shumisana u itela u vhumba mapulo a vhutshilo na mutakalo wa vhathu. Chronic Daily Intake (CDI), Hazard Quotient (HQ) and Hazard Index (HI) zwoṱhe zwo dzumbululwa zwi fhasi ha 1, zwine zwa sumbedza khombo ya fhasi ya u vhanga malwadze a sa ḓivhei uri a nga vhanga pfuko. Musi hu tshi pendelwa, ngudo yo sumbedza masiandoitwa mavhi o ṱanganedzwaho nga mugodini, u bva kha tshanduko kha tshumiso ya mavu na u fukedzwa ha mavu, u ya kha masiandoitwa kha mutakalo wa vhathu, khathihi na tshanduko kha vhuimo ha maḓi. Naho vhuimo ha maḓi nga nomboro ṱhukhu ine ya papamala ine ya bvisela khagala uri masiandoitwa a mugodini kha vhuḓi ha maḓi ha athu vha mahulwane kha tsimbi dzi lemelaho dzo senguluswaho, hezwi zwi nga kha ḓi sa vha zwone kha dziṅwe tsimbi dzi lemelaho. Ngudo i themendela u kombetshedzwa ho khwaṱhaho ha milayo ya mupo, u ṱola na u vusuludza, na u dzhenelela ha tshitshavha kha tsheo dza migodi. Zwiṅwe hafhu, u ṱola khombo nnzhi dza dziṅwe tsimbi dzi lemelaho hu u ṱuṱuwedzwa u itela u angaredza vhuimo ha mulambo wa tsini. Text in English with summaries in Zulu and Venda 2025-11-01T00:00:00Z https://ir.unisa.ac.za/handle/10500/32101 Flood susceptibility analysis in Oshakati and Ongwediva within the Cuvelai-Etosha Basin (CEB), north-central Namibia, using remote sensing and GIS techniques Shakela, Tuhafeni Shiwovanhu Floods are a major problem affecting many parts of the world. Generally, the Cuvelai Etosha Basin (CEB) of north-central Namibia and specifically Oshakati and Ongwediva towns are no exceptions to this problem. Floods have ravaged the study area throughout the past and continue to do so in present times. Flood analysis in Oshakati and Ongwediva was carried out to map and determine drainage patterns, inundated zones and flood susceptibility. The research relied on collected geographic datasets of satellite images, YXZ survey points of the study area from which the DEM was created, cadastral data and participants' perceptions through a participatory GIS questionnaire. Remote sensing and GIS were used in the research. ArcGIS, Model Maker and Microsoft Excel were used in this research. Remote sensing techniques through the use of onscreen digitising was used to map shallow depressions, streams and inundated zones. Flood susceptibility was generated in ArcGIS after classifying the DEM into five elevation categories, from which flood susceptibility classes were deduced. Participatory GIS was used to further determine flood impact and rank flood susceptibility in Oshakati and Ongwediva towns. Parts of the study area were found to fall within shallow depressions and streams. Using onscreen digitisation, it was found that 18.60% of the entire towns of Oshakati and Ongwediva was situated within shallow depressions and streams, leaving 81.40% of Oshakati and Ongwediva shallow depressions and stream free. Considering the two towns individually, 21.0% of Oshakati town is in shallow depressions and streams, while 15.40% of Ongwediva town is situated in shallow depressions and streams. Shallow depressions features are primarily found in the town of Oshakati, degenerating into streams towards the southern part of the town as they flow towards Etosha pan in the south. Stream features are concentrated in the Ongwediva town, mainly in the eastern part of the town running through settlements such as the Sky location. An inundation map showed that 23% of Oshakati and Ongwediva towns was inundated during the 2009 flood season. The towns of Oshakati and Ongwediva is subjected to different flood susceptibility classes ranging from very high to very low. The very high flood susceptibility class occupied 6.54% of the two towns, while 24.48% of the Oshakati and Ongwediva towns is situated in high flood susceptible zones. Further, 32.70%, 24.52% and 11.76% of Oshakati and Ongwediva are respectively located in moderate, low, and very low flood-susceptible zones. Looking at the individual towns, Oshakati town is more susceptible to flooding than Ongwediva town, given that more of its land is situated in very high and high flood susceptible zones compared to Ongwediva town. Several institutions, businesses, public places and critical infrastructure fell into very high and high flood-susceptible zones, especially in Oshakati. In Ongwediva town, most institutions, businesses, and public places did not fall into flood-susceptible zones; they were used to being surrounded by flood water, which restricted access to them. Of all the participants in participatory GIS, 16% were never affected by floods, while 84% reported being affected by floods. Oshoopala, Uupindi and Oneshila are the most flood affected settlements in Oshakati, whereas Efidi location, Sky location and western extensions of 12-17&20 are the most flood affected in Ongwediva town based on participatory GIS data. Ekuku location in Oshakati town and the CBD and the suburbs for both towns are the least affected by floods based on participants, perceptions. Results of data analysis has indicated that Oshakati town is more prone to flooding than Ongwediva town. This is evident from very high and high flood susceptibility classes that occupies a larger area in Oshakati town than in Ongwediva town. Moreover, Oshakati town has more of its land falling within shallow depressions, streams and inundation in comparison to Ongwediva town. 2024-10-01T00:00:00Z https://ir.unisa.ac.za/handle/10500/31949 A GIS-based approach to analyse potable water acccessibility in Langeloop Village in Ehlanzeni District Municipality, Mpumalanga Mathaba, K. M. Potable water accessibility is fundamentally a human right, crucial for sustaining life and ensuring the well-being of individuals and communities. However, in rural areas, people struggle to find enough clean water to cook and drink; they travel or walk long distances to access potable water. Langeloop settlement is a rural area that struggles to access potable water. Therefore, this study aimed to analyse potable water accessibility to the Langeloop community using a GIS-based approach. Langeloop settlement consists of 11 sections/extensions used in this study. The mixed method research approach was used, and potable water sources such as standpipes were captured using a GPS, while observations and a questionnaire were used to conduct a survey. Spatial service area network analysis was performed. The findings of the study are that water accessibility is below average, and many households still do not have access to potable water. This study also found that water availability is a more prominent problem than water proximity. The recommendations of the study include 140 proposed standpipes in the areas where potable water is not accessible. However, it reflects the importance of resource allocation and targeted interventions to improve water access for communities in need. 2024-01-01T00:00:00Z