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Investigating seismicity in Cape Town: implications for active fault lines in the Western Cape, South Africa
Despite being in a stable continental region (SCR), South Africa has experienced significant seismic activity. Historical records cite a possible 6.5 magnitude earthquake in Cape Town in 1809. On September 29, 1969, a 6.3 magnitude earthquake struck the Ceres-Tulbagh region, less than 100 km from th...
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| Format: | Thesis |
| Language: | English English |
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Department of Geological Sciences
2026
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| Summary: | Despite being in a stable continental region (SCR), South Africa has experienced significant seismic activity. Historical records cite a possible 6.5 magnitude earthquake in Cape Town in 1809. On September 29, 1969, a 6.3 magnitude earthquake struck the Ceres-Tulbagh region, less than 100 km from the Koeberg Nuclear Power Station (KNPS) in Cape Town. Previous studies have found a relationship between enhanced micro-seismicity over long periods and source zones of historical SCR earthquakes. This thesis seeks to identify heightened micro-seismic activity on regional fault structures to infer potential source zones for the 1809 event and future damaging earthquakes. To achieve this, eighteen three-component geophones were deployed across a 40 by 35-kilometre area near the KNPS. The geophones recorded data from August to October 2021 and were located near the Ceres-Tulbagh region, Cape Town, the proposed Milnerton fault, and the Colenso fault zone. Seismicity around these fault zones was analyzed using machine learning, visual inspection, and Short-Time Average to Long-time Average (STA/LTA) algorithms. Thirty-five events were found, categorized into two groups of elevated seismicity: one group was located offshore, outside the study area, while the other was situated between the proposed Milnerton fault and the Colenso fault system. Within the second group, the Colenso fault system shows elevated micro-seismicity, indicating that it is potentially active. Additional findings suggest that machine learning and visual examination of waveform data are more accurate than STA/LTA algorithms combined with manual assessment at detecting micro-seismic phases and consequently events. |
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