Abstract
We present the Malawi Active Fault Database (MAFD), an open‐access (https://doi.org/10.5281/zenodo.5507190) geospatial database of 113 fault traces in Malawi and neighboring Tanzania and Mozambique. Malawi is located within the East African Rift's (EAR) Western Branch where active fault identification is challenging because chronostratigraphic data are rare, and/or faults are buried and so do not have a surface expression. The MAFD therefore includes any fault that has evidence for displacement during Cenozoic East African rifting or is buried beneath the rift valley and is favorably oriented to the regional stresses. To identify such faults, we consider a multidisciplinary data set: high‐resolution digital elevation models, previous geological mapping, field observations, seismic reflection surveys from offshore Lake Malawi, and aeromagnetic and gravity data. The MAFD includes faults throughout Malawi, where seismic risk is increasing because of population growth and its seismically vulnerable building stock. We also investigate the database as a sample of the normal fault population in an incipient continental rift. We cannot reject the null hypothesis that the distribution of fault lengths in the MAFD is described by a power law, which is consistent with Malawi's relatively thick seismogenic layer (30–40 km), low (<8%) regional extensional strain, and regional deformation localization (50%–75%) across relatively long hard‐linked border faults. Cumulatively, we highlight the importance of integrating onshore and offshore geological and geophysical data to develop active fault databases along the EAR and similar continental settings both to understand the regional seismic hazard and tectonic evolution.
Plain Language Summary
Earthquakes represent the occurrence of slip along cracks in the Earth's crust. Therefore, mapping these cracks, or “faults,” is important when assessing earthquake hazards. However, faults are challenging to identify as they may not be visible at the surface. Fault mapping also requires recognizing which faults have slipped in earthquakes in the recent geologic past, as these “active” faults are the most likely faults to have future earthquakes. Here, we describe how we identified active faults in Malawi, which is located along the tectonically active East African Rift. Faults under Lake Malawi were mapped using images of lake sediments that were generated from sound waves. Onshore, some faults were mapped from their expression in the landscape. Other faults, not visible at the surface, were identified from aeromagnetic data, which image the spatial distributions of magnetic minerals in the Earth's crust. Faults are considered active if that show evidence for slip during East African rifting in Malawi. We combined the active faults identified from these analyses into the Malawi Active Fault Database, a freely available geospatial database. We suggest that this database will be useful for seismic hazard planning in Malawi, where population growth and vulnerable buildings are increasing earthquake risk.
Key Points
Digital elevation models, offshore seismic reflection surveys, and aeromagnetic data are combined to identify active faults in Malawi
Mapped faults are incorporated into the Malawi Active Fault Database, an open‐access geospatial database
The mapped faults follow a power law length distribution, which is consistent with strain localization onto a few long (>50 km) faults