The Bou Arada Trough is an east–west-oriented structure located 80 km SW of Tunis, characterizing the central Tunisian Atlas. This trough is filled by a thick Quaternary sand and clay series and is bordered by complex systems of folds generally trending NE–SW. Contacts between the Bou Arada Trough and the neighbouring folds are accommodated by NE–SW- and NW–SE-oriented faults. In contrast to the other troughs of the Tunisian Atlas, which are related to the Pliocene–Quaternary orogenic period, the geodynamic evolution of the Bou Arada Trough began in the Maastrichtian and has continued until the present day. Structural, tectonosedimentary and seismic data analyses are undertaken in the study area to better understand the evolutionary scenario of this trough. The results obtained show that the Bou Arada Trough is fragmented into three NW–SE-oriented sub-basins and records a continuous history of downthrow. Indeed, during extensional to transtensional regimes, this trough has evolved in response to the two networks of perpendicular fractures whereas during compressive to transpressive periods, the collapse of the Bou Arada Trough has been induced by a pull-apart mechanism using the same network of faults but with a strike-slip movement. The Bou Arada Trough thus preserves a record of the convergence between the European and African plates since the Maastrichtian.

The present work tests the use of hypsometric integral (HI) in identifying neotectonic and lithology signals in the Utica-Mateur basin (north-eastern Tunisia), a region recognised by low deformation rates. We computed HI values using three digital elevation models (DEMs) of 10, 30 and 90 m pixel resolution. We extracted maximum, minimum and mean elevations from each DEM. The obtained results reveal that the HI spatial distributions did not demonstrate clear spatial patterns and did not correlate with geological substrates. We also find that the distribution of HI is independent of the DEM resolution, but are influenced by the size of the moving window. By applying the hot spot analysis ( -statistics) on extracted HI data, we find two main clusters with high (hot spots) and low (cold spots) HI values. These hot spots correspond mainly to active faults and coincide with shallow earthquake clusters in the study area.