Salt tectonics in a double salt‐source layer setting (Eastern Persian Gulf,Iran): Insights from interpretation of seismic profiles and sequential cross‐section restoration

Salt tectonics in the Eastern Persian Gulf (Iran) is linked to a unique salt‐bearing system involving two overlapping ‘autochthonous’ mobile source layers, the Ediacaran–Early Cambrian Hormuz Salt and the Late Oligocene–Early Miocene Fars Salt. Interpretations of reflection seismic profiles and sequential cross‐section restorations are presented to decipher the evolution of salt structures from the two source layers and their kinematic interaction on the style of salt flow. Seismic interpretations illustrate that the Hormuz and Fars salts started flowing in the Early Palaeozoic (likely Cambrian) and Early Miocene, respectively, shortly after their deposition. Differential sedimentary loading (downbuilding) and subsalt basement faults initiated and localized the flow of the Hormuz Salt and the related salt structures. The resultant diapirs grew by passive diapirism until Late Cretaceous, whereas the pillows became inactive during the Mesozoic after a progressive decline of growth in the Late Palaeozoic. The diapirs and pillows were then subjected to a Palaeocene–Eocene contractional deformation event, which squeezed the diapirs. The consequence was significant salt extrusion, leading to the development of allochthonous salt sheets and wings. Subsequent rise of the Hormuz Salt occurred in wider salt stocks and secondary salt walls by coeval passive diapirism and tectonic shortening since Late Oligocene. Evacuation and diapirism of the Fars Salt was driven mainly by differential sedimentary loading in annular and elongate minibasins overlying the salt and locally by downslope gliding around pre‐existing stocks of the Hormuz Salt. At earlier stages, the Fars Salt flowed not only towards the pre‐existing Hormuz stocks but also away from them to initiate ring‐like salt walls and anticlines around some of the stocks. Subsequently, once primary welds developed around these stocks, the Fars Salt flowed outwards to source the peripheral salt walls. Our results reveal that evolving pre‐existing salt structures from an older source layer have triggered the flow of a younger salt layer and controlled the resulting salt structures. This interaction complicates the flow direction of the younger salt layer, the geometry and spatial distribution of its structures, as well as minibasin depocentre migration through time. Even though dealing with a unique case of two ‘autochthonous’ mobile salt layers, this work may also provide constraints on our understanding of the kinematics of salt flow and diapirism in other salt basins having significant ‘allochthonous’ salt that is coevally affected by deformation of the deeper autochthonous salt layer and related structures.     

Tree failure prediction model (TFPM): machine learning techniques comparison in failure hazard assessment of Platanus orientalis in urban forestry

Natural Hazards - Trees are generally harmed by multitude factors consisting of ecological condition and anthropogenic pressures in the cities. This study compares the multilayer perceptron (MLP)...     

Spatial interpolation of monthly and annual rainfall in northeast of Iran

Precipitation maps are the key input to many hydrological models. In this paper different univariate (inverse distance weighing and ordinary kriging) and multivariate (linear regression, ordinary cokriging, simple kriging with varying local mean and kriging with an external drift) interpolation methods are used to map monthly and annual rainfall from sparse data measurements. The study area is Golestan Province, located in northeast of Iran. A digital elevation model is used as complementary information for multivariate approaches. The prediction performance of each method is evaluated through cross-validation and visual examination of the precipitation maps produced. Results indicate that geostatistical algorithms clearly outperform inverse distance weighting and linear regression. Among multivariate techniques, ordinary cokriging or kriging with an external drift yields the smallest error of prediction for months April to October (autumn and winter) for which the correlation between rainfall and elevation is greater than 0.54. For all other months and annual rainfall, ordinary kriging provides the most accurate estimates.