This study proposes an artificial intelligence approach to assess watershed morphometry in the Makran subduction zones of South Iran and Pakistan. The integrates machine learning algorithms, including neural networks (ANN), support vector regression (SVR), multivariate linear (MLR), on a single platform. area was analyzed by extracting watersheds from Digital Elevation Model (DEM) calculating e...

In the present paper various transects perpendicular to Iranian Makran coasts (Chabahar-Gawater) were studied using satellite image processing, field observations, sandy shore profiling and grain size analysis to evaluate sedimentology and geomorphology of the area. Data revealed that the study area includes exposed rocky shores (52%), sandy shores (40%), and mud flats (8%) sheltered in estuari...

The Makran Subduction Zone is the primary seismic/tsunami hazard of northwestern Indian Ocean, but little known its on-shore seismic structure. We derived a shear wave velocity model extending to 100 km depth beneath ∼400 km-long profile oriented parallel convergence vector Arabian Sea Plate. Receiver function/surface analysis shows that average structure in coastal region comprises ∼22–28 km-t...