The aim of this work is to identify and characterize microtextural signatures in silica glass grains (used as analogous to quartz) that are produced during aqueous transport at different flow velocities, with variable sediment concentrations, transport distances, and time intervals. To achieve this, an open-channel flow experiment was conducted with a mixture of sand and silica glass microspheres in varying conditions—velocity (from 0.67 to 1.4 m/s), duration (1 or 10 minutes), distance (0 to 2.5 m) and sediment concentration (60 or 80%). Experimental conditions were used to replicate natural phenomena such as river superficial velocity or coastal swash processes. Before the experiment the microsphere surfaces were imaged and clear of any microtextural imprint. Increasing velocity, distance, and sediment concentration exhibited a strong correlation with higher numbers of surfaces abundantly covered with microtextures of mechanical origin (i.e., craters, abrasion marks, and v-shaped percussion marks). SEM microphotographs of silica were analyzed and classified to provide examples of the specific microtextures produced during the open-channel flow experiment. The purpose of the experiment was to characterize surface microscopic signatures in quartz grains replicating hydrodynamic conditions of coastal and fluvial environments. The results demonstrated a strong correlation between higher velocities (and higher sediment concentrations) and a larger presence of microtextural mechanical imprints in the grains analyzed, thus demonstrating a clear relation between microtextural imprints and water flow modes. These results have important implications for future microtextural works analyzing grain imprints and their relation to sediment transport types. An example demonstrated here is that the higher presence of v-marks could be used as an indicator of supercritical flow conditions.

Risco Geológico: Uma Abordagem Integrada entre Métodos de Mapeamento Geotécnico Analisados em Nova Friburgo, RJ

Climate change-driven rainfall extremes are increasingly threatening global road infrastructure through amplified landslide hazards. Here we quantified global landslide susceptibility by coupling seven machine learning models with ensemble projections from the Coupled Model Intercomparison Project Phase 6 under four shared socioeconomic pathways. Results indicate a general upward trend in global road risk, with the most severe rise (approximately 30.6%) occurring under the high-emission scenario by 2100. Currently, approximately 8.3% of the global land area of the road is at high and very high risk of landslides, mainly concentrated in eight hotspots, including the middle west of North America, eastern United States, western Europe, South and East Asia, and southeastern Asia. Across countries with different income levels, high-income countries’ road risk exceeds others by 2–5-fold. These projections highlight the urgent need for climate adaptation strategies in high-risk regions, particularly where aging infrastructure intersects with intensifying hazards in high-income countries.

The precise location of the seismic source of 1755 CE Great Lisbon earthquake is still uncertain. The aim of this work is to use an onland sedimentary record in southern Portugal to test and validate seismic sources for the earthquake. To achieve this, tsunami deposit thicknesses from over 150 cores collected at Salgados in southern Portugal were compared to the results of a tsunami sediment transport model (Delft3D‐FLOW) that simulates tsunami propagation, inundation, erosion, and deposition. Five different hypothetical seismic sources were modeled with varying bed roughness coefficients to assess how well they reproduced observed patterns of tsunami deposit thicknesses and dune. Modeled and observed historical tsunami arrival times were also used to test different earthquake sources. Based on these comparisons, three modeled earthquake sources were able to reproduce the observed data, suggesting they should be regarded as somewhat more likely sources for the 1755 earthquake in contrast to four other modeled sources. The fault closest to shore (Marquês de Pombal) yielded the best correlations between model and observations.