Geosciences

Earthquake-induced soil liquefaction poses significant geotechnical hazards, including sand boiling, loss of foundation bearing capacity, lateral spreading, pipeline flotation, uneven settlement, and slope instability. While cyclic liquefaction constitutive models can effectively simulate and predict site liquefaction behavior, their reliability hinges on the accurate calibration of constitutive parameters. Traditional calibration methods often fail to capture the comprehensive material response, are labor-intensive, time-consuming, and susceptible to subjective judgment. To overcome these limitations, this study develops an intelligent calibration framework for a cyclic liquefaction constitutive model by integrating a numerical solver for unit tests with the genetic algorithm (GA)-based optimization framework. The proposed method is rigorously evaluated in terms of calibration accuracy, convergence, repeatability, uncertainty, and computational efficiency. Validation via a series of laboratory unit tests on materials from an extremely high earth-rock dam project confirms the method’s effectiveness. Results demonstrate that the intelligent calibration approach achieves a high accuracy of 91.84%, offering a reliable, efficient, and robust solution for parameter determination.

The island of Mindoro forms the northeastern part of the Palawan Continental Terrane, a terrane that is considered to have formed at the southwestern margin of SE China and subsequently drifted into its present position as a consequence of the opening of the South China Sea. Using U-Pb age determinations of detrital zircon in sedimentary rocks and of current river sediments, this study aims to establish the relationships between the various geological units exposed on this island. The results indicate that some established units have left no trace in the current river sediments. On the other hand, some ages found in the age distributions of river sediments have no known source in the studied units. The data presented support the concept that the Northeast Mindoro Block is distinct from the Southwest Mindoro Block. Both blocks contain units that may be correlated with units exposed in northern and southern Palawan, and thus both appear to be related to the SE China margin of the South China block.

This study presents the digitization and integration of Kazakhstan’s legacy gravimetric maps at a scale of 1:200,000 into a modern geospatial database using ArcGIS. The primary objective was to convert analog gravity data into a structured, queryable, and spatially analyzable digital format to support contemporary geoscientific applications, including geoid modeling and regional geophysical analysis. The project addresses critical gaps in national gravity coverage, particularly in underrepresented regions such as the Caspian Sea basin and the northeastern frontier, thereby enhancing the accessibility and utility of gravity data for multidisciplinary research. The methodology involved a systematic workflow: assessment and selection of gravimetric maps, raster image enhancement, georeferencing, and digitization of observation points and anomaly values. Elevation data and terrain corrections were incorporated where available, and metadata fields were populated with information on the methods and accuracy of elevation determination. Gravity anomalies were recalculated, including Bouguer anomalies (with densities of 2.67 g/cm³ and 2.30 g/cm³), normal gravity, and free-air anomalies. A unified ArcGIS geodatabase was developed, containing spatial and attribute data for all digitized surveys. The final deliverables include a 1:1,000,000-scale gravimetric map of free-air gravity anomalies for the entire territory of Kazakhstan, a comprehensive technical report, and supporting cartographic products. The project adhered to national and international geophysical mapping standards and utilized validated interpolation and error estimation techniques to ensure data quality. The validation process by the modern gravimetric surveys also confirmed the validity and reliability of the digitized historical data. This digitization effort significantly modernizes Kazakhstan’s gravimetric infrastructure, providing a robust foundation for geoid modeling, tectonic studies, and resource exploration.