pure and applied geophysics最新文献

Mining operations are essential for various industrial sectors, requiring a comprehensive approach to exploration, extraction, processing, and waste management. In uranium mining, waste management is particularly critical due to the presence of radioactive materials in tailings, posing environmental and public health risks. Geotechnical characterization of rock masses supporting tailings dams is fundamental to ensuring structural integrity and safety. This study aimed to correlate compressional wave velocities with geomechanical rock quality parameters in the foundation of a radionuclide storage dam. While the initial analysis suggested a reasonable correlation, the application of this relationship to new seismic tests during the mine’s decommissioning phase did not yield a significant predictive capability. Despite this limitation, the consistency between rock quality designation values obtained via photogrammetry and geophysical methods underscores the potential of integrated approaches for rock mass assessment. These findings contribute to geotechnical, mining, civil engineering, and geophysical applications, reinforcing the need for multi-method validation in subsurface investigations.

The CSIR-NGRI, Hyderabad, conducted seismic imaging of the crust and lithosphere structures of the Hyderabad region during the period 2020–21 by installing a 10-station broadband seismic network. The data from this network was used to perform a joint inversion of P-radial receiver functions (PRFs) and fundamental mode group velocity dispersion data of Rayleigh waves to estimate the crustal and lithospheric thicknesses beneath the eastern Dharwar Craton (EDC), India. Modelled Moho depths range from 35.5 to 37.6 km, with a mean of (36.7 ± 0.7) km, while modelled lithospheric thicknesses range from 134.0 to 154.0 km, with a mean of (139.6 ± 6.7) km. The modelled Moho depths reveal an NW–SE trending crustal thinning in the southwestern part of the Hyderabad region while the modelled lithospheric thicknesses show an NNE-SSW trending elongated region of down-warping below the central part of the study region, which is bounded by thinning of the lithosphere on both the eastern and western sides. A stacking of radial PRFs using the common conversion point (CCP) indicates three seismic discontinuities, namely the Moho discontinuity (an increase in positive PRF amplitude at 30.0–35.0 km depth), the Hales discontinuity (an increase in positive PRF amplitude at 90.0–115.0 km depth), and the Lithosphere-Asthenosphere Boundary (an increase in negative PRF amplitude at 140.0–160.0 km depth). Our modelling reveals a (36.7 ± 0.7) km thick Archean crust and a (139.6 ± 6.7) km thick lithosphere beneath the Hyderabad region, indicating the absence of a thick cratonic root beneath the EDC.

The Banda Islands is a sub-district within the Province of Maluku. As outlined in the Regional Spatial Plan for the period 2011–2031, Banda Island is specifically delineated as the Provincial Strategic Activity Center, with a primary focus on tourism as the key strategic activity. However, it is imperative to note that the Banda Islands are highly susceptible to earthquakes and tsunamis. Majority tsunamis occuring in Banda Islands classified as near-field tsunamis, so the rapid execution of data collection, processing, modelling, and analysis is crucial. But, the technical data available for tsunamis in this area is notably limited. This study endeavours to address this gap by constructing a comprehensive tsunami database through simulations and numerical modelling of various scenarios. The TUNAMI F1 model, a simulation methodology grounded in linear equations for tsunami wave propagation, is employed in this research. By leveraging historical earthquake source data, the model generated tsunami data amounting to 1,647 instances from 234 earthquake epicentres. Notably, the magnitude of an earthquake and its proximity directly correlate with the resultant maximum wave height and arrival time; higher magnitudes and closer proximity lead to increased wave height and swifter arrival times. The computed maximum tsunami height at the Banda Islands is estimated to reach 13 m. Furthermore, the arrival time for a tsunami exceeding 2 m in height ranges from 0 to 46 min at two designated observation points within the Banda Islands. This dataset is anticipated to serve as a valuable addition to the existing database managed by the Meteorology, Climatology, and Geophysical Agency (BMKG), enhancing its comprehensiveness. This database is intended to support tsunami early warning systems (TEWS) through rapid scenario retrieval in coastal areas. Additionally, it is poised to fortify the efficacy of the tsunami early warning system, thereby contributing to the development of a disaster-resilient tourism sector in the Banda Islands.

Using the dimensional analysis a novel model for shock wave generation during explosive volcanic eruptions is proposed. An analytical derivation of the dependence of the shock wave’s peak pressure on the initial energy and the distance from the epicenter in the case of a volcanic explosion has been obtained, whose predictions agree with the results of numerical modeling within the margin of error. A relationship between the parameters of the shock wave in the vicinity of the source and those of the atmospheric Lamb wave is established, offering an explanation for the phenomenon of longer-than-expected periods in volcanic Lamb waves, first observed following the 1980 eruption of Mount St. Helen’s. Differences between atmospheric Lamb waves generated by volcanic explosive eruptions and thermonuclear tests are studied. Additionally, based on the introduced model, a method for estimating the composition of volcanic gases based solely on observational data from points distant from the epicenter is proposed. The model’s consistency with observational data is demonstrated through a comparison with barographic measurements from the January 15, 2022, Hunga-Tonga eruption, provided by Albuquerque Seismological Laboratory, where the Lamb wave was recorded at 50 stations worldwide. The evolution of Lamb wave parameters with distance and its attenuation characteristics were investigated using observational data.

Numerous rockfalls occur along the southern foothills of the Alborz mountain range, particularly affecting the Chalus highway. This study aims to identify the key factors influencing rockfall events and to produce a susceptibility zoning map using GIS-based modeling techniques. A high-resolution 10-m DEM, geological maps, and field data were integrated to simulate rockfall frequency, velocity, height, and energy. The analysis identified nine high-risk zones along the highway corridor. Results indicate that while tectonic activity plays a role in rock fragmentation, climatic conditions particularly freeze–thaw cycles during winter are the main trigger for rockfalls. The generated susceptibility map provides essential information for road management and risk mitigation strategies.

Certain regions of Algeria, particularly in the Northeast, are currently facing heightened seismic activity alongside considerable social and economic challenges. Should a seismic event akin to the Djidjelli (now Jijel) earthquake of August 21 and 22, 1856, strike again, numerous coastal cities may suffer significant damage. This study is part of a broader project aimed at estimating seismic risk and damage levels following seismic events, with a particular focus on initial acceleration computation, which serves as a crucial tool for our modeling. Given the significance of conducting studies that enable the estimation of seismic risk and potential damage in urban agglomerations, the overall goal of this work is to assess seismic risk in an urban agglomeration using a deterministic scenario to estimate the risk, seismic vulnerability and damage potential. We provide a seismic risk scenario for Jijel city, with a particular focus on the susceptibility of its historically significant districts: Bourmel-Ben Achour, Ouled Aissa–Camp Chevalier, and the Old City. Using a Ground Motion Prediction Equation, we calculated the maximum expected ground acceleration based on the following considerations: (a) the 1856 Jijel seismic event as a reference; (b) site impacts associated with the area’s geological characteristics; (c) building damage; and (d) seismic vulnerability. This research presents a Peak Ground Acceleration (PGA) map that incorporates the influence of site lithology (Avib). The highest acceleration was recorded in the city center, with EC8 offering a reliable estimate of acceleration across all three examined areas: Bourmel-Ben Achour, Ouled Aissa–Camp Chevalier, and the Old City. The strongest tremors are felt in Jijel’s city center and eastern regions. Correlation with the geological features reveals an estimated PGA of 0.28 g in the Old Town area. This estimate closely aligns with the PGA of 0.52 g obtained from our independent analysis, which accounts for local lithology and site conditions. Furthermore, according to the RPA (Algerian earthquake engineering code) the Jijel province is classified as Zone IIa (medium seismicity), with an acceleration data of 0.25 g. This study integrates Geographic Information Systems (GIS) data into risk models.

The impacts of climate change on precipitation and drought are of great importance for agriculture, water resources and ecosystems. The CMIP6 models developed by the Intergovernmental Panel on Climate Change (IPCC) within the scope of the Coupled Model Intercomparison Project Phase 6 (CMIP6) simulate future climate conditions under various climate scenarios and provide a better understanding of possible changes at regional and global levels. In this study, 4 different CMIP6 models, namely CANESM5, EC-EARTH3, MIROC6 and MRI-ESM2, were used to model future precipitation and temperature data in Isparta region located in the Lakes Region. Six different optimistic and pessimistic Shared Socioeconomic Pathway (SSP) scenarios, namely SSP1-1.9, SSP1-2.6, SSP2-4.5, SSP3-7.0, SSP4-6.0 and SSP5-8.5, were considered in the modelling phase. In the projections made until 2100, it is predicted that in optimistic and pessimistic scenarios, temperature increases may reach up to 2.84 °C, 3.3 °C, 4.06 °C, 5.18 °C, 4.77 °C and 5.78 °C, respectively, and precipitation may decrease by approximately 14.9%. In addition, the results obtained from drought analyses using the Standardized Precipitation Index (SPI) show that the severity and duration of current droughts will increase significantly in the future due to decreases in precipitation and increases in temperatures in the coming years. In Isparta, which is located in the Lakes Region, a region vulnerable to drought, it is very important to develop drought management strategies in order to minimize the effects of severe droughts that may occur in the future.

Graphical abstract

Earth science has embraced the application of deep learning (DL) across various fields. The research aimed to enhance the Analog Data Assimilation (AnDA) approach by integrating a DL technique. This involved using a representative catalog of the dynamical model to rebuild the system dynamics. The outcome of this was the development of the Deep Data Assimilation (DeepDA) technique, which uses ensemble-based assimilation methods like the Ensemble Kalman Filter (EnKF) and Particle Filter (PF) along with DL to model system dynamics. To achieve this, an artificial recurrent neural network with a long short-term memory (LSTM) architecture was utilized for data-driven forecasting. To assess the effectiveness of DeepDA as compared to the AnDA model-driven assimilation methods, a series of numerical experiments were conducted using the chaotic dynamical model Lorenz-63. The results demonstrated that DeepDA exhibits highly efficient computational capabilities and satisfactory prediction accuracy and skills compared to AnDA.