pure and applied geophysics最新文献

Active seismic surveys, together with passive seismic monitoring surveys, magnetic and gravitational field mapping and electrical conductivity measurements (Protocol to the Comprehensive Nuclear Test Ban Treaty (CTBT), Part II), are geophysical detection technologies that can contribute jointly to the search logic for the detection of On-Site Inspection (OSI) underground anomalies or artifacts. This work has carried forward a system solution to active seismic surveys based on optical fiber sensor arrays, which in general meets the technical requirements of OSI equipment list. The system consists of 800 channels (up to 1000 channels) that include three component seismic geophones working in the frequency band 5–500 Hz (up to 1–1000 Hz). The vehicle engine driven power system can support several days of operations and the storage capacity can support several days of measurements. Fast Flexible Convolutional Neural Network (FFCNN) deep learning noise reduction method has been applied to weak signal recognition. A user-friendly 2-D/3-D human–machine interactive data interpretation software platform has been developed for the data visualization and analysis. This system is adaptable to any seismic sources, such as explosives, vibrating sources, weight drop and sledgehammers. This system has been tested and verified in the field and can be suitable for future OSI activities.

In microseismic monitoring, accurately identifying the arrival time of the P-wave initial arrival is crucial for the precise location and analysis of microseismic sources. However, due to the typically low energy of microseismic signals and poor signal-to-noise ratio (SNR), existing first-arrival picking algorithms struggle with the accuracy of picking results when dealing with microseismic data of low SNR, as they are greatly affected by strong background noise. To address this issue, this study proposes a new initial arrival identification method, which first employs variational mode decomposition (VMD) and the sample entropy method for denoising microseismic data with a low SNR, and then utilizes the pruned exact linear time (PELT) algorithm to determine the time of the microseismic initial arrival. Compared with the traditional short-term average and long-term average ratio (STA/LTA) algorithm and the Akaike information criterion (AIC) method, the method proposed in this paper demonstrates significant advantages in terms of picking precision and noise resistance.

A crisp step function is not an adequate threshold for studies of Markovian occurrence of large earthquakes, because it can lead to missing or pseudo links in an observed sequence that should be a Markov chain. A more realistic threshold is a fuzzy one where there is a transition magnitude band, located between those magnitudes that are too small for the earthquakes to be part of a Markovian process and those who are certainly large enough for the earthquakes to be part of it, where earthquakes may or may not be part of the process. This fuzzy threshold is described by a membership function that gives the probability of an earthquake with a given magnitude belonging to the process. We propose a membership function with probabilities in the transition band proportional to the seismic moment. To estimate empirical transition probabilities when considering a fuzzy magnitude threshold, we propose a counting strategy for the observed transitions and justify it through Monte Carlo simulations. The counting strategy is illustrated by application to the model from a previous seismic study of the Japan area by testing, through Monte Carlo simulations, how well the counting strategy results resemble optimum estimations of the transition probabilities. The simulations are also used to study the behavior of three Markovianity measures, and it is found that the peak values of these measures are not useful in identifying the true transition band, but that this band may be better identified by using the whole set of values taken by each measure for different transition band models. As an illustration, the measures were applied to real data from the previous study, a short set corresponding to a single realization, and found that the behavior of the measures does not agree with those expected from a crisp threshold, but agree, within the limitations of the data, with either a fuzzy threshold going from zero probability for magnitudes (Mle 6.9) to probability one for (Mge 7.2) or from zero probability for magnitudes (Mle 7.0) to probability one for (Mge 7.2).

This study presents an analytical solution for the electric current formation in the lower ionosphere as a result of charged aerosols being ejected from the ground before the earthquakes. The impact of ionosphere-related processes on radio wave propagation through the atmosphere is explored by investigating the resulting energy losses of electromagnetic waves traversing this ionospheric layer. Theoretical considerations suggest that these processes may generate detectable electromagnetic signals, offering insights into seismic precursors. The effects of electron density inhomogeneities in the upper ionospheric layers on electromagnetic wave properties such as group delay, Faraday rotation, and Doppler frequency shift are examined. Understanding these effects aims to improve ionospheric monitoring techniques to detect pre-earthquake disturbances. To validate the theoretical findings, a comparison is made with the empirical data from various sources, including VLF transmitters and GPS-TEC measurements. This comparative analysis underscores the potential of electromagnetic phenomena as credible indicators of impending seismic events.

This study examines trends in minimum and maximum temperatures at various climate stations located in different regions of Morocco for a period of five decades (1970 to 2019). Mann–Kendall, Sen’s estimator, Innovative Trend Analysis (ITA) and Innovative Polygon Trend Analysis (IPTA) were used in the analysis. The results show significant fluctuations, at different time scales, between minimum and maximum temperatures at all stations. In coastal areas, such as Rabat Sale, minimum temperatures fell during January and February while other months saw increases. Average minimum temperatures in Rabat Sale tend to fall by 0.5 °C. On the other hand, maximum temperatures in Rabat Sale rose by 0.2 °C. A decrease of 0.4 °C for T_min and 1.6 °C for T_max were observed in higher continental regions, such as Meknes. Other stations, such as Fez Sais (0.6 °C T_min and 2.6 °C T_max) and Taza (1.1 °C T_min and 2.6 °C T_max) showed an upward trend. Trends also vary, with notable increases in minimum and maximum temperatures, indicating different climatic dynamics according to altitude and locality. In particular, the ITA highlights a significant increase in annual maximum temperatures, with a P-value < 0.05 and trend slopes ranging from 0.0015 °C per year in Rabat Sale to 0.0076 °C per year in Taza. In addition, the IPTA results confirm diversity of upward and downward trends on monthly and seasonal scales, highlighting impact of geographical factors such as proximity to sea, topography, and continentality that contribute to formation of regional microclimates. The results highlight significant impact of climate change in Morocco.

On January 23, 2024, an M_w 7.0 earthquake struck Wushi County, Xinjiang. This study used Sentinel-1A data to obtain the co-seismic deformation field utilising the InSAR technique in the Wushi area. An earthquake uniform slip model was determined using a Bayesian algorithm. The earthquake fault slip distribution was inverted using the steepest descent method (SDM), and the seismic impact on neighbouring faults was evaluated using the Coulomb instability criteria. The maximum displacement was approximately 76 cm in line of sight (LOS) direction as observed using ascending Interferometric Synthetic Aperture Radar (InSAR) data. The fault is responsible for earthquake trends towards the northwest, with a dip angle of approximately 62.8°, strike of approximately 229°, and slip angle of approximately 49.8°, and it displays a compressive and sinistral strike-slip motion. The fault parameters and spatial position were aligned with the Maidan Fault at the southern margin of the Tianshan Mountains. Coulomb stress analysis revealed that regions such as the Kuokesale Fault Zone, the Dashixia Fault Zone, the Tuoshengan Fault (northwest of the epicentre), the Piqiang North Fault Zone, and the Wensu North Fault Zone situated in the southeast of the epicentre experienced stress accumulation and warranted attention. The co-seismic deformation field of the two strong aftershocks indicates a southeast-trending reverse fault located in the middle of the basin. This fault, influenced by the continuous compressive movement of the Maidan Fault, predominantly exhibited reverse movement during an earthquake. The seismic activity in the Wushi earthquake sequence indicates crustal shortening in the southern Tianshan region facilitated by the absorption of compression from the frontal compressional thrust belt and high-angle reverse faults in the orogenic belt.

This study explores the feasibility of using fluctuations in the recurrence magnitude dispersion factor (b-value) as a seismic precursor for the Mizoram earthquake that occurred on November 26, 2021, in the Indo-Burma region of northeast India. Employing a comprehensive and homogeneous earthquake catalog spanning from 1900 to 2020, the seismic analysis involved delustering and completeness testing. The research implements a sub-sectional b-value calculation method, dividing the study area into uniformly sized grid cells (2° × 2°) and performing temporal b-value mapping for each grid. The epicenter of the Mizoram earthquake was located within a grid cell characterized by an intermediate b-value. Time-series analysis of the b-value indicated a notable decline preceding the main event, suggesting its potential as a seismic precursor. The study also examines depth-dependent variations in the b-value, revealing an inverse relationship between the b-value and crustal stress. To evaluate the significance of b-value anomalies, the Kolmogorov–Smirnov (K-S) statistic was employed instead of visual inspection. Additionally, the research provides probabilistic estimates of seismic hazard parameters, including the most probable maximum yearly earthquake, mean return period, and probabilities of earthquakes of varying magnitudes. These findings contribute to a deeper understanding of the complex seismotectonic framework and high lithospheric variability in the investigated region.

The present study has employed a regional Land Surface Model (LSM) to investigate the impact of historical land cover changes on land surface characteristics over the Indian subcontinent for the period of 1930–2013. Four simulations that include a control run and three experiment runs are performed with the Noah 3.6 LSM within the Land Information System (LIS). In the present study, the Noah LSM is driven by meteorological forcings, with radiation data obtained from the Global Data Assimilation System (GDAS) and the rainfall data obtained from IMD gridded rainfall data. The control run is performed with a MODIS-IGBP land cover map, while the three experimental runs are performed with three different potential land cover maps for the years 1930, 1975, and 2013. The potential land cover maps for the above three simulations are developed by blending the MODIS-IGBP data set with the fractional forest cover data set; the latter data is available for the years 1930, 1975, and 2013. Results indicate that the historical land cover change (1930 to 2013) has reduced the annual mean of latent heat flux and net surface heat flux over the Indian domain by (-)24.74 (W/m^2) and (-)14.18 (W/m^2) respectively, while the sensible heat flux and the soil temperature has increased by 4.97 (W/m^2) and 2.78 K. The annual mean change in latent heat flux, sensible heat flux, and soil temperature demonstrate that the largest changes occur when the land cover changes from forest to urban land as compared to forest to cropland, forest to grassland and forest to open shrubland. The annual mean change in latent heat flux is moderately large for the land cover change from forest to open shrubland when compared to forest to grassland and forest to cropland. The above is attributed to the effects of evapotranspiration, which has high values for the cropland followed by grassland and open shrubland. Furthermore, the triple collocation method is employed to assess the impact of historical land cover change on soil moisture. Results indicate that the triple collocation method effectively demonstrates the impact of land cover change on soil moisture.