Acta Geodaetica et Geophysica最新文献

Mud volcanoes are geological structures observed throughout the world that arise from the upwelling of deep fluids along discontinuities in the subsoil. The detection of mud fluid migration pathways can be challenging, even when using Electrical Resistivity Tomography (ERT) as detectability issues may arise from complex geological settings. This paper presents new results from 2D and 3D ERT synthetic modelling for the investigation of the shallow, internal structure of terrestrial mud volcanoes. This study revealed the internal structure of the ‘Cenerone-Pineto’ mud volcano (Central Italy) and provided further clues as to its internal structure. The main results of the study are: the presence of a mud chamber, which represents the last phase of mud accumulation before final emission, not located beneath the crater but laterally offset, as well as the presence of a narrow, shallow feeder channel; these findings represent evidence of a much more complex structure than one would expect. This means that the mud volcano is not supplied with mud fluids directly from below as would be the case with an uprising of deep fluid along a near-vertical open fracture and that the shallow mud fluid reservoir is not correlated to the distribution of any mud volcano observed on the surface. Findings from this study are consistent with the observed structural features already noted in ERT and seismic field data collected at the ‘Cenerone-Pineto’ mud volcano and may be helpful in explaining the mechanisms and processes involved in mud volcanism in similar geological settings.

Water vapour is a critical atmospheric parameter to understand the Earth's climate system and it is characterized by a complex variability in time and space. GNSS observations have become an important source of information of the water vapour, thanks to its high temporal and spatial resolution. However, the lack of meteorological sites collocated with the GNSS site could hamper water vapour retrieval. The empirical blind models can fill this gap. This study analyses the temporal and spatial distribution of the water vapour using nine GNSS sites located on the Atlantic coast of Spain and France, with the empirical blind model GPT3 as the source of meteorological information. The observations were processed with Bernese 5.2 software on a double difference approach and validated with Zenith Total Delay EUREF REPRO2 values. Consequently, four-years series of water vapour was determined and validated using two matched radiosonde sites. The characterization of the water vapour on the area shows clear seasonal characteristics that the technique captures, using an empirical blind model for the whole process. Maximum values are observed in summer season and minimum in winter. The PWV tends to decrease with increasing latitude in the area of the study. The short-term variations can be reproduced by the high temporal resolution of the GNSS-retrieved water vapour and show a different behaviour over the area, but a similar pattern with a peak in the afternoon and minimum at night was found. Also, less variability is observed in winter season and higher in summertime.

Calculation methods for large-scale strain rate fields from GNSS horizontal velocity can be divided into two types, namely mathematical and physical methods, which reflect different characteristics of the strain rate field. Therefore, it is necessary to combine these two types of methods to obtain a more reasonable strain rate field. In this study, strain rate fields made from the least-squares collocation (mathematical method) and fault model (physical method) were jointly processed by using Helmert variance component estimation, and the reliability of the joint results was analyzed based on the simulated and measured GNSS velocity. Then, the effect of station density on the strain rate field in the Sichuan-Yunnan region was analyzed, and the results show that the mathematical method was influenced by station density significantly. Based on the joint strain rate field in the Sichuan-Yunnan region, shallow seismicity forecast rates was calculated in conjunction with the Global Centroid-Moment-Tensor Earthquake Catalogue from 1976 to 2021. The results indicate that the shallow seismicity forecast rates of the Sichuan-Yunnan region is high, with 3 Mw ≥ 7.0 earthquakes may occur every 100 years.

Ultrasonic testing techniques are non-invasive and generally used in geosciences to obtain the longitudinal and shear wave velocities for either concrete or rock materials, which are essential to investigate the physical and mechanical properties of the materials. However, the accuracy and reliability of the material velocities depend on the precise reading of the first arrival time directly on the recorder. In ultrasonic testing, due to the heterogeneity of the samples and noise, it is often problematic especially to determine the S-wave first arrival time both directly on the recorder and from the recorded signal, and this process mainly depends on user experience. This study focuses on the semi-automatic picking of the first arrival time (FAT) of ultrasonic shear (S)-wave signals. For this, after an application of a band-pass filter (BP) to suppress the noise components, the cross-correlation (CC) technique using an operator signal estimated by Kolmogorov spectral factorization from the filtered signal is applied to determine the boundaries of the possible time interval of the FAT. An automatic search then reads the FAT which encounters the maximum amplitude value within the interval. The technique has been tested for synthetic and real data sets. The results show that the FAT can be picked within safe and acceptable limits within errors ± 2.0 µs and ensure that the velocities of materials such as rock and concrete will be obtained accurately. Therefore, this also provides the ability to calculate other related physical and mechanical parameters of the materials.

This study focuses on the possible ionospheric anomalies before the Mw7.2 earthquake in Haiti on August 14, 2021. Based on the dual-frequency observation data of Global Navigation Satellite System (GNSS) stations and Global Ionosphere Maps (GIM) data products, the sliding interquartile range method was applied to detect and analyze the changes of ionospheric Total Electron Content (TEC) anomalies before the earthquake. The results show that the TEC anomalies over five GNSS stations show the common existence of anomalous times, which are July 28, August 1, August 2, August 7, and August 13, 2021, respectively. Combining space weather parameters and GIM, it is tentatively concluded that the TEC anomaly that appeared on August 1 (i.e., the 13th day before the earthquake) was not disturbed by geomagnetic storms and solar activity, and may be related to the breeding earthquake. An ionospheric anomaly close to 6 TECU was present near the epicenter 13 days before the earthquake, which is strongly associated with the peak variation of the equatorial anomaly. This suggests that an anomalously increased vertical electric field may have been generated before the earthquake, which in turn enhanced the “fountain effect” and created a strong northern hump.

Acoustic-gravity waves (AGWs) generated in the lower atmosphere can cause the ionosphere’s ionized plasma. Therefore, the electromagnetic signals transmitted from the navigation and communication satellites can be distorted based on AGWs propagating to upper atmosphere height and then disturbing the ionosphere. In this work, total electron content (TEC) was derived from dense Hubei continuously operating reference stations (HBCORS) to detect the potential ionospheric disturbance associated with a severe thunderstorm that hit Wuhan city on March 2, 2018. TEC values were examined under meticulous observation for the space weather indices. Furthermore, a de-trending algorithm, the so-called numerical divergence by multiple intervals, was applied to TEC sequences to detect the ionospheric disturbance due to the event. The slant TEC (STEC) variations near the thunderstorm area had a higher amplitude content than those that were away from it. The STEC deviations (dTEC) have been compared with a non-lighting day. Our findings indicated that the dTEC was insignificant compared with the day of the event. Afterwards, regional ionosphere maps (RIMs) were modeled through the HBCORS data around Hubei province. RIMs were employed to analyze the vertical TEC (VTEC) response to the thunderstorm. VTEC responses were detected by a proposed de-trend method so-called differences from the average value. The ionosphere showed a positive response up to 2 TECU, especially in the northern part of Hubei province where the maximum VTEC amplitude variations coincided with the thunderstorm influence. The findings are tentatively interpreted by lightning-induced electric fields and AGWs.