Acta Geodaetica et Geophysica最新文献

The Debrecen area, as part of the Great Hungarian Plain (GHP), is associated with a multi-aquifer system that is overly exploited to fulfill the development plans. This research aims to jointly interpret and model gravity and magnetic data to map the subsurface geology and structures that govern groundwater occurrence. Various potential field techniques, including spectral analysis, anomaly derivatives, analytical signal, and Euler deconvolution were employed to map the distribution and depth of the buried geological structures. The combination of the potential field techniques enabled the construction of a detailed lineament map, providing valuable insights into the distribution of the subsurface structural features. It was indicated that the main structural trend is NW–SE and NE–SW, that coincides with the main structural trends in Hungary. Subsequently, a lineament density map is derived, indicating that the eastern, central, and northwestern parts of the area form the most promising zones for groundwater prospection. The joint inversion of gravity and magnetic data has further enhanced the understanding of subsurface geology. The depth to the basement rock varied between 1.18 and 2.2 km. The highest depth to the basement meets with thick sedimentary sequences bounded by normal faults forming graben and horst structures. Moreover, the distribution of these sediments is investigated using lithological logs indicating the thickness of the main hydrostratigraphic units in the Debrecen area. These units include Nagyalföld Aquifer, Algyő Aquitard, Endrőd Aquitard, and Miocene Badenian Aquifer units, which mainly consist of sand, silt, marl, and gravel. The recent study demonstrated the effectiveness of the joint interpretation in enhancing the knowledge of lithology and geological structures. However, a detailed geophysical survey is recommended to characterize the hydrostratigraphic units in the Debrecen area.

Total least squares estimation based on Gauss–Newton method in nonlinear errors-in-variables (NEIV) model will encounter the problems of convergence, correctness and accuracy of solution related to the selected initial parameter values. In this contribution, a new total least squares estimator is introduced to solve NEIV model. This method is an extension of the homotopy nonlinear weighted least square (HNWLS) method, which is used in the nonlinear Gauss–Markov model where only the dependent variables contain random errors. The new estimator is called homotopy nonlinear weighted total least squares (HNWTLS), because it adopts weighted total least squares adjustment criterion and homotopy method to estimate nonlinear model parameters. The homotopy function of HNWTLS is constructed by using the normal equation of weighted total least squares adjustment criterion. By taking the error vector of independent variables as a parameter vector, the NEIV model is transformed into a classical nonlinear adjustment model. Then, according to the conclusion of HNWLS, the calculation formula of HNWTLS is derived, and the corresponding calculation algorithm is developed accordingly, where the standard Euler prediction and Newton correction method are introduced into it to tracks the homotopy curves. Finally, three examples to demonstrate the advantage and efficiency of HNWTLS estimator are given and some conclusions are drawn.

Possible ionospheric TEC precursor and crustal stress (b-value) precursor related to the M_w 7.7 Colima earthquake of September 19, 2022, were analyzed in the present study. b-value analysis was conducted using the Gutenberg-Richter law. Results indicate a decrease in the b-value towards the western part of Colima Rift and Michoacan Block due to an increase in the effective stress level before major earthquakes. Further, the Poisson probability was also computed from the derived data that indicates the probability of 82% occurrence for a 7.7 M_w earthquake. In addition, several negative anomalies in TEC (Total Electron Content) before the 7.7 M_w Colima earthquake were observed by GPS data. A distinct anomaly was observed on 22 August and 6 September, 2022, 28 and 13 days before the earthquake. The study also found that TEC values were significantly low in areas with lower b-values, indicating a higher probability of larger earthquakes. Additionally, a low TEC zone was detected near the epicenter before the earthquake using TEC data from a dense network of 57 GPS sites in Mexico.

The study of the thermophysical properties of coal bed mudstone at high temperatures is important for the development of compartmentalized in-situ gasification of underground coal, geothermal mining, and other engineering applications. To this end, this study analyzes the changes in the compressive strength, mineral composition, and microstructure of coal-derived mudstone when exposed to high temperatures through the use of systematic tests such as uniaxial compression and wave velocity test as well as NMR, XRD, and SEM analyses. The influence of temperature on the compressive strength of mudstones was determined, and mechanisms governing the changes in the compressive strength and thermal damage in coal-based mudstone under high-temperature conditions were revealed. The results show that the compressive strength of coal-derived mudstone initially increases and then decreases with an increase in temperature. Between room temperature and 200℃, the mudstone is subjected to thermal expansion, the compactness of the sample is enhanced and the compressive strength is improved. Between 200–800℃, the porosity of the mudstone greatly increases greatly. In addition, the number of pores and the average pore size increases, and fractures in the mineral surfaces begin to open, expand, and interconnect, compressive strength began to deteriorate. Furthermore, the mineralogy of the mudstones changes under high-temperature conditions, primarily expressed in the decomposition of kaolinite and the formation of illite as the temperatures increase. In addition, quartz undergoes a polymorphic transition, resulting in changes to the angle between Si-O tetrahedra in quartz crystals change accompanied by significant volume expansion. In addition, the breaking of O-H bonds in kaolinite results in the collapse of its crystal structure, resulting in severe mineral damage and the deterioration of the compressive strength of the mudstone.

On February 6, 2023, a magnitude 7.8 earthquake and subsequent strong seismic activity struck in Kahramanmaras region, causing over 50,000 deaths in Turkey and Syria. The earthquake resulted in a surface rupture of the East Anatolian Fault Zone (EAFZ) spanning approximately 300 km. To gain new insights into the neotectonic and current stress field in the region, we compiled 141 focal mechanism solutions (FMS) of earthquakes (with magnitude M ≥ 3) that occurred along the EAFZ between 05/01/2003 and 27/02/2023. Stress inversion, by using the Win-Tensor program, indicated a predominant strike-slip tectonic regime, with few normal and thrust events related to complex fault geometry along the principal displacement zone. The calculated pressure/tension axes in the first order stress field are mainly sub-horizontal, with a maximum horizontal compressive stress (SHmax) direction of N19 ± 9.9° E, which aligns well with the slip character of the EAFZ. To reconstruct the second and third order stress fields, the study area was subdivided into five zones based on their structures and geomorphological characteristics. Reduced stress tensors were obtained for each zone, indicating a small rotation of SHmax directions under a prevailing strike-slip faulting regime. The maximum (σ1) and minimum (σ3) stress axes are nearly horizontal; while the intermediate (σ2) stress axis is nearly vertical, consistent with a predominant strike-slip regime. The results show, also, that the Kahramanmaras earthquake was caused by the neotectonic reactivation of northeast-striking sinistral strike-slip fault, with a north–south-oriented maximum horizontal stress axis. The neotectonic activity along the EAFZ aligns well with the collision models between the Arabian and Eurasian plates. Finally, a detailed seismic hazard assessment is required for the EAFZ and nearby regions.

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.