Acta Geophysica最新文献

The extraction of geothermal energy is associated with induced seismicity. Depending on the extraction parameters, such as injection pressure and volume, the induced seismicity is time-dependent. We investigate the case of the two geothermal power plants of Insheim and Landau, which are located in the Upper Rhine Graben in Southwest Germany. The induced seismicity was observed by a local seismic network consisting of a total of 19 stations, resulting in an earthquake catalog comprising 930 events for the Landau reservoir and 1985 events for the Insheim reservoir, both between 2012 and 2022. Based on this earthquake catalog, seismic source areas are defined for both reservoirs, and a probabilistic seismic hazard assessment (PSHA) is performed. Using temporal subsets of the earthquake catalog, PSHA can also be performed for shorter time ranges, resulting in larger expected PGV values in times of higher induced seismicity. The seismic velocity profiles obtained by site effect studies based on ambient seismic noise measurements highlight relatively large variations of the site effects on short scales in the area. The consequences of these lateral variations on the seismic hazard assessment are also discussed.

Floods are among the most widespread and devastating natural disasters, accounting for 47% of all weather-related events and affecting over 2.3 billion people, particularly in Asia. Assessing flood-prone areas is crucial for effective disaster risk reduction, but existing flood damage estimation methods, such as depth-damage functions, often lack regional adaptability and accuracy. This study addresses this gap by integrating geospatial data, remote sensing, and artificial intelligence (AI) to identify flood-affected areas in the Kan basin, Tehran. We applied deep learning methods, specifically U-Net and fully convolutional neural network (FCN) algorithms, to optical and radar images from four flood events. Our results demonstrate that the U-Net model achieves significantly higher accuracy (88%) in identifying flood-affected areas compared to the FCN model (55% accuracy). This superior performance is further supported by the mean intersection over union (mIoU) values, with U-Net achieving 0.65, compared to 0.55 for FCN. The key message of this investigation is that deep learning, particularly the U-Net model, applied to remote sensing data holds significant promise for enhancing flood monitoring, early warning systems, and disaster management strategies by enabling more accurate and timely flood assessments.

An investigation was conducted to determine radon concentrations, radon exhalation rate, and potential radiological hazard parameters associated with cement collected from five factories in Sulaymaniyah city, Kurdistan region, Iraq. Using solid-state nuclear track detectors such as CR39, the samples were analyzed by etching processes. The average radon concentration, radium concentration, and radon exhalation rate were 138.16 ({text{Bq}},{text{m}}^{ - 3}), 0.254 ({text{Bq}},{text{kg}}^{ - 1}), and 0.317 ({text{Bq}},{text{m}}^{ - 2} ,{text{h}}^{ - 1}), respectively. In sample 14, radon concentrations were within the suggested range of 200–600 ({text{Bq}},{text{m}}^{ - 3}), and the radon exhalation rate was well below the global average of 57.600 ({text{Bq}},{text{m}}^{ - 2} ,{text{h}}^{ - 1}). In addition, parameters related to potential radiological hazards were calculated for cement samples, the average annual effective dose indoor and outdoor were 3.49 and 1.31 ({text{mSv}},{text{y}}^{ - 1}), so this study's value was within the global average limitations (1–5 ({text{mSv}},{text{y}}^{ - 1})). Also, the excess lifetime cancer risk indoor and outdoor were 12.5 × 10⁻³ and 4.69 × 10⁻³ greater than the world value of 0.29 × 10⁻³.

Intensity prediction equations (IPEs) are critical for quickly obtaining the macroscopic intensity of a site post-earthquake, with regional dependencies influencing their design. Historically, most IPEs in China have focused primarily on the factors of distance and magnitude. This study develops site-specific IPEs for Western China, using data from 53 seismic events since 1970, to address the previously overlooked importance of site conditions and overcome the limitations of past models. The data were categorized into three site groups, with IPEs derived through multiple nonlinear regression methods. Our findings reveal that macroscopic intensities at category III and IV sites are notably higher than those at categories I and II, with this disparity increasing alongside the magnitude. Unlike conventional IPEs, the IPEs proposed in this paper incorporate local geological and seismological characteristics, enhancing prediction accuracy across varied site conditions. This methodology distinctly contrasts with prior approaches by providing a nuanced assessment that integrates comprehensive site categorization, resulting in more precise intensity predictions. This advancement is particularly crucial for effective emergency management and disaster mitigation strategies in seismically active regions.

This study addresses the substantial terrestrial gamma radiation exposure and associated radiological risk in the Amsoi region, located in the seismically active Kopili Fault Zone (KFZ) on the periphery of Shillong Plateau’s gneissic complex. A portable monitoring device highly sensitive to gamma radiation, equipped with a NaI (Tl) scintillator, was used to quantify the terrestrial gamma dose rates in indoor and outdoor air. The recorded dose rates varied among house patterns, with mud houses having the highest. The calculated absorbed dose rates indoors and outdoors were found to be in the range of 157.9–362.5 nGy h⁻¹ and 163.7–336.2 nGy h⁻¹, respectively, which are much higher than the reported population-weighted global averages of 84 nGy h⁻¹ and 59 nGy h⁻¹. The indoor-to-outdoor ratio was also calculated and found to be in the range of 0.7–1.4. The elevated terrestrial gamma radiation could be attributed to the geological setting of the study area, located in the seismically active KFZ. The annual effective dose equivalents for indoor and outdoor environments were calculated and found to be in the ranges of 0.8–1.8 mSv and 0.2–0.4 mSv, respectively. The excess lifetime cancer risk was assessed by calculating the lifetime effective dose and was found to be in the range of 3.4 × 10^–3–7.3 × 10^–3, which is considerably higher than the global average of 1.45 × 10^–3. This study has revealed that the populations residing in this seismically active fault zone are living precariously under high terrestrial gamma radiation.

Research in earthquake engineering heavily relies on strong motion observation. The quality of strong motion records directly affects the reliability of earthquake disaster prevention, rapid reporting of seismic magnitude, earthquake early warning, and other areas. Currently, basic mathematical methods, such as zero-line adjustment and filtering, are commonly employed to ensure the quality of strong motion records. However, these methods often rely on subjective judgment based on human experience when dealing with abnormal waveforms in strong motion records, leading to relatively low efficiency. To address this challenge, this paper proposes an innovative Transformer model based on Bayesian optimization to efficiently identify baseline drift anomalies in strong motion records. By partitioning the strong motion record data from the 1999 Chi-Chi earthquake in Taiwan, China, into two categories: high-quality records (with minimal baseline drift) and low-quality records (with significant baseline drift), we extracted data with distinct features and inputted them into the proposed model for training. Data with distinct features were extracted and input into the proposed model for training. Finally, the model was used to predict whether strong motion records exhibited baseline drift abnormalities. The experimental results show that the optimized Transformer model achieves a performance exceeding 85% in key evaluation metrics such as accuracy and F1 scores. It is capable of efficiently identifying a substantial volume of strong motion records with baseline drift within a short period of time. The model effectively performs the baseline drift classification task for strong motion records and can be used for subsequent identification of abnormalities after baseline drift correction, enabling automation in handling abnormal data related to baseline drift.

The article by Al-Najjar et al. (2022a) possesses abundant flaws in geopolitical, geographical and hydrological contexts. The paper ignores a vast body of scientific literature about the study region of the Negev Desert, Israel, in general, and Nahal Besor (Wadi Gaza) in particular. The paper’s methodology lacks data collection from the field. These gaps and flaws lead to erroneous and geopolitically slandered research conclusions. Nahal Besor is a large transboundary ephemeral river shared between Israel, the West Bank (Palestinian and Israeli territories) in the northeast, and finally, its western outlet into the Mediterranean Sea is in the Gaza Strip. Despite the current political ordeal between the two nations to accurately portray and model the segment of the river in the downstream coastal plain of Gaza, it is crucial to use the data of upstream Israeli floods that in some events reach the Strip. In this comment, we utilize some of the main flaws of Al-Najjar et al. (2022a) to demonstrate that how the hypothesized potential flood geohazard of Gaza can be significantly reduced by binational and regional cooperation such as using upbasin bank-side reservoirs in the northwestern Negev, Israel.

During the construction of deep and large foundation pits in floodplain areas, it is inevitable to cause stratum disturbance and endanger the safety of the surrounding environment. This paper focuses on the influence of deep foundation pit excavation on surrounding environment based on a soft soil deep foundation pit project in Nanjing floodplain area. A series of laboratory tests were conducted to obtain the parameters of the small strain hardening (HSS) model for the typical soil layers. Then PLAXIS 3D software is used to simulate the excavation process of the foundation pit. On the basis of field measurement and numerical model, the deformation characteristics of deep foundation pit and surrounding environment are analyzed. The HSS model and the appropriate model parameters can effectively simulate the deformation behavior during the excavation of the foundation pit. Aiming at the problem of excessive deformation of foundation pit and surrounding pipelines, the reinforcement effect of reinforced soil in active and passive areas under different reinforcement parameters is analyzed. The optimal reinforcement width and depth should be determined after reasonable analysis to obtain the best economic benefits.