Source parameters calculated from displacement spectra of both P and S waves are used to discriminate between earthquakes and quarry blasts in three regions of Egypt during the 2009–2015 period. We ...use vertical component seismograms from 440 earthquakes and 450 quarry explosions with
M
D
1.5 to 3.3 to calculate source parameters, including scalar moments and corner frequencies. The
M
o
(P,S) vs.
f
c
(P,S) and P- to S-wave corner frequency
f
c
(P)/
f
c
(S) ratios are used to distinguish quarry blasts from earthquakes. A comparison of
M
o
(P,S) vs.
f
c
(P,S) for both earthquakes and explosions in Egypt demonstrates that explosions had significantly lower corner frequencies than earthquakes, particularly for S-wave displacement spectra. In contrast to the Northern and Central regions, the Southern Egyptian region provides a perfect separation of corner frequencies of earthquakes and explosions for both P- and S-waves. The empirically derived average ratio of
f
c
(P)/
f
c
(S) for earthquakes is 1.28, 1.26 and 1.26 in the Northern, Central and Southern Egyptian regions, respectively. For explosions, average
f
c
(P)/
f
c
(S) ratios are 1.89, 1.86 and 2.0 in the three Egyptian regions, respectively. According to these findings, the average ratio of
f
c
(P) to
f
c
(S) for explosions is higher than those for earthquakes, implying that the differences in ratios enhance the ability of the
f
c
(P) vs.
f
c
(S) approach to discriminate between earthquakes and explosions. Based on the average
f
c
(P)/
f
c
(S) ratios vs.
M
w
in the whole of Egypt, the observed
f
c
(P)/
f
c
(S) discrimination threshold value for separating quarry explosions from earthquakes is 1.51–1.52.
This paper introduces a new technique in the automatic detection of storm sudden commencement (SC) using the discrete wavelet transform (DWT). A geomagnetic storm is a global simultaneous phenomenon ...affecting the whole Earth, which means that all ground magnetometers running online will record this event. An algorithm using different characteristic features of the SC is proposed. The selection of an optimal threshold for feature parameters is critical for the success of SC automatic detection. Therefore, this paper uses particle swarm optimization (PSO) to determine the optimal feature threshold values. The developed algorithm is based on data records from a network of ground magnetometers. This algorithm is implemented via multi-resolution analysis (MRA) of the DWT using the Haar wavelet filter. Four-year data sampled at one sample/s from six ground stations from low to high latitudes were analyzed to develop and test this technique. Data representing 450 days from five stations operating simultaneously are available. The confusion matrix of all possible outcomes shows that the accuracy of the proposed algorithm is 97.33%.
Many quarries in East Cairo are used as solid waste landfills. These locations are now impossible to find from the ground surface due to the urban development of New Cairo. In this study, a ...subterranean landfill site near the Ring Road in East Cairo, Egypt, was found and delineated using electrical resistivity tomography (ERT) data and multi-temporal high-resolution satellite imagery. Up to 2005, the research location was a WNW-oriented quarry that had been randomly filled with diverse solid materials, according to an analysis of changes shown on the satellite images. Based on the change detection data, ERT survey planning was done. The ERT measurements identified the infill material-occupied electrically conductive zones on the plan view and separated them from the resistive zones, representing the natural soil areas. Two distinct geoelectrical units could be distinguished by combining the satellite images and the ERT results: Unit-2 (the lower unit) is characterized by high resistivity values that characterize the original soil (bedrock), whereas Unit-1 (the upper unit) is defined by low to moderate resistivity values that are the solid waste materials. The contact between the bedrock and the infill materials was mapped and delineated using the closely spaced grid of ERT profiles and the thorough topographic map. Ground surface elevation, the depth of Unit 1’s lower boundary, and this unit’s thickness change throughout the researched site are some criteria that might be addressed and used to characterize the unit of interest (Unit 1).
In this study, seismic events in Northern and Central Egypt are inspected to discriminate quarry blasts from earthquakes. We examine a collection of 639 events in both time and frequency domains ...with local magnitudes of 1.5 ≤ ML ≤ 3.3 from the Egyptian Seismological Network’s seismic event catalogue between 2009 and 2015. The maximum S-wave to the maximum P-wave amplitude ratio, complexity (C), spectral ratio (S
r
), and power of events (P
e
) classifiers as well as two statistical approaches, linear discriminant function (LDF) and quadratic discriminant function (QDF), are used to distinguish between earthquakes and quarry blasts. The usage of the LDF and QDF forms did not result in any major differences in the discrimination. The results obtained by the LDF and QDF from (P
e
-C) are the best of all approaches. The findings of all approaches were compared to get a final categorization for each event, and a decision was achieved when at least three of the four methods provided the same event category. In Northern Egypt, 243 earthquakes and 308 quarry blasts could be identified as final decisions, with two misclassified events, resulting in an overall success rate of 99.6%. In Central Egypt, 48 earthquakes and 36 quarry blasts were classified as a final decision, with two misclassified events, for an overall success percentage of 97.6%.
Geophysical surveys were conducted in the Lahun area (Fayoum, Egypt). The Lahun area is known to have been the royal necropolis during the period of Senusret II (1897–1878 BC), where he built his ...pyramid. Integrated magnetic and gravity measurements were applied to investigate five locations in the area. The gravity survey was implemented in the areas where chambers, shafts, or cavity-like structures are expected, and magnetic survey was applied in the areas where mudbrick structures are expected. The magnetic survey was conducted using a Geoscan fluxgate gradiometer, whereas the gravity survey was conducted using a Scintrex CG-5 gravimeter. The geophysical survey successfully revealed anomalies that could be part of the trench between the Queen’s Pyramid and the Senusret II Pyramid, several pits in the eastern and southern sides of Senusret II Pyramid, two chambers that could be royal tombs, and the remains of three large mudbrick structures that could be ancient warehouses.
In this work, we propose an artificial neural network (ANN) with seven input parameters for the prediction of disturbance storm time (Dst) index 1 to 12 hr ahead. The ANN uses past near‐Earth solar ...wind parameter values to forecast the Dst. The input parameters are the solar wind interplanetary magnetic field, north‐south component of interplanetary magnetic field, temperature, density, speed, pressure, and electric field. The ANN was trained on the data period from 1 January 2007 to 31 December 2015, which contains 78,888 hourly data samples. While the period from 1 January 2016 to 31 May 2017 was used to test the prediction capabilities of the ANN. Several ANN structures were tested and the best results were determined using the correlation coefficient (R) during the training and prediction phases. The results indicate an adequate accuracy of R = 0.876 for prediction 2 hr in advance and R = 0.857 for prediction 12 hr in advance. The power of the proposed ANN was illustrated using the strongest six storms recorded during the prediction period. Generally, the duration and number of the input parameters significantly affect the training and prediction performance of the applied ANN. The results are outstanding in term of accuracy when considering a medium‐term prediction of 12 hr in advance and in terms of timing of the Dst minimum occurrence. In addition, the results show a strong dependence on the solar wind electric current.
Plain Language Summary
We propose an artificial neural network for the prediction of disturbance storm time (Dst) index 1 to 12 hr ahead. The ANN uses 24 past hourly solar wind parameters values to forecast the Dst index. The input parameters are the solar wind interplanetary magnetic field, southward component of interplanetary magnetic field, temperature, density, speed, pressure, and electric field. Several ANN structures were tested and the best results were determined using the correlation coefficient (R) during the training and prediction phases. The results indicate an adequate accuracy of R = 0.876 for prediction 2 hr in advance and R = 0.857 for prediction 12 hr in advance. Generally, the duration and number of the input parameters significantly affect the training and prediction performance of the applied ANN. The results are outstanding in term of accuracy when considering a medium‐term prediction of 12 hr in advance and in term of timing of the Dst minimum occurrence. In addition, the results show a strong dependence on the solar wind electric current.
Key Points
Optimized ANN structure to forecast the Dst index
Solar wind parameters were used for forecasting the Dst index 1 to 12 hr in advance
Investigating the geoeffectiveness of the solar wind parameters
Kamil Crater in Egypt Folco, Luigi; Di Martino, Mario; El Barkooky, Ahmed ...
Science (American Association for the Advancement of Science),
08/2010, Letnik:
329, Številka:
5993
Journal Article
Recenzirano
We report on the detection in southern Egypt of an impact crater 45 meters in diameter with a pristine rayed structure. Such pristine structures are typically observed on atmosphereless rocky or icy ...planetary bodies in the solar system. This feature and the association with an iron meteorite impactor and shock metamorphism provides a unique picture of small-scale hypervelocity impacts on Earth's crust. Contrary to current geophysical models, ground data indicate that iron meteorites with masses of the order of tens of tons can penetrate the atmosphere without substantial fragmentation.
The Geomagnetic storms are considered as one of the major natural hazards. Egyptian geomagnetic observatories observed multiple geomagnetic storms during 18 February to 2 March 2014. During this ...period, four interplanetary shocks successively hit the Earth’s magnetosphere, leading to four geomagnetic storms. The storm onsets occurred on 18, 20, 23 and 27 February. A non-substorm Pi2 pulsation was observed on 26 February. This Pi2 pulsation was detected in Egyptian observatories (Misallat and Abu Simbel), Kakioka station in Japan and Carson City station in US with nearly identical waveforms. Van Allen Probe missions observed non-compressional Pc4 pulsations on the recovery phase of the third storm. This Pc4 event is may be likely attributed to the decay of the ring current in the recovery phase.
The flood plain of the Nile River has been a safe dwelling throughout history. Recently with a growing population and vast growing urbanization some buildings have started to experience structural ...damages, which are not related to their construction design, but rather to the ground conditions around the buildings’ foundations. Variations in properties of the soil supporting the buildings’ foundations such as soil bearing capacity, moisture content and scouring may eventually lead to the failure of these buildings. This study is attempting to characterize the variations in the soil properties around the City Star shopping mall, in eastern Cairo, where a large building has tilted over the past few years. This tilting may lead to the collapse of the whole building if it continues at the same rate. An integrated geophysical investigation including multi-channel analysis of surface wave (MASW), ground penetrating radar (GPR) and 2-D electrical resistivity tomography (ERT) was used around the affected building to help detect possible causes of deterioration. The GPR data showed a soil-fill layer overlaying a thick bottom layer of higher moisture content. The MASW data revealed a middle layer of relatively low shear wave velocity sandwiched between two relatively high shear wave velocity layers. The ERT data showed an upper low resistivity layer overlying a high resistivity layer. Integrating the interpretations of the three geophysical methods provide a combined model that reflects lateral and vertical variation in the soil properties. This variation becomes dramatic near the tilted corner of the building.
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