Misattributed tsunami 3: the Mw 7.7 2013.9.24 SE Pakistan earthquake

The M_w 7.7 earthquake that struck SE Pakistan on 24 September 2013 at 11.29.48 UTC was a sinistral strike-slip event on a branch of the Ornach-Nal-Chaman fault system which hereabouts separates the Eurasian Plate from the Indian Plate. Although the focus was at a depth of 15 km and 400 km inland the earthquake was accompanied by the emergence of an island off the Makran coast and the generation of a tsunami with a peak amplitude of 27 cm at Muscat (Oman) and 20 cm at Chah Bahar (Iran). At DART marine buoy 23228 in the Indian Ocean 500 km to the south a series of seismic Rayleigh waves about 4 min after the main shock was followed 54 min later by a tsunami with a peak amplitude of 1 cm. The Rayleigh series is here attributed to seafloor vibration during accelerated subduction of the Arabian Plate beneath the Eurasian Plate, and the tsunami to the development or reactivation of one or more reverse faults on the seaward portion of the Makran imbricate fan. As in the 2010.2.27 M_w 8.8 Maule (Chile), the 2004.12.26 M_w 9.2 Sumatra–Andaman, the 2005.3.28 M_w 8.7 Nias (Indonesia) and the 2011.3.11 M_w 9.0 Tohoku (Japan) earthquakes, the link between tsunami generation and slip on the megathrust is thus very indirect, to the detriment of attempts to mitigate coastal hazards using teleseismic data when nearshore seafloor monitoring would probably prove more effective.     

Mineral and chemical composition of Karak mudstone, Kohat Plateau, Pakistan: implications for smectite-illitization and provenance

The Karak mudstone interbedded in an Eocene evaporite sequence, is dominated by R-1 ordered illite-smectite with a 20 to 30% expandable component. Minor phases include kaolinite, chlorite, illite/muscovite, plagioclase, potash feldspar, quartz, dolomite and pyrite. The present illite-smectite was probably originally smectite or highly expandable illite-smectite which underwent conversion to illite-smectite with a low expandable component in a comparatively low-temperature (ca. 100°C) closed-system sedimentary basinal diagenetic environment at a depth of ca. 5 km. Al³⁺ and K⁺ necessary for the conversion reaction were provided through the breakdown of potash feldspar. Burial under a 5 km thick pile of sediments produced some of the observed structures. Whole-rock chemistry presented here suggests that the mudstone formed by severe weathering of acidic source rocks. The influx of freshwater probably flushed out Ba, Rb, Ca and Mn from the restricted basin.     

Exploring Placer Gold Deposits through Integrated Geophysical and Geochemical Techniques at the Confluence of the Indus and Kabul Rivers, NW Pakistan

Analysis of the anomalous magnetic mineral intensities and geochemistry for placer gold deposits are presented for those of the Attock area at the confluence of the Indus and Kabul rivers in northwestern Pakistan. Two grids covering an area of 10x18 m2 and 8x10 m2 were analyzed using a G-858 Cesium Vapor Magnetometer. The anomalous zones obtained were plotted on contour maps, 2D and 3D magnetic intensity maps. Based on the magnetic anomalies, grid-1 of the study area was sampled at three different anomalous zones for geochemical analysis. These zones contain gold concentrations, ranging from 2.11 ppm to 6.109 ppm with an average of 4.01 ppm. Increase in gold concentration in the subsurface within the anomalous zones indicates that magnetometer survey followed by a geochemical analysis can potentially narrow down the gold-bearing anomalous zones.     

STRUCTURAL AND THERMAL EVOLUTION OF THE SOUTH ASIAN CONTINENTAL MARGIN ALONG THE KARAKORAM AND HINDU KUSH RANGES,NORTH PAKISTAN

STRUCTURAL AND THERMAL EVOLUTION OF THE SOUTH ASIAN CONTINENTAL MARGIN ALONG THE KARAKORAM AND HINDU KUSH RANGES,NORTH PAKISTAN     

Multi-hazard susceptibility mapping based on Convolutional Neural Networks

Multi-hazard susceptibility prediction is an important component of disasters risk management plan. An effective multi-hazard risk mitigation strategy includes assessing individual hazards as well as their interactions. However, with the rapid development of artificial intelligence technology, multi-hazard susceptibility prediction techniques based on machine learning has encountered a huge bottleneck. In order to effectively solve this problem, this study proposes a multi-hazard susceptibility mapping framework using the classical deep learning algorithm of Convolutional Neural Networks (CNN). First, we use historical flash flood, debris flow and landslide locations based on Google Earth images, extensive field surveys, topography, hydrology, and environmental data sets to train and validate the proposed CNN method. Next, the proposed CNN method is assessed in comparison to conventional logistic regression and k-nearest neighbor methods using several objective criteria, i.e., coefficient of determination, overall accuracy, mean absolute error and the root mean square error. Experimental results show that the CNN method outperforms the conventional machine learning algorithms in predicting probability of flash floods, debris flows and landslides. Finally, the susceptibility maps of the three hazards based on CNN are combined to create a multi-hazard susceptibility map. It can be observed from the map that 62.43% of the study area are prone to hazards, while 37.57% of the study area are harmless. In hazard-prone areas, 16.14%, 4.94% and 30.66% of the study area are susceptible to flash floods, debris flows and landslides, respectively. In terms of concurrent hazards, 0.28%, 7.11% and 3.13% of the study area are susceptible to the joint occurrence of flash floods and debris flow, debris flow and landslides, and flash floods and landslides, respectively, whereas, 0.18% of the study area is subject to all the three hazards. The results of this study can benefit engineers, disaster managers and local government officials involved in sustainable land management and disaster risk mitigation.     

巴基斯坦近40a气温时空变化特征分析

基于巴基斯坦不同气候区4个代表站(卡拉奇、雅各布阿巴德、奎达、德罗什)1979—2018年地面观测资料和ERA-Interim气温资料,利用一元线性回归、Mann-Kendall突变检验和Morlet小波分析,分析其气温时空变化特征。结果表明:(1)巴基斯坦过去40 a经历了先降温后增温的过程,除北部山区年平均气温增温趋势显著,四季总体都有增温,春秋两季增温趋势显著。巴基斯坦于1998年左右发生气温突变,年平均气温存在4~5、12、20~22和32 a的周期。(2)ERAInterim再分析资料与地面观测数据拟合分析显示两者相关性达到极显著水平,除北部山区外,在大部分区域误差较小,能够较好地反映巴基斯坦气温的变化特征。(3)巴基斯坦年、季平均气温空间分布地带性明显,高温区位于南部印度河平原、三角洲地区,低温区分布在北部山区,年、春季、秋季平均气温变化在空间上总体均呈现明显增长趋势.