塔里木盆地西部白垩纪—古近纪海相地层框架及对重大地质事件的记录

塔里木盆地西部白垩纪—古近纪发生了大规模的海侵事件,形成一个喇叭状向西开口的海湾,该海湾属于东特提斯洋的一个分支。该地区白垩纪—古近纪海相地层记录了东特提斯洋演化和一系列重大地质事件,具有重要的研究价值,但对其地层的研究仍相对薄弱,对重大地质事件的研究还不够深入。本文拟通过详细的岩石地层、生物地层和其他地层方法,完善地层划分与对比框架,并在此基础上讨论Cenomanian/ Turonian界线大洋缺氧事件(OAE2)、白垩纪/古近纪界线(K/Pg)、古新世—始新世极热事件(PETM)、特提斯海进与海退等一系列重大地质事件。塔里木盆地白垩纪—古近纪海相或海陆过渡相地层自下而上为克孜勒苏群、库克拜组、乌依塔克组、依格孜牙组、吐依洛克组、阿尔塔什组、齐姆根组、盖吉塔格组、卡拉塔尔组、乌拉根组和巴什布拉克组,上述地层中含有丰富的有孔虫、介形虫、钙质超微、沟鞭藻、孢粉、双壳类、腹足类等化石,以及少量菊石、腕足类、海胆和鲨鱼牙齿等化石。综合的生物地层和年代地层研究表明,克孜勒苏群的时代为早白垩世Barremian-Albian期,库克拜组—依格孜牙组的时代为晚白垩世Cenomanian-Maastrichtian期(Cenomanian/Turonian界线可能位于库克拜组三段),吐依洛克组的时代为白垩纪—古近纪过渡期;阿尔塔什组的时代为古新世早中期,齐姆根组为古新世晚期—始新世最早期,盖吉塔格组—乌拉根组的时代为中始新世中晚期,巴什布拉克组的时代为晚始新世,但不排除最上部进入渐新世早期。塔里木盆地的海侵开始于克孜勒苏群中上部沉积期(Albian晚期—Aptian早期),但规模很有限,大规模的海侵始于晚白垩世Cenomanian早期;从晚白垩世—古新世,共经历了5次大规模的海侵—海退事件;大约41 Ma前后,海水退出盆地南部的昆仑山山前,34 Ma前后,海水退出盆地北部的天山山前。上述海侵—海退事件可能受构造和全球海平面变化的双重影响,但构造事件对海侵的启动和结束可能更具决定性的影响。阐述了塔里木盆地西部白垩纪—古近纪海相地层所记录的OAE2、K/Pg界线、PETM和特提斯海侵—海退等事件,其中笔者及团队第一次在塔里木盆地西部齐姆根组中所发现和报道的PETM事件,将有助于揭示全球近岸地区PETM的特征和生物-环境响应。在未来的研究中,需要进一步厘清塔里木盆地西部地层序列,建立更加精细的生物地层和年代地层框架,加强对PETM和特提斯海侵—海退等重大地质事件的研究。     

Effects of climate anomaly on rainfall,groundwater depth,and soil moisture on peatlands in South Sumatra,Indonesia

Climate anomalies can cause natural disasters such as severe fires and floods on peatlands in South Sumatra. Factors that affect the natural disasters on peatlands include rainfall, groundwater level, and soil moisture. This paper aims to study the effect of the climate anomalies in 2019 and 2020 and effects of these influencing factors on peatlands in South Sumatra. The data used in this study was derived from in-situ measurement at two SESAME’s measurement stations in the study area. The results indicate that in the 2019 dry season, the rainfall was minimal, the lowest groundwater table depth was ?1.14 m and the lowest soil moisture was 3.4%. In the 2020 dry season, rainfall was above the monthly average of 100 mm, the lowest groundwater level was ?0.44 m, and the lowest soil moisture was 26.64%. There is also a strong correlation between soil moisture and groundwater table depth. The correlation between the two is stronger when there is less rainfall.     

Knickpoints along the upper Indus River,Pakistan: an exploratory survey of geomorphic processes

This article summarizes an exploratory study carried out to investigate the significance of various geomorphic features on the formation of observed knickpoints along the upper Indus River in northern Pakistan. These features include bedrock lithology, active faults, sediment flux from tributary channels, and landslide dams which have blocked the main channel. The knickpoints and their related geomorphic parameters (channel profile, concavity, drainage area and normalized steepness index, etc.) were extracted from Advanced Spaceborne Thermal Emission and Reflection (ASTER) Global Digital Elevation Models (GDEMs) with 30 m resolution using ArcGIS, River Tools, and Matlab software. A total of 251 major and minor knickpoints were extracted from the longitudinal profile along a ~ 750 km reach upstream of Tarbela Reservoir. The identified knickpoints and their respective normalized steepness index (k_sn values) were compared with bedrock lithology, mapped faults, regional landslide/rockslide inventory, and the locations of historic landslide dams. The analyses revealed that the knickpoints do not correlate with the bedrock lithology except where major unit boundaries coexist with mapped faults, especially in reaches criss-crossed by active thrust faults in the Nanga Parbat Haramosh (NPHM) region. Neither did the river’s major confluences exhibit any notable knickpoints, but the correlations between knickpoints, mapped landslides, and historic rockslide avalanche dams accounted for approximately 75% of the observed knickpoints, a surprising finding. These observations suggest that more detailed studies aided by high resolution data should be undertaken to further explore the characteristics of knickpoints triggered by tectonic uplift, local fault offset, bedrock erodibility, and landslide/rockslide dams.     

Landslide inventory and susceptibility assessment using multiple statistical approaches along the Karakoram highway,northern Pakistan

China-Pakistan Economic Corridor(CPEC)is a framework of regional connectivity,which will not only benefit China and Pakistan but will have positive impact on Iran,Afghanistan,India,Central Asian Republic,and the region.The surrounding area in CPEC is prone to frequent disruption by geological hazards mainly landslides in northern Pakistan.Comprehensive landslide inventory and susceptibility assessment are rarely available to utilize for landslide mitigation strategies.This study aims to utilize the high-resolution satellite images to develop a comprehensive landslide inventory and subsequently develop landslide susceptibility maps using multiple techniques.The very high-resolution(VHR)satellite images are utilized to develop a landslide inventory using the visual image classification techniques,historic records and field observations.A total of 1632 landslides are mapped in the area.Four statistical models i.e.,frequency ratio,artificial neural network,weights of evidence and logistic regression were used for landslide susceptibility modeling by comparing the landslide inventory with the topographic parameters,geological features,drainage and road network.The developed landslides susceptibility maps were verified using the area under curve(AUC)method.The prediction power of the model was assessed by the prediction rate curve.The success rate curves show 93%,92.8%,92.7%and 87.4%accuracy of susceptibility maps for frequency ratio,artificial neural network,weights of evidence and logistic regression,respectively.The developed landslide inventory and susceptibility maps can be used for land use planning and landslide mitigation strategies.     

Geochemistry and Mineralogy of Paleocene Coal from the Padhrar and Darra Adam Khel Coalfields of Pakistan

Pakistan is rich in coal resources, which amount to around 186 billion tons. The Paleocene Padhrar and Darra Adam Khel coalfields are located in the Central Salt Range Punjab Province and the Khyber Pakhtunkhwa Province, Pakistan, respectively. Padhrar coal has not been studied in detail and the Darra Adam Khel coalfields are newly-discovered, so no research has been done, due to security considerations. In this study, an attempt has been made to study the geochemical and mineralogical characteristics of the Padhrar and Darra Adam Khel coals, in order to learn about the coal quality, element enrichment mechanism, sedimentary medium conditions and potentially valuable elements for coal utilization. The Padhrar and Darra Adam Khel coals are low to medium ash, low moisture content, high in volatiles and high total sulfur coal. The vitrinite reflectance in Darra Adam Khel coal is higher than in Padhrar coal, indicating either a greater burial depth or the effects of Himalayan tectonism. The vitrinite content is dominant in the Padhrar and Darra Adam Khel coals, followed by inertinite and liptinite, the major minerals including quartz, clay minerals, calcite and pyrite. The trace elements Ni, As, Be Zn, Ge, Mo, Ta, W, Co and Nb, Sn, Hf, Ta, Pb, Th, Cd, In, Be, V, Cr, Zr, Ag, Li, W and Co are concentrated in some of the Padhrar and Darra Adam Khel coal samples, respectively. The Padhrar coal shows positive Ce, Eu and Gd anomalies, with most of the Darra Adam Khel coal showing negative Ce, Eu and positive Gd anomalies with high LREE. The Al2O3/TiO2 values indicate that the sediment source of the Padhrar and Darra Adam Khel coals is mostly related to intermediate igneous rocks. The Sr/Ba, SiO2 + Al2O3, Fe2O3 + CaO + MgO/SiO2 + Al2O3 and high sulfur content in the Padhrar and Darra Adam Khel coals indicate epithermal and marine water influence with a tidal flat, coal-forming environment and a deltaic coal-forming environment, respectively.     

High-resolution regional gravity field model of Pakistan based on best residual terrain model (RTM) of topography and interpolation techniques

This study focuses on the development of absolute gravity model for Pakistan based on best possible residual terrain model of gravity using residual terrain modeling technique. The datasets used for the development of model are observed gravity, global gravity models, and Shuttle Radar Topographic Mission (SRTM30) elevation data. The residual terrain modeling technique has been used in the remove-restore procedure for smoothing the observed gravity field. Different topographic elevation models were tested in the model selection and one best possible model with minimum mean and standard deviation was selected for residual terrain effects. Least square collocation technique has been used for quality control and error estimates. The best possible covariance model was established from residual gravity for onward prediction of gravity anomalies at the earth surface for error and prediction analysis. The residual terrain effect of gravity, value of free air anomaly from EGM96, and observed free air anomaly are added to normal gravity to compute the absolute gravity at earth surface. The prediction of these parameters is made by employing Lagrange interpolation with least square adjustment. The results are compared with ～5% randomly selected data points not utilized for the development of covariance function and/or model development. Spline interpolation technique has also been used for the prediction of gravity field-related parameters. Lagrange interpolation exhibits relatively superior results over spline-based interpolation. This is as per expectation due to the reason that additional gridding for spline interpolation filters the signal part as well. This fact is evident from the results of spline interpolation of Grid-I and Grid-II with relatively better prediction results in Grid-I. This version of the model is capable of prediction having limiting error of 30 mGal. The predicted results show that 96.16% of prediction data falls within above-mentioned limit with Lagrange interpolation technique with least square adjustment for whole Pakistan area. The adverse effect of gridding is absent in case of Grid-I due to relatively flat areas and predicted data matches totally with control values for both spline as well as Lagrange interpolations. However, in case of Grid-II which includes high mountains of Himalaya, gridding effect is present and the accuracy of the predicted results falls to ～92%. The computed results have been compared with absolute values predicted using EGM96 and EGM2008 models as well. The gravity field recovered with PAKGM model is much better, i.e., ～ 96.16%, than both with EGM96 and EGM2008 which is about 85% only.     

Integrated Reservoir Characterization and Petrophysical Analysis of Cretaceous Sands in Lower Indus Basin,Pakistan

The reservoir character of the Cretaceous sand is evaluated in Lower Indus Basin, Pakistan where water flooding is very common. Thus, prediction of subsurface structure, lithology and reservoir characterization is fundamental for a successful oil or gas discovery. Seismic reflective response is an important tool to detect sub-surface structure. Seismic reflection response is not enough to highlight geological boundaries and fluids in the pore space therefore, the use of integrated approach is vital to map sub-surface heterogeneities with high level of confidence. Based on seismic character and continuity of prominent reflectors four seismic horizons are marked on the seismic sections. All the strata is highly disturbed and distorted with presence of a network of fault bounded horst and graben structures, which indicate that the area was under compressional tectonic regime. These fault bounded geological structure formed structural traps favorable for the accumulation of hydrocarbon. The petrophysical analysis reveals that the Cretaceous sand formation has four types of sand: Sand A, B, C and D with good porosity (15 % average) and low volume of shale. Although complete petroleum system is present with structural traps and reservoir character of sand interval is very good but these sands are highly saturated with water thus are water flooded, which is the main reason of the abundant wells in the study area.     

Diffusion of China’s coal-fired power generation technologies: historical evolution and development trends

Natural Hazards - With increasing environmental pressure and the promotion of structural reforms on the supply side, a trend of transformation and upgrading is inevitable in coal-fired power...     

OpenDA-NEMO framework for ocean data assimilation

Data assimilation methods provide a means to handle the modeling errors and uncertainties in sophisticated ocean models. In this study, we have created an OpenDA-NEMO framework unlocking the data assimilation tools available in OpenDA for use with NEMO models. This includes data assimilation methods, automatic parallelization, and a recently implemented automatic localization algorithm that removes spurious correlations in the model based on uncertainties in the computed Kalman gain matrix. We have set up a twin experiment where we assimilate sea surface height (SSH) satellite measurements. From the experiments, we can conclude that the OpenDA-NEMO framework performs as expected and that the automatic localization significantly improves the performance of the data assimilation algorithm by successfully removing spurious correlations. Based on these results, it looks promising to extend the framework with new kinds of observations and work on improving the computational speed of the automatic localization technique such that it becomes feasible to include large number of observations.     

Using geographical information systems to assess groundwater contamination from arsenic and related diseases based on survey data in Lahore,Pakistan

The present study was aimed at assessing the groundwater contamination from arsenic (As) and its impact on health from survey data in Lahore, Pakistan. OK (ordinary kriging) technique was used to create As and pH surfaces for samples from 380 groundwater wells at different locations and depths in the study area. Geographic information systems (GIS) was applied to delineate areas for safe, risk, and dangerous zones of As in drinking water from groundwater wells at 640 to 850 ft depths. To analyze effects of high As on public health, GIS-based field surveys were conducted to link health data along location of respondents to As contamination levels in the delineated safe, risk, and dangerous zones. Moreover, various pH levels and their effectiveness were studied to suggest cost-effective As treatment in the study area. Our results show that As contaminated strata varies with depth of groundwater wells, i.e., 44.50% areas comprising safe zone of drinking water from deep wells at 850 ft depth compared to 26% areas of shallow water at 640 ft depth. About 35% area with pH range (7 to 7.5) is marked in the risk and danger zones of As that can be initially targeted for treatment. Surveys confirm that people living in the risk and danger zones have some kind of As-related diseases.