Hydrogeological aspects of groundwater drainage of the urban areas in Kuwait City

Residential areas in Kuwait City have witnessed a dramatic rise in subsurface water tables over the last three decades. This water rise phenomenon is attributed mainly to over irrigation practices of private gardens along with leakage from domestic and sewage networks. This paper presents a comprehensive study for urban drainage in two selected areas representing the two hydrogeological settings encountered in Kuwait City. In the first area, a vertical drainage scheme was applied successfully over an area of 1 km². The system has been under continuous operation and monitoring for more than 4 years without problems, providing a permanent solution for the water rise problem in this area. The hydrogeological system has approached steady state conditions and the water levels have dropped to about 3·5 m below the ground surface. In the second area a dual drainage scheme, composing of horizontal and vertical elements, is proposed. Horizontal elements are suggested in the areas where the deep groundwater contains hazardous gases that may pose environmental problems. The proposed drainage scheme in the second area has not yet been implemented. Field tests were conducted to assess the aquifer parameters in both areas and a numerical model has been developed to predict the long‐term response of the hydrogeological system in the two areas under consideration. Copyright © 2001 John Wiley & Sons, Ltd.     

New insights into the origin of perylene in geological samples

The origin of the polycyclic aromatic hydrocarbon (PAH) perylene in sediments and petroleum has been a matter of continued debate. Reported to occur in Phanerozoic organic matter (OM), fossil crinoids and tropical termite mounds, its mechanism of formation remains unclear. While a combustion source can be excluded, structural similarities to perylene quinone-like components present in e.g. fungi, plants, crinoids and insects, potentially suggest a product-precursor relationship. Here, we report perylene concentrations, ¹³C/¹²C, and D/H ratios from a Holocene sediment profile from the Qingpu trench, Yangtze Delta region, China. Perylene concentrations differ from those of pyrogenic PAHs, and rise to prominence in a stratigraphic interval that was dominated by woody vegetation as determined by palynology including fungal spores. In this zone, perylene concentrations exhibit an inverse relationship to the lignin marker guaiacol, D/H ratios between −284‰ and −317‰, similar to the methoxy groups in lignin, as well as co-variation with spores from wood-degrading fungi. ¹³C/¹²C of perylene differs from that of land plant wax alkanes and falls in the fractionation range expected for saprophytic fungi that utilise lignin, which is isotopically lighter than cellulose and whole wood. During progressive lignin degradation, the relative carbon isotopic ratio of the perylene decreases. We therefore hypothesise a relationship of perylene to the activity of wood-degrading fungi. To support our hypothesis, we analysed a wide range of Phanerozoic sediments and oils, and found perylene to generally be present in subordinate amounts before the evolutionary rise of vascular plants, and to be generally absent from marine-sourced oils, few exceptions being attributed perhaps to a contribution of marine and/or terrestrial-derived fungi, anoxia (especially under marine conditions) and/or contamination of core material by fungi. A series of low-molecular-weight aromatic quinones bearing the perylene-backbone were detected in Devonian and Cretaceous sediments, potentially representing precursor components to perylene.     

Seismic sources for southern Pakistan and seismic hazard assessment of Karachi

Natural Hazards - Karachi is Pakistan’s largest city with population exceeding 18 million and is amongst the top five most congested cities in the world. Karachi has experienced no earthquake...     

Household vulnerability and resilience in flood hazards from disaster-prone areas of Punjab,Pakistan

Natural Hazards - An environmental variation has caused Pakistan an alarming portrait of vulnerability in flood disasters. The government has focused on a number of realistic actions, heartening...     

辽东半岛复州湾剖面寒武系第二统光合作用生物膜建造的核形石

作为一种经常大于鲕粒的包覆颗粒类型,核形石以其不平滑的圈层被解释为微生物成因,区别于成因存在较大争议的鲕粒,而且常与鲕粒和其他类型的碳酸盐颗粒相互共生;作为一种在围绕着生物碎屑和非生物碎屑核心的序列式纹层化作用过程中形成的球形或假球型生物沉积构造,核形石还常常单独产出和分布,所以又被解释为微生物碳酸盐岩,或者被归为球状叠层石。在辽东半岛寒武系第二统碱厂组和馒头组之中,厘米级别大小的核形石密集发育在三级层序的顶部,成为一种时间特化的相。另外,以下重要特征将辽东半岛寒武系第二统的核形石特征化,包括:(1)与凝块和微凝块共生;(2)多为球状和椭球状;(3)由不均一的非纹层状致密泥晶和微亮晶构成;(4)核形石皮层以及核形石间凝块中发育特别的蓝细菌鞘钙化化石等。尽管穿越成岩作用过滤器去解释古代核形石复杂的形成机理存在着巨大的挑战,也尽管形成这些核形石的复杂生物膜钙化作用细节需要更加深入地研究才能得到更好地了解,但是,辽东半岛第二统碱厂组和馒头组核形石中直接的微生物化石证据,尤其是核形石内较为丰富的钙化蓝细菌鞘化石,使其成为一个了解光合作用生物膜建造核形石的典型实例。     

Genetic Structure and Diversity of the Moon Jellyfish Aurelia coerulea Polyp Population in Jaran Bay,Korea, Revealed by Mitochondrial COI and 16S rRNA Genes

Ocean Science Journal - Blooms of the moon jellyfish (Aurelia coerulea) have been responsible for huge economic losses and environmental disruptions in oceans around the world. The mass occurrence...     

Imaging of Stratigraphic Pinch-Out Traps Within the Lower-Cretaceous Shaly-Sandstone System,Pakistan, Using 3D Quantitative Seismic Inverted Porosity–Velocity Modeling

Incised valleys form excellent stratigraphic pinch-out traps. Traditional seismic data analysis techniques fail to predict quantitatively the porous and low-velocity sand-fills for incised valleys. The 3D quantitative seismic inverted porosity–velocity (3DQSIPV) analysis was applied in the Indus Basin, SW Pakistan. The reflection strength attribute better portrayed the reservoir sandstone and faults compared to seismic amplitude attribute. The sweetness-based continuous wavelet transform authenticated the development of the stratigraphic play. The 17 Hz amplitude delineated the non-porous seal and porous reservoirs of sand-filled incised valley and strand plain, and faults. The integrated model of seismic attributes categorizes the reservoir and seal constituents. The petrophysical modeling corroborated the gas-bearing “sweet-spots” within the stratigraphic-based dynamical system. The facies modeling predicted the for coarse-grained sandstone and fine-grained shales, depositional environments, fluctuations of sea level and their impacts on the overall development of stratigraphic plays. The predicted density and P-wave velocity for the sandstone-filled incised valley of the lowstand system tract were?~?1.4–1.75 g/cc and?~?3217–3802 m/s, respectively. The predicted density and P-wave velocity for the sealing shales facies of strand plain of transgressive system tract were?~?1.9–2.1 g/cc and 2.55–2.7 g/cc and 3900–4700 m/s, respectively. The 3DQSIPV predicted?>?25% porosity and?~?3300 m/s velocity of reservoirs in the west. The eastern zones shows?<?12% porosity and high velocity of?~?4580 m/s. Cross-plots of porosity, velocity, and thickness showed correlation coefficients of R²?>?0.90 for inverted velocity. This workflow may serve as an analogue for the remaining oil and gas fields of the Indus Basins of Pakistan and similar geological settings of divergent plate margins.

     

Context inference and prediction modeling in ubiquitous health GIS

The ever‐increasing population in cities intensifies environmental pollution that increases the number of asthmatic patients. Other factors that may influence the prevalence of asthma are atmospheric parameters, physiographic elements and personal characteristics. These parameters can be incorporated into a model to monitor and predict the health conditions of asthmatic patients in various contexts. Such a model is the base for any asthma early warning system. This article introduces a novel ubiquitous health system to monitor asthmatic patients. Ubiquitous systems can be effective in monitoring asthmatic patients through the use of intelligent frameworks. They can provide powerful reasoning and prediction engines for analyzing various situations. Our proposed model encapsulates several tools for preprocessing, reasoning and prediction of asthma conditions. In the preprocessing phase, outliers in the atmospheric datasets were detected and missing sensor data were estimated using a Kalman filter, while in the reasoning phase, the required information was inferred from the raw data using some rule‐based inference techniques. The asthmatic conditions of patients were predicted accurately by a Graph‐Based Support Vector Machine in a Context Space (GBSVMCS) which functions anywhere, anytime and with any status. GBSVMCS is an improved version of the common Support Vector Machine algorithm with the addition of unlabeled data and graph‐based rules in a context space. Based on the stored value for a patient's condition and his/her location/time, asthmatic patients can be monitored and appropriate alerts will be given. Our proposed model was assessed in Region 3 of Tehran, Iran for monitoring three different types of asthma: allergic, occupational and seasonal asthma. The input data to our system included air pollution data, the patients’ personal information, patients’ locations, weather data and geographical information for 270 different situations. Our results showed that 90% of the system's predictions were correct. The proposed model also improved the estimation accuracy by 15% in comparison to conventional methods.