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1.
Slab breakoff: a model for Caledonian, Late Granite syn-collisional magmatism in the orthotectonic (metamorphic) zone of Scotland and Donegal, Ireland 总被引：12，自引：0，他引：12
None of the existing models for calc-alkaline “Late Granite” (Siluro–Devonian) genesis in the metamorphic Caledonian orogenic belt of Ireland and Scotland fully explains their spatial, age or chemical character. A consistent model must involve the closure of Iapetus Ocean, where slab breakoff is a natural consequence of attempted subduction of continental crust. Expected outcome is a long linear belt of high-K, calc-alkaline magmas, some with characteristic trace element signatures, specifically high Ba, Sr and Zr. Other features include the critical magmatic association of coeval appinite and granite, rapid uplift, erosion and the low-grade regional metamorphism in the Southern Uplands. The linear heat pulse on breakoff is spatially, intensity and time limited producing small volume melts emplaced as separated plutons, over a short time span. Magmatism in the Caledonian metamorphic belt is accurately accounted for by slab breakoff on collision of Baltica with the Scoto–Greenland margin during the Scandian orogeny, following Iapetus Ocean closure. The two chemically, isotopically and areally distinctive suites in the metamorphic belt in Scotland, viz. the Argyll and Cairngorm Suites, can be modelled by reference to the Donegal granites where sequential partial melting of new, lamprophyric underplated crust, then shallower old crust, as heat conduction moved up through the crust on slab breakoff, produced magmas characteristic of the two suites. 相似文献
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Integrated geoelectrical resistivity and hydrogeochemical methods for delineating and mapping heavy metal zone in aquifer system 总被引：1，自引：0，他引：1
Nur Islami Samsudin Hj Taib Ismail Yusoff Azman Abdul Ghani 《Environmental Earth Sciences》2018,77(10):383
A novel study on using geoelectrical resistivity, soil property, and hydrogeochemical analysis methods for delineating and mapping of heavy metal in aquifer system is presented in this paper. A total of 47 surveys of geoelectrical resistivity with Wenner configuration were conducted to determine the subsurface and the groundwater characteristics. The groundwater sample from 53 existing wells and 2 new wells has been analyzed to derive their water chemical content. The chemical analysis was done on the soil sample obtained from new two wells and from selected locations. The water and soil chemical analysis results from the new two wells were used as calibration in resistivity interpretation. The occurrence of heavy metal in aquifer system was expected to detect using the geoelectrical resistivity survey for the whole study area. The result of groundwater analysis shows that the groundwater sample contains a relatively low concentration of Fe (<?0.3 mg/L) elongating from the south up to the middle region. While in the middle and the northwestern, Fe concentration is relatively high (around 12 mg/L). Chemical analysis of soil sample shows that in the lower resistivity zone (<?18 Ωm), Al and Fe concentrations are comparatively high with an average of 68,000 and 40,000 mg/kg, respectively. Starting from the middle to the northwestern zone, the resistivity value appears to be low. It is definitely caused by higher Al and Fe concentration within the soil, and it is supported also by lower total anion content in the groundwater. While the resistivity value of more than 40 Ωm in aquifers is obtained in the zone which Fe concentration is relatively lower in the soil but not present in the groundwater. Correlation Fe concentration in the soil and Fe concentration in the groundwater sample shows the trend of positively linear; however, the Al concentration in soil has no correlation with Al content in groundwater. Finally, the probability of high heavy metal zone in the aquifer system is easily delineated by the distribution of geoelectrical resistivity presented in depth slice shapes which extend from the Boundary Range Composite Batholith in the north to the northwest. 相似文献
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E. A. Rahim Bahaa-eldin I. Yusoff S. Abdul Rahim W. Y. Wan Zuhairi M. R. Abdul Ghani 《Environmental Earth Sciences》2011,63(5):1043-1055
This paper aims at determining of inorganic leachate contamination for a capped unsanitary landfill in the absence of hydrogeological data. The 2D geoelectrical resistivity imaging, soil physicochemical characterization, and surface water analysis were used to determine contamination load and extent of selective heavy metal contamination underneath the landfill. The positions of the contaminated subsoil and groundwater were successfully delineated in terms of low resistivity leachate plumes of <10 Ωm. Leachate migration towards the reach of Kelang River could be clearly identified from the resistivity results and elevated concentrations of Fe in the river downslope toe of the site. Concentration of Fe, Mn, Ca, Na, K, Mg, Cu, Cr, Co, Ni, Zn, and Pb was measured for the subsoil samples collected at the downslope (BKD), upslope (BKU), and the soil-waste interface (BKI), of the landfill. The concentration levels obtained for most of the analyzed heavy metals significantly exceed the normal range in typical municipal solid waste landfill sites. The measured heavy metal contamination load in the subsoil is in the following order Fe ? Mn > Zn > Pb > Cr > Cu. Taking into consideration poor physical and chemical characteristics of the local soil, these metals first seem to be attenuated naturally at near surface then remobilize unavoidably due to the soil acidic environment (pH 4.2-6.18) which in turn, may allow an easy washing of these metals in contact with the shallow groundwater table during the periodic fluctuation of the Kelang River. These heavy metals are believed to have originated from hazardous industrial waste that might have been illegally dumped at the site. 相似文献
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H. Md. Azamathulla Yong Chong Cuan Aminuddin Ab. Ghani Chun Kiat Chang 《Arabian Journal of Geosciences》2013,6(9):3469-3480
This study presents gene expression programming (GEP), an extension of genetic programming, as an alternative approach to modeling the suspended sediment load relationship for the three Malaysian rivers. In this study, adaptive neuro-fuzzy inference system (ANFIS), regression model, and GEP approaches were developed to predict suspended load in three Malaysian rivers: Muda River, Langat River, and Kurau River [ANFIS (R 2?=?0.93, root mean square error (RMSE)?=?3.19, and average error (AE)?=?1.12) and regression model (R 2?=?0.63, RMSE?=?13.96, and AE?=?12.69)]. Additionally, the explicit formulations of the developed GEP models are presented (R 2?=?0.88, RMSE?=?5.19, and AE?=?6.5). The performance of the GEP model was found to be acceptable compare to ANFIS and better than the conventional models. 相似文献
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The use of data‐driven modelling techniques to deliver improved suspended sediment rating curves has received considerable interest in recent years. Studies indicate an increased level of performance over traditional approaches when such techniques are adopted. However, closer scrutiny reveals that, unlike their traditional counterparts, data‐driven solutions commonly include lagged sediment data as model inputs, and this seriously limits their operational application. In this paper, we argue the need for a greater degree of operational reasoning underpinning data‐driven rating curve solutions and demonstrate how incorrect conclusions about the performance of a data‐driven modelling technique can be reached when the model solution is based upon operationally invalid input combinations. We exemplify the problem through the re‐analysis and augmentation of a recent and typical published study, which uses gene expression programming to model the rating curve. We compare and contrast the previously published solutions, whose inputs negate their operational application, with a range of newly developed and directly comparable traditional and data‐driven solutions, which do have operational value. Results clearly demonstrate that the performance benefits of the published gene expression programming solutions are dependent on the inclusion of operationally limiting, lagged data inputs. Indeed, when operationally inapplicable input combinations are discounted from the models and the analysis is repeated, gene expression programming fails to perform as well as many simpler, more standard multiple linear regression, piecewise linear regression and neural network counterparts. The potential for overstatement of the benefits of the data‐driven paradigm in rating curve studies is thus highlighted. Copyright © 2011 John Wiley & Sons, Ltd. 相似文献
6.
Mohamed Yacine Tebbouche Djamel Machane Souhila Chabane El-Hadi Oubaiche Aghiles Abdelghani Meziani Dalila Ait Benamar Hakim Moulouel Ghani Cheikh Lounis Rabah Bensalem Abderrahmane Bendaoud 《Arabian Journal of Geosciences》2018,11(7):154
The original version of this paper was published with incomplete affiliation. Given in this article are the complete affiliations. 相似文献
7.
Brahim Meziani Djamel Machane Abderrahmane Bendaoud Ghani Cheikh Lounis El-Hadi Oubaiche Souhila Chabane Rabah Bensalem Hakim Moulouel 《Arabian Journal of Geosciences》2017,10(5):117
The Ain Turck (Bouira) landslide, in north-center Algeria, is one of the numerous instabilities recorded along the Lakhdaria-Bouira section of the 1200-km-long east-west Algerian highway. The locality of Ain Turck is known for its unstable slopes characterized by a very rough morphology with steep slopes (20 to 25%). This slide threatens the inhabitants of the Ibournanen village, located down the unstable slope, where parts of some houses have fallen into ruin, while others are cracked. It is characterized by an active movement extending over a more or less important slope, of the order of a hundred meters. The land mobilized by this movement corresponds to the layer of shale clays and clays overlaid by a backfill, placed there following the east-west highway works. Geological, geomorphologic, and geotechnical analysis allows determining the soil instability probably related to earthworks during the construction of the highway section a few years earlier, followed by a particularly rainy season in 2012. Acquisitions of ambient seismic noise and H/V ratio processing, as well as the acquisition of an electrical resistivity profile at the instability site, have reinforced our preliminary interpretations of depth and geometry of the sliding surface. 相似文献
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Hazi Md. Azamathulla Aminuddin Ab. Ghani Chun Kiat Chang Zorkeflee Abu Hasan Nor Azazi Zakaria 《洁净——土壤、空气、水》2010,38(10):969-976
In this study, a novel machine learning technique called the support vector machine (SVM) method is proposed as a new predictive model to predict sediment loads in three Malaysian rivers. The SVM is employed without any restriction to an extensive database compiled from measurements in the Muda, Langat, and Kurau rivers. The SVM technique demonstrated a superior performance compared to other traditional sediment‐load methods. The coefficient of determination, 0.958, and the mean square error, 0.0698, of the SVM method are higher than those of the traditional method. The performance of the SVM method demonstrates its predictive capability and the possibility of the generalization of the model to nonlinear problems for river engineering applications. 相似文献