Interpretation case study of the Sahl El Qaa area, southern Sinai Peninsula, Egypt

The study area is located in the Sinai Peninsula, which is considered one of the most promising regions for oil resources. Three different tectonic forces affect the area in the triple junction structures associated with the opening of the Gulf of Suez and the strike slip movement along the Gulf of Aqaba. The main goal of this work is to model the structure of the basement rocks in the study area using magnetic methods. To achieve this, a high-resolution land magnetic survey was acquired and the results were combined with existing seismic reflection data. The magnetic interpretation was carried out using the analytical signal, horizontal gradient, Euler and Werner deconvolution and 3D magnetic modelling methods. We concluded that most of the deduced structures are trending in N–S, N35°–N45° west and E–W directions. The Aqaba trend (N15°–N25° east) is barely noticeable. The depth to the basement rocks ranges from 1 km to more than 2 km below sea level and these results are in agreement with the available well log data. In addition, interpretation of seismic reflection sections was carried out and compared with overlapping magnetic profiles interpreted using Euler deconvolution. They show that the sedimentary section was affected by the basement tectonics, with faults extending from the basement upwards through the sedimentary cover. These faults constitute good potential structural traps for oil accumulation.     

Diagnostic study and modeling of the annual positive water temperature onset

A data-driven model is designed using artificial neural networks (ANN) to predict the average onset for the annual water temperature cycle of North-American streams. The data base is composed of daily water temperature time series recorded at 48 hydrometric stations in Québec (Canada) and northern US, as well as the geographic and physiographic variables extracted from the 48 associated drainage basins. The impact of individual and combined drainage area characteristics on the stream annual temperature cycle starting date is investigated by testing different combinations of input variables. The best model allows to predict the average temperature onset for a site, given its geographical coordinates and vegetation and lake coverage characteristics, with a root mean square error (RMSE) of 5.6 days. The best ANN model was compared favourably with parametric approaches.     

Impacts of Large-Scale Surface Modifications on Meteorological Conditions and Energy Use: A 10-Region Modeling Study

Summary  This paper summarizes results from a mesoscale modeling study to quantify the possible meteorological and energy-use impacts of large-scale increases in surface albedo and vegetative fraction. Ten regions in the U.S. were characterized and simulated in base- and modified-surface conditions. Time- and space-dependent meteorological variables were simulated for each region in four 3-day episodes to represent a range of seasonal variations. Using a simple interpolative procedure, a complete year of hourly weather data was created for each region (based on episodic meteorological simulation results) and input into energy-use models. The modified weather input was used to assess the effects of large-scale albedo and vegetative fraction changes on annual energy consumption in each of the ten areas targeted in this study. The simulations suggest annual electricity savings of between 1and 6.7 kWh m⁻² (of roof area) in residential neighborhoods and between 2 and 6.1 kWh m⁻² in office areas, depending on region. Annual gas penalties amount to up to 34.8 MJ m⁻² (of roof area) in residential neighborhoods and up to 21.1 MJ m⁻² in office areas. Received December 1, 1996 Revised May 11, 1998     

Numerical model of antecedent rainfall effect on slope stability at a hillslope of weathered granitic soil formation

Modeling rainwater infiltration in slopes is vital to the analysis of slope failure induced by heavy rainfall. Although the significance of rainwater infiltration in causing landslides is widely recognized, there have been different conclusions as to the relative roles of antecedent rainfall to slope failure. In this study, a numerical model was developed to estimate the effect of antecedent rainfall on an unsaturated slope, the formation of a saturated zone, and the change in slope stability under weak rainfall and rainstorm event. Results showed that under a rainstorm event, slope failure occurred at comparably similar time although the antecedent rainfall drainage periods prior to the major rainfall were different (i.e., 24-h, 48-h and 96-h). However, under weak rainfall condition, differences of the antecedent rainfall drainage periods have significant effect on development of pore-water pressure. A higher initial soil moisture conditions caused faster increase in pore water pressure and thus decreasing the safety factor of the slope eventually increasing likelihood of slope failure.     

Total least square method applied to rating curves

The ordinary least square method (OLS) has been the most frequently used least square method in hydrological data analysis. Its computational algorithm is simple, and the error analysis is also simple and clear. However, the primary assumption of the OLS method, which states that the dependent variable is the only error‐contaminated variable and all other variables are error free, is often violated in hydrological data analyses. Recently, a matrix algorithm using the singular value decomposition for the total least square (TLS) method has been developed and used in data analyses as errors‐in‐variables model where several variables could be contaminated with observational errors. In our study, the algorithm of the TLS is introduced in the evaluation of rating curves between the flow discharge and the water level. Then, the TLS algorithm is applied to real data set for rating curves. The evaluated TLS rating curves are compared with the OLS rating curves, and the result indicates that the TLS rating curve and the OLS rating curve are in good agreement. The TLS and OLS rating curves are discussed about their algorithms and error terms in the study. Copyright © 2013 John Wiley & Sons, Ltd.     

Climate changes associated with high-amplitude <Emphasis Type="Italic">Sq</Emphasis> geomagnetic variations

When the solar irradiance propagates between the outer magnetospheric regions and the ionosphere, dynamic processes of the magnetosphere-ionosphere-thermosphere system are affected at the lower end of their paths by the interaction of radiation with the neutral troposphere. The main target of this work is to investigate the relationship between the diurnal magnetic field variations resulting from solar activities and the variation in the troposphere temperature. Meteorological and geomagnetic data acquired from different observatories located in Egypt, Portugal and Slovakia in a long-term and daily-term scales were analyzed.     

Paving the Way for Social Learning When Governance Is Weak: Supporting Dialogue Between Stakeholders to Face a Groundwater Crisis in Morocco

Approaches to improve the governance of social–ecological systems are difficult to define in situations where governance is weak, that is, involving limited interactions between the actors and weak management of natural resources. This article analyzes an action research process implemented in the Chaouia coastal region of Morocco, where weak governance of the social–ecological system led to a groundwater and agricultural crisis. A dialogue between local actors was set up with the aim of identifying strategies to address the crisis. First separately and then together, farmers’ groups and staff members of public organizations analyzed the existing situation, scenarios for the future of the area, and strategies to cope with the crisis. Contrary to the expectations of the participants, farmers and staff members of public organizations had productive discussions. This approach clarified how social learning can be achieved and governance improved in this situation of weak governance.     

Numerical investigation on the performance of Wells turbine with non-uniform tip clearance for wave energy conversion

The performance of a Wells turbine with various non-uniform tip clearances was investigated using computational fluid dynamics (CFD). The investigation was performed on numerical models of a NACA0020 blade profile under steady flow conditions. The performance of turbines with uniform and non-uniform tip clearances was compared. The results were also compared with experimental results in literature. It was shown that the performance of turbine with non-uniform tip clearance is similar with that of turbine with uniform one in terms of torque coefficient, input power coefficient, and efficiency. However, the turbine with non-uniform tip clearance seems to have a preferable overall performance. An investigation on the flow-field around the turbine blade was performed in order to explain the phenomena.     

Shear behavior of sensitive marine clay–steel interfaces

Many soil–structure interaction problems require the knowledge of the shear resistance and behavior between the soil and construction materials. Although sensitive marine clay deposits are widely found in Canada (Leda clay) and many regions in the world (e.g., Scandinavia), and steel is a common construction material for many civil engineering structures, our understanding of the interface shear behavior between sensitive marine clay and steel is still limited. This paper presents the results of an experimental study on the interface shear behavior between Leda clay and steel. In this research, direct shear tests (DSTs) are conducted to investigate the interface shear strength parameters and behavior between Leda clay and steel, and the effect of several factors (e.g., steel surface roughness, properties of the Leda clay) on the interface shear behavior and parameters. All tests have been carried out with a standard DST apparatus at normal loads which range from 250 to 450 kPa. The results show that the Leda clay interface shear behavior can be significantly affected by the steel surface roughness, the Leda clay’s OCR, dry density, and salt content. The results presented in this paper will contribute to a more cost-effective design of geotechnical structures in Leda clay.     

Tenfold cross validation artificial neural network modeling of the settlement behavior of a stone column under a highway embankment

Construction of embankments in engineering structures on soft clay soils normally encounters problems related to excessive settlement issues. The conventional methods are inadequate to analyze and predict the surface settlement when the necessary parameters are difficult to determine in the field and in the laboratory. In this study, artificial neural network systems (ANNs) were used to predict settlement under embankment load using soft soil properties together with various geometric parameters as input for each stone column (SC) arrangement and embankment condition. Data from a highway project called Lebuhraya Pantai Timur2 in Terengganu, Malaysia, were investigated. The FEM package of Plaxis v8 program analysis was utilized. The actual angle of internal friction, spacing between SC, diameter of SC, length of SC, and height of embankment were used as the input parameters, and the settlement was used as the main output. Non cross validation (NCV) and tenfold cross validation (TFCV) were used to build the ANN model. The results of the TFCV model were more accurate than those of the NCV model. Comparisons made with the predictions of the Priebe model showed that the proposed TFCV model could provide better predictions than conventional methods.