Structure de socle,sismostratigraphie et héritage structural au cours du rifting au niveau de la marge d'Ifni/Tan-Tan (Maroc sud-occidental)

Seismic reflection profiles from the Ifni/Tan-Tan Atlantic margin of southern Morocco, interpreted in the light of well data and field geology from the Western Anti-Atlas, allowed us to establish the seismostratigraphic framework of the syn-rift series and to reveal (i) a compressional structural style in the pre-Triassic basement similar to that established in the adjacent outcropping onshore basement but with an opposed western vergence, (ii) the importance of inherited anterior structures in the formation of Triassic-Liassic rift structures and (iii) an east–west propagation of these rift structures. To cite this article: N. AbouAli et al., C. R. Geoscience 337 (2005).     

Interactive discovery of sequential patterns in time series of wind data

Wind speed and direction vary over space and time due to the interactions between different pressures and temperature gradients within the atmospheric layers. Near the earth’s surface, these interactions are modulated by topography and artificial structures. Hence, characterizing wind behaviour over large areas and long periods is a complex but essential task for various energy-related applications. In this study, we present a novel approach to discover wind patterns by integrating sequential pattern mining and interactive visualization techniques. The approach relies on the use of the Linear time Closed pattern Miner sequence algorithm in conjunction with a time sliding window that allows the discovery of all sequential patterns present in the data. These patterns are then visualized using integrated 2D and 3D coordinated multiple views and visually explored to gain insight into the characteristics of the wind from a spatial, temporal and attribute (type of wind pattern) point of view. This proposed approach is used to analyse 10 years of hourly wind speed and direction data for 29 weather stations in the Netherlands. The results show that there are 15 main sequential patterns in the data. The spatial task shows that weather stations located in the same region do not necessarily experience similar wind pattern. For within the selected time interval, similar wind patterns can be observed in different stations and in the same station at different times of occurrence. The attribute task discovered that the repetitive occurrences of chosen pattern indicate as regular wind behaviour at different weather stations that persisted continuously over time. The results of these tasks show that the proposed interactive discovery facilitates the understanding of wind dynamics in space and time.     

Using inverse modeling and hierarchical cluster analysis for hydrochemical characterization of springs and Talkhab River in Tang-Bijar oilfield,Iran

Hierarchical cluster analysis (HCA) and inverse modeling (PH REdox EQuilibrium (in C language) (PHREEQC)) were simultaneously useful approaches in interpreting surface water hydrochemistry within Talkhab River in the Tang-Bijar oilfield, Iran, where large uncertainties exist in the understanding of the water quality system. Q-mode HCA applied to the data revealed three major surface water associations distinguished on the basis of the major causes of variation in the hydrochemistry. The three water groups were classified as upstream waters (group 1: Ca–SO₄), intermediate waters (group 2: Ca–SO₄–Cl), and downstream waters (group 3: Na–Cl). Geochemical reaction models were constructed using PHREEQC to establish the reactions associated with the different mineral phases through inverse modeling. The hydrochemical compositions of the water groups and the mass balance calculations indicate that the dominant processes and reactions responsible for the hydrochemical evolution in the system are (1) dissolution of evaporites, (2) precipitation of carbonate minerals, (3) silicate weathering reactions, (4) limited mixing with saline water, and (5) ion exchange.     

Estimation of air-overpressure produced by blasting operation through a neuro-genetic technique

Blasting operations usually produce significant environmental problems which may cause severe damage to the nearby areas. Air-overpressure (AOp) is one of the most important environmental impacts of blasting operations which needs to be predicted and subsequently controlled to minimize the potential risk of damage. In order to solve AOp problem in Hulu Langat granite quarry site, Malaysia, three non-linear methods namely empirical, artificial neural network (ANN) and a hybrid model of genetic algorithm (GA)–ANN were developed in this study. To do this, 76 blasting operations were investigated and relevant blasting parameters were measured in the site. The most influential parameters on AOp namely maximum charge per delay and the distance from the blast-face were considered as model inputs or predictors. Using the five randomly selected datasets and considering the modeling procedure of each method, 15 models were constructed for all predictive techniques. Several performance indices including coefficient of determination (R ²), root mean square error and variance account for were utilized to check the performance capacity of the predictive methods. Considering these performance indices and using simple ranking method, the best models for AOp prediction were selected. It was found that the GA–ANN technique can provide higher performance capacity in predicting AOp compared to other predictive methods. This is due to the fact that the GA–ANN model can optimize the weights and biases of the network connection for training by ANN. In this study, GA–ANN is introduced as superior model for solving AOp problem in Hulu Langat site.     

Regional modelling of rainfall-induced runoff using hydrological model by incorporating plant cover effects: case study in Kelantan,Malaysia

The objective of this paper is to develop a spatial temporal runoff modelling of local rainfall patterns effect on the plant cover hilly lands in Kelantan River Basin. Rainfall interception loss based on leaf area index, loss/infiltration on the ground surface, and runoff calculation were considered as the main plant cover effects on the runoff volume. In this regard, a hydrological and geotechnical grid-based regional model (integrated model) was performed using Microsoft Excel^® and GIS framework system for deterministic modelling of rainfall-induced runoff by incorporating plant cover effects. The infiltration process of the current model was integrated with the precipitation distribution method and rainfall interception approach while the runoff analysis of integrated model was employed based on loss/infiltration water on the ground surface with consideration of water interception loss by canopy and the remaining surface water. In the following, the spatial temporal analysis of rainfall-induced runoff was performed using 10 days of hourly rainfall events at the end of December 2014 in Kelantan River Basin. The corresponding changes in pressure head and consequent rate of infiltration were calculated during rainfall events. Subsequently, flood volume is computed using local rainfall patterns, along with water interception loss and the remaining surface water in the study area. The results showed the land cover changes caused significant differences in hydrological response to surface water. The increase in runoff volume of the Kelantan River Basin is as a function of deforestation and urbanization, especially converting the forest area to agricultural land (i.e. rubber and mixed agriculture).     

Transmission electron microscopic study of antiphase domains in CaAl2Ge2O8-Feldspar

Transmission electron microscopic study of synthetic CaAl₂Ge₂O₈-feldspar revealed two types of antiphase domains: type “b”-antiphase domains with the displacement vector 1/2 [110] and type “c”-antiphase domains with the displacement vector 1/2 [111]. The “b”-domains were on the order of 0.1 μm in size, while the “c”-domains displayed wall to wall distances mostly between 0.1 and 1 μm. The formation of the two types of antiphase domains is due to reductions in translational symmetry associated with the phase transitions \(C\bar 1 \to I\bar 1 \to P\bar 1\) . The antiphase domain textures of CaAl₂Ge₂O₈-feldspar are very similar to the textures found in natural and synthetic anorthite, CaAl₂Si₂O₈.     

Analytical correlation of a dynamic brace buckling experiment

A dynamic response analysis procedure for an x-braced tubular steel offshore platform frame is described, including details of the mathematical model adopted to represent the dynamic buckling behaviour of the brace member. Results obtained with this mathematical technique are compared with experimental data measured during shaking table tests of a 5/48 scale model frame. The agreement between experiment and analysis is excellent for different levels of response, ranging from linearly elastic to cyclic brace buckling.     

Self-organised clustering for road extraction in classified imagery

The extraction of road networks from digital imagery is a fundamental image analysis operation. Common problems encountered in automated road extraction include high sensitivity to typical scene clutter in high-resolution imagery, and inefficiency to meaningfully exploit multispectral imagery (MSI). With a ground sample distance (GSD) of less than 2 m per pixel, roads can be broadly described as elongated regions. We propose an approach of elongated region-based analysis for 2D road extraction from high-resolution imagery, which is suitable for MSI, and is insensitive to conventional edge definition. A self-organising road map (SORM) algorithm is presented, inspired from a specialised variation of Kohonen's self-organising map (SOM) neural network algorithm. A spectrally classified high-resolution image is assumed to be the input for our analysis. Our approach proceeds by performing spatial cluster analysis as a mid-level processing technique. This allows us to improve tolerance to road clutter in high-resolution images, and to minimise the effect on road extraction of common classification errors. This approach is designed in consideration of the emerging trend towards high-resolution multispectral sensors. Preliminary results demonstrate robust road extraction ability due to the non-local approach, when presented with noisy input.     

Regression‐based approach to low flow prediction in the Maryland Piedmont region under joint climate and land use change

We examine the low flow records for six urbanized watersheds in the Maryland Piedmont region and develop regression equations to predict annual minimum low flow events. The effects of both future climate (based on precipitation and temperature projections from two climate models: Hadley and the Canadian Climate Centre (CCC)) and land use change are incorporated to illustrate possible future trends in low flows. A regression modelling approach is pursued to predict the minimum annual 7‐day low flow estimates for the proposed future scenarios. A regional regression model was calibrated with between 10 and 50 years of daily precipitation, daily average temperature, annual imperviousness, and the daily observed flow time‐series across six watersheds. Future simulations based on a 55 km² urbanizing watershed just north of Washington, DC, were performed. When land use and climate change were employed singly, the former predicted no trends in low flows and the latter predicted significant increasing trends under Hadley and no trends under CCC. When employed jointly, however, low flows were predicted to decrease significantly under CCC, whereas Hadley predicted no significant trends in low flows. Antecedent precipitation was the most influential predictor on low flows, followed by urbanization. Copyright © 2006 John Wiley & Sons, Ltd.     

Disaggregation of daily rainfall data using Bartlett Lewis Rectangular Pulse model: a case study in central Peninsular Malaysia

Short duration rainfall data are required for certain hydrological risk assessments. However, short timescale rainfall intensity records are still scarce due to the high cost and low reliability of the monitoring systems. One way to solve this problem is by disaggregating rainfall data using stochastic methods. This study used the Bartlett Lewis Rectangular Pulse model to disaggregate daily rainfall into hourly rainfall for ten stations in the central region of Peninsular Malaysia. The performance of the model was evaluated on its ability to reproduce statistical properties, namely the mean and standard deviation, derived from the historical records over the disaggregated rainfall. The disaggregation of daily to hourly rainfall produced daily and hourly means that closely matched the historical records. However, the standard deviations of the disaggregated daily rainfall were lower than the historical values. Despite the significant differences in the standard deviation, both data series exhibit similar patterns and the model adequately preserved the trends of all the statistical properties used in evaluating its performance.