A synthetic approach integrating surface and subsurface data for prospecting deep aquifers: the Southeast Tunisia

The Southeast Tunisia has remarkable thermal springs that have been used for bathing since many years. Currently, studies are being carried out to investigate the possible use of the hot water for heating buildings and for greenhouses. Springs with discharge temperatures between 26.8 and 58°C exist in the area. The flow rates range between 7 and 66 l/s with total dissolved solids (TDS) varying between 2,020 and 4,030 mg/l. Both geological–hydrogeological setting and the similarity in chemical characteristics between the Zarat spring and nearby water wells suggest that the hot water from this spring may be related to the Senonian aquifer. However, the hydrogeothermal approach shows that the depth of the reservoir that supplies the Zarat spring is greater than that of the Senonian aquifer. In fact, geothermometry approach indicates that fluids emerging from the Lower Cretaceous sandstones reach temperatures of approximately 78°C at depth, while the fluid temperature from the nearby water wells is 32°C. Through the integration of various types of data we found that the thermal water of Southeast Tunisia is of meteoric origin. This water infiltrates deeply into the Lower Cretaceous sandstones and reaches a high temperature before rising upwards to supply the hot springs and well discharge zones. It appears that the upward movement of hot water from the deep aquifers to shallow ones is probably due to the abundant fractures in the area.     

Harold Edwin Hurst: the Nile and Egypt,past and future

ABSTRACT

H.E. Hurst spent some 60 years studying the Nile for the Egyptian government, and laid the foundation for a monumental set of hydrological records and investigations. His studies of the size of over-year reservoirs needed to maintain a given yield from Nile flows showed that this was greater than that based on random series. This finding, known as the Hurst phenomenon, was confirmed by other natural series and led to important advances in practical and theoretical statistics. His work led to the design of the Aswan High Dam and to continued research in Egypt.

Editor D. Koutsoyiannis; Guest editor E. Eris     

A supervised committee machine artificial intelligent for improving DRASTIC method to assess groundwater contamination risk: a case study from Tabriz plain aquifer,Iran

Vulnerability maps are designed to show areas of greatest potential for groundwater contamination on the basis of hydrogeological conditions and human impacts. The objective of this research is (1) to assess the groundwater vulnerability using DRASTIC method and (2) to improve the DRASTIC method for evaluation of groundwater contamination risk using AI methods, such as ANN, SFL, MFL, NF and SCMAI approaches. This optimization method is illustrated using a case study. For this purpose, DRASTIC model is developed using seven parameters. For validating the contamination risk assessment, a total of 243 groundwater samples were collected from different aquifer types of the study area to analyze \( {\text{NO}}_{ 3}^{ - } \) concentration. To develop AI and CMAI models, 243 data points are divided in two sets; training and validation based on cross validation approach. The calculated vulnerability indices from the DRASTIC method are corrected by the \( {\text{NO}}_{3}^{ - } \) data used in the training step. The input data of the AI models include seven parameters of DRASTIC method. However, the output is the corrected vulnerability index using \( {\text{NO}}_{3}^{ - } \) concentration data from the study area, which is called groundwater contamination risk. In other words, there is some target value (known output) which is estimated by some formula from DRASTIC vulnerability and \( {\text{NO}}_{3}^{ - } \) concentration values. After model training, the AI models are verified by the second \( {\text{NO}}_{3}^{ - } \) concentration dataset. The results revealed that NF and SFL produced acceptable performance while ANN and MFL had poor prediction. A supervised committee machine artificial intelligent (SCMAI), which combines the results of individual AI models using a supervised artificial neural network, was developed for better prediction of vulnerability. The performance of SCMAI was also compared to those of the simple averaging and weighted averaging committee machine intelligent (CMI) methods. As a result, the SCMAI model produced reliable estimates of groundwater contamination risk.     

Vibration screening by trench barriers,a review

This paper provides a review of various investigations concerned with vibration isolation using trench barriers and factors affecting their performance, also extracts design recommendations, because there is no exact conclusion of researches in this field. Vibrations induced by different sources can be seriously harmful to structures and occupants. Geometrical parameters, soil characteristics, and filling material properties can affect a barrier’s performance. Investigators have applied analytical approach, finite element, boundary element, experimental, and field studies to identify relevant factors. Various geometrical parameters affecting trench’s isolation level were examined, among which depth of trench was found to be the most important, but in most cases, the width of the trench and source-barrier distance have a low effect. Shear-wave velocity ratio of filling material and surrounding soil has the most significant role of all material properties. Using high-energy-absorbing materials can lead to better isolation. The majority of studies consider soil and filling material’s behavior to be elastic, so changes in loading amplitude have no effect on vibration reduction. Finally, among special cases in vibration isolation by trenches, non-rectangular and multiple ones found to be economically satisfying and well-isolating barriers.     

Effect of silica fume on compressive strength of oil-polluted concrete in different marine environments

In the present research, effect of silica fume as an additive and oil polluted sands as aggregates on compressive strength of concrete were investigated experimentally. The amount of oil in the designed mixtures was assumed to be constant and equal to 2% of the sand weight. Silica fume accounting for 10%, 15% and 20% of the weight is added to the designed mixture. After preparation and curing, concrete specimens were placed into the three different conditions: fresh, brackish and saltwater environments (submerged in fresh water, alternation of exposed in air & submerged in sea water and submerged in sea water). The result of compressive strength tests shows that the compressive strength of the specimens consisting of silica fume increases significantly in comparison with the control specimens in all three environments. The compressive strength of the concrete with 15% silica fume content was about 30% to 50% higher than that of control specimens in all tested environments under the condition of using polluted aggregates in the designed mixture.     

Expansion of cavities in layered elastic system

Theoretical formulations to the problem of expansion of spherical and cylindrical cavities in a layered elastic system are presented. The medium surrounding the cavity is assumed to consist of several layers, and each is idealized as a linear elastic solid. The solutions are expressed in matrix forms and can be obtained using a programmable calculator. The developed solutions are of some importance in geomechanics. The spherical cavity solution can be used to compute the settlement of single axially loaded piles. The predicted settlement using the analysis outlined herein agrees reasonably well with one case of field measurements. The cylindrical cavity solution can be used to manifest the effect of disturbed mass at the cavity wall on the stress–strain and deformation characteristics of the intact mass.     

Prospection géoélectrique pour l'étude de l'aquifère thermal des calcaires récifaux, Hmeïma–Boujabeur (Centre ouest de la Tunisie)

The Hmeïma–Boujabeur zone is considered as an important geothermal province for Tunisia. The reef limestone, characterized by intense fracturation and important karstification, confers them the property to be a regional thermal aquifer. A geophysical study based on two complementary geoelectrical methods, the Electrical Sounding (ES) and Magneto-Telluric Sounding (MTS), turned out to be very efficient to provide a complete electrical image of the underground until about 1-km depth. The synthetic approach integrating all data allowed us to delimit the favourable area for thermal water exploitation. To cite this article: M. Gouasmia et al., C. R. Geoscience 338 (2006).     

The Bajocian–Bathonian plant fossil from the Hojedk formation,Lenjan section,Kerman, Iran

The Jurassic successions represent a wide distribution in North of the Kerman province. These successions include Ab-Haji, Badamu, and Hojedk formations. The Hojedk Formation contains the plant fossils. The Lenjan section is one of the suitable areas for paleontological studies on the Hojedk Formation. The study section is mostly composed of green sandstone and shale with several interbedded coal veins with different thicknesses. The thickness of the Hojedk Formation is about 200 m in the Lenjan section. In this study, seven genera and 13 species of macro plant fossils were identified and described, including Nilssonia undulata, Nilssonia bozorga, Nilssonia berriesi, Nilssonia sp., Klukia cf. exilis, Klukia exilis, Cladophlebis antarctica, Coniopteris lobata, Coniopteris murrayana, Elatocladus confertus, Podozamites sp., Equisetites sp., and Coniopteris sp. The Bajocian–Bathonian can be attributed to the Lenjan section based on the recognized flora.