Environmental characterization of a karst polje: an example from Izeh polje,southwest Iran

Groundwater contamination is a well-known phenomenon, which occurs on local and regional scales in Izeh polje. The aims of this paper are investigation of the impact of human activities on the polje ecosystem, determination of the vulnerability of ground water, and to solve environmental problems. Nitrate contamination of groundwater in the Izeh polje was predicted using a solute transport model. The nitrate concentration in groundwater in most parts of Izeh polje is greater than maximum concentration permissible for drinking water, i.e., 45 mg/l. The main source of nitrate in the eastern underground areas of Izeh city is the domestic sewage. Bacterial pollution of shallow ground water in Izeh polje is severe and widespread. About 45% of ground water samples in May and September 2001 have positive MPN coliforms. Infiltration of polluted surface waters and decrease of water table depth, have lead to bacterial pollution of 80% of ground water samples in January 2002. The northeast, south and southwest areas of Izeh polje have higher pollution potential rather than its middle parts. The aquifer vulnerability indices in the middle, eastern, and northern parts of the polje are moderately lower as a result of decreased sediment size of the aquifer. The pollution in the polje depends on the amount and presence of pollutants. If they do exist, the possibility of pollution is considerable due to the coarseness of materials and shallow depth of groundwater table.     

Nouvelles données structurales et datations 40K–40Ar sur les roches métamorphiques de la région de Neyriz (zone de Sanandaj–Sirjan,Iran méridional). Leur intérêt dans le cadre du domaine néo-téthysien du Moyen-Orient

The metamorphic rocks of the Neyriz area (Sanandaj–Sirjan zone) represent a Palaeozoic sequence, the upper part of which being palaeontologically dated from the Carboniferous and the Permian. Field structural analysis of the whole sequence, detailed in laboratory by microstructural one and ⁴⁰K–⁴⁰Ar dating carried on separated minerals, lead to establish that the whole sequence, from gneisses to Permian rocks, has suffered a unique synmetamorphic deformation, of variable intensity, marked by a foliation. Isotopic ages measured on extracted amphiboles and micas, clustered in four groups between 300 and 60 Ma, show the successive stages of their slow exhumation, which ended by the end of the Cretaceous. To cite this article: R. Sheikholeslami et al., C. R. Geoscience 335 (2003).     

Strike-slip faulting, rotation, and along-strike elongation in the Kopeh Dagh mountains, NE Iran

The Kopeh Dagh is a linear mountain range separating the shortening in Iran from the stable, flat Turkmenistan platform. In its central part is an array of active right-lateral strike-slip faults that obliquely cut the range and produce offsets of several kilometres in the geomorphology and geological structure. They are responsible for major destructive earthquakes in the 19th and 20th centuries and represent an important seismic hazard for this now-populous region of NE Iran. These strike-slip faults all end in thrusts, revealed by the uplift and incision of Late Quaternary river terraces, and do not continue beyond the Atrak river valley, which forms the southern margin of the Kopeh Dagh. The cumulative offset on these strike-slip faults, and their associated rotation about vertical axes, can account for ∼60 km of N–S shortening. This value is similar to estimates of the Late Quaternary N–S right-lateral shear between central Iran and Afghanistan, which must be accommodated in NE Iran. The strike-slip faults also require ∼30 km of along-strike extension of the Kopeh Dagh, which is taken up by the westward component of motion between the South Caspian Basin and both Eurasia and Central Iran. It is probable that these motions occurred over the last ∼10 Ma.     

Non-parametric trend analysis of the aridity index for three large arid and semi-arid basins in Iran

Currently, an important scientific challenge that researchers are facing is to gain a better understanding of climate change at the regional scale, which can be especially challenging in an area with low and highly variable precipitation amounts such as Iran. Trend analysis of the medium-term change using ground station observations of meteorological variables can enhance our knowledge of the dominant processes in an area and contribute to the analysis of future climate projections. Generally, studies focus on the long-term variability of temperature and precipitation and to a lesser extent on other important parameters such as moisture indices. In this study the recent 50-year trends (1955–2005) of precipitation (P), potential evapotranspiration (PET), and aridity index (AI) in monthly time scale were studied over 14 synoptic stations in three large Iran basins using the Mann–Kendall non-parametric test. Additionally, an analysis of the monthly, seasonal and annual trend of each parameter was performed. Results showed no significant trends in the monthly time series. However, PET showed significant, mostly decreasing trends, for the seasonal values, which resulted in a significant negative trend in annual PET at five stations. Significant negative trends in seasonal P values were only found at a number of stations in spring and summer and no station showed significant negative trends in annual P. Due to the varied positive and negative trends in annual P and to a lesser extent PET, almost as many stations with negative as positive trends in annual AI were found, indicating that both drying and wetting trends occurred in Iran. Overall, the northern part of the study area showed an increasing trend in annual AI which meant that the region became wetter, while the south showed decreasing trends in AI.     

Prediction of drought in dry lands through feedforward artificial neural network abilities

Drought is one of the most important natural hazards in Iran. It is especially more prevalent in arid and hyper arid regions where there are serious limitations in regard to providing sufficient water resources. On the other hand, drought modeling and particularly its prediction can play important role in water resources management under conditions of lack of sufficient water resources. Therefore, in this study, drought prediction in a hyper arid location of Iran (Ardakan region) has been surveyed based on the abilities of artificial neural. Standardized Precipitation Index (SPI) in different time scales (3, 6, 9, 12, and 24 monthly time series) computed based on the data gathered from four rain gauge stations. After evaluation and testing of different artificial neural networks (ANN) structures, gradient descent back propagation (traingd) network showed higher abilities than others. Then, the predictions of SPI time series with different monthly lag times (1:12 months) were tested. Generally, drought prediction by ANNs in the Ardakan region has shown considerable results with the correlation coefficient (R) more than 0.79 and in the most cases and it rises more than 0.90, which indicates the ANN’s ability of drought prediction.     

Evaluating sampling locations in river water quality monitoring networks: application of dynamic factor analysis and discrete entropy theory

In this paper, a methodology is proposed for evaluating sampling locations in an existing river water quality monitoring network. The dynamic factor analysis is utilized to extract the independent dynamic factors from time series of water quality variables. Then, the entropy theory is applied to the independent dynamic factors to construct transinformation–distance (T–D) curves. The computation time in the case of using dynamic factors is significantly less than when the raw data is used because the number of independent dynamic factors is usually much less than the number of monitored water quality variables. In this paper, it is also shown that by clustering the study area to some homogenous zones and developing T–D curves for each zone, the accuracy of the results is significantly increased. To evaluate the applicability and efficiency of the proposed methodology, it is applied to the Karoon River which is the most important river system in Iran.     

Investigating the effects of lateral stress to vertical stress ratios and caverns shape on the cavern stability and sidewall displacements

Effects of lateral stress to vertical stress ratio on behavior of a cavern in various geomechanical and geometrical conditions were studied. Results indicated that the range of one to two lateral stress to vertical stress ratios was the best condition for cavern stability. The ranges causing tension and compressive failure were specified as well. Two-dimensional stability analyses were carried out by using Phase². Key point location on the cavern side wall was investigated and determined using an equation based on a large number of numerical analyses. Subsequently, in order to predict the elasto-plastic displacement and elastic displacement on a side wall key point, two equations were fitted based on various cavern cross sections considering four basic factors, i.e., rock deformation modulus, overburden depth of caverns, heights of the caverns, and the lateral stress to vertical stress ratio. The proposed equations were utilized to predict displacement at the key points of 10 projects subsequent to which the computation results were compared to in-site measuring results and back analysis results. Finally, using key point displacement as a stability factor, the effects of three different shapes of caverns including mushroom, horse shoe, and elliptical were investigated on cavern stability. The most optimum shape was elliptical in a vast range of lateral stress to vertical stress ratios; mushroom and horse shoe shapes were preferred in uniaxial stress fields concerning the rock quality.     

Quality assessment of groundwater at south Al Madinah Al Munawarah area, Saudi Arabia

Groundwater is the main source of irrigation within south Al Madinah Al Munawarah region. It is also an important source of drinking water in many areas including Madinah city. The wells installed in the aquifer of the study area (south Madinah city) are not currently regulated by the local authorities although they are a key component of water supply. The aquifers in the study area range from unconfined to semi-confined and confined. The main aim of this study is to assess the groundwater in the region for drinking and agricultural uses. For this purpose, hydrochemical analyses of major, minor and trace constituents and nutrients were performed on 29 groundwater samples from the aquifer located about 20 km south of Madinah. The recharge rate of the aquifer of the study area was estimated to be 6.58 % of the annual precipitation using the chloride mass-balance method. Chloride was positively correlated with major ions, which suggests that agricultural activities have some effect on groundwater chemistry through leaching of readily soluble salts from the soil zone. Groundwater of the study area is characterized by dominance of Na over Ca. Chloride was found to be the most dominant anion and replaced by HCO₃, thus reflecting geochemical evolution in the study area. The groundwater of the study area is not safe for drinking but can be safely used for salt-tolerant crops.     

Perogenesis of granites, Sharm El-Sheikh area, South Sinai, Egypt: petrological constrains and tectonic evolution

Precambrian granites of the Sharm El-Sheikh area in south Sinai, Egypt belong to collisional and post-collisional Magmatism (610–580 Ma). The granites are widely distributed in the northern part of the Neoproterozoic Arabian-Nubian Shield. South Sinai includes important components of successive multiple stages of upper crust granitic rocks. The earliest stages include monzogranite and syenogranites while the later stages produced alkali feldspar granites and riebeckite-bearing granites. Numerous felsic, mafic dikes and quartz veins traverse the study granites. Petrographically, the granitic rocks consist mainly of perthite, plagioclase, quartz, biotite and riebeckite. Analysis results portray monzogranites displaying calc-alkaline characteristics and emplaced in island-arc tectonic settings, whereas the syenogranites, alkali-feldspar granites and the riebeckite bearing-granites exhibit an alkaline nature and are enriched in HFSEs similar to granites within an extensional regime. Multi-element variation diagrams and geochemical characteristics reinforce a post-collision tectonic setting. REEs geochemical modeling reveals that the rocks were generated as a result of partial melting and fractionation of lower crust basaltic magma giving rise to A₁ and A₂ subtype granites. They were subsequently emplaced within an intraplate environment at the end of the Pan-African Orogeny.     

A simultaneous perturbation stochastic approximation algorithm for coupled well placement and control optimization under geologic uncertainty

Development of subsurface energy and environmental resources can be improved by tuning important decision variables such as well locations and operating rates to optimize a desired performance metric. Optimal well locations in a discretized reservoir model are typically identified by solving an integer programming problem while identification of optimal well settings (controls) is formulated as a continuous optimization problem. In general, however, the decision variables in field development optimization can include many design parameters such as the number, type, location, short-term and long-term operational settings (controls), and drilling schedule of the wells. In addition to the large number of decision variables, field optimization problems are further complicated by the existing technical and physical constraints as well as the uncertainty in describing heterogeneous properties of geologic formations. In this paper, we consider simultaneous optimization of well locations and dynamic rate allocations under geologic uncertainty using a variant of the simultaneous perturbation and stochastic approximation (SPSA). In addition, by taking advantage of the robustness of SPSA against errors in calculating the cost function, we develop an efficient field development optimization under geologic uncertainty, where an ensemble of models are used to describe important flow and transport reservoir properties (e.g., permeability and porosity). We use several numerical experiments, including a channel layer of the SPE10 model and the three-dimensional PUNQ-S3 reservoir, to illustrate the performance improvement that can be achieved by solving a combined well placement and control optimization using the SPSA algorithm under known and uncertain reservoir model assumptions.