Evaluation of floodplain variability considering impacts of climate change

In this study, an approach is presented for handling hydraulic uncertainties in the prediction of floodplain. Different factors affect river flood characteristics. Furthermore, the high changeability of flooding conditions leads to high variability of the inundation. River morphology is one of the most effective factors in river flood characteristics. This factor is influenced by sedimentation and erosion in the river cross sections, which affects the discharge variation. The depth and the width of the river cross section lead to an increase or decrease in the river flow path. This results in changes in the extent of the floodplain based on the generated rainfall. The inundated region boundaries are determined by utilizing the mean first‐order second‐moment analysis. The proposed method is applied to the Kajoo River in the south‐eastern part of Iran. Determination of floodplain uncertainty is a damage‐reduction policy in this region. Also, it is useful to prepare the necessary activities for overcoming the flood hazards. Climate change is the second effective factor on the floodplain uncertainties. Climate change affects the magnitude, extent and depth of inundation and it may intensify the flood problem. Therefore, the future rainfall pattern of the study area under climate change is simulated to evaluate its impacts on the river flow characteristic. Subsequently, a hydraulic routing model is used to determine floodplain. Finally, the copula function is used to estimate the joint probability of the changes in the inundation area due to changes in river morphology and the rainfall changes due to impacts of climate change. Results show that the uncertainties of the extent of floodplain are affected by climate change and river morphology, leading to noticeable changes in the magnitude and frequency of floods. Evaluating these impacts and estimating corresponding river discharges will help in the study of river dynamics, and will also contribute towards devising effective mitigation and management strategies. Copyright © 2010 John Wiley & Sons, Ltd.     

Dye Removal,Energy Consumption and Operating Cost of Electrocoagulation of Textile Wastewater as a Clean Process

In this research, the efficiency of electrocoagulation treatment process using aluminum electrodes to treat synthetic wastewater containing Reactive Red198 (RR198) was studied. The effects of parameters such as voltage, time of reaction, electrode connection mode, initial dye concentration, electrolyte concentration, and inter electrode distance on dye removal efficiency were investigated. In addition, electrical energy consumption, electrode consumption, and operating cost at optimum condition have been investigated. The results showed that dye and chemical oxygen demand removals were 98.6 and 84%, respectively. Electrode consumption, energy consumption and operating cost were 0.052 kg/m³, 1.303 kWh/m³ and 0.256 US$/m³, respectively. Dye removal kinetic followed first order kinetics. It can be concluded that electrocoagulation process by aluminum electrode is very efficient and clean process for reactive dye removal from colored wastewater.     

Cluster and R-mode factor analyses on soil geochemical data of Masjed-Daghi exploration area, northwestern Iran

Masjed-Daghi is located in Julfa sheet (1:100,000 series) in the northwest of Iran. The area consists of a very likely gold mineralization bearing epithermal mineralization which appears to be associated with a porphyry Cu–Mo system at deeper levels. Ninety-three soil samples were collected and analyzed for 13 elements (Au, Mo, Cu, Pb, Sn, Ag, Zn, Cr, Mn, Ba, Be, Ni, Co) by using emission spectrometry and atomic absorption spectrophotometry. The data were processed and interpreted using univariate and multivariate statistical analyses. The distribution of the majority of variables is slightly to moderately positively skewed which can be interpreted by log-normal model. Only Ni, Be, and Mn show normal distribution. Based on cluster analysis, the variables can be classified into two main groups. The first group consists of the main ore forming elements such as Au, Ag, and Ba which belong to epithermal system and Mo, Sn, and Cu which have more affiliation to porphyry mineralization. The principal component analysis extracted three factors. These factors calculated using varimax rotated R-mode factor loading matrix account for more than 65 % of the total variance. The first factor represents the main constituents of the epithermal system (Au, Ag, Ba) and its geochemical halo at the northeast of the study area. The second factor represents the main constituents of the porphyry system (Cu, Mo, Sn) and its geochemical halo in the western part of the study area which is overlapped with the volcanic rocks affected by local intrusions with higher alteration overprint. The third factor, however with less significance, represents Pb and Zn which are not the main ore constituents but can be considered as pathfinder elements. The results have been used to locate hidden orebodies using presented factor score mapping.     

Seismic potential of the North Qazvin zone,Alborz

The North Qazvin region is a part of the Central Alborz Mountains in Iran and has experienced destructive earthquakes. This region is a popular and industrial zone near Tehran, capital of Iran. To identify the highest and lowest seismic hazard location and consequently the seismic zonation of this region, different parameters, such as topography, geology, tectonics and seismicity, have been focused. Accordingly, the north of Qazvin region can be divided into three subzones: western, eastern and southern. Seismic activity of the western zone is higher than the other ones and seismic potential of the eastern zone is higher than the other two zones. This zoning is also necessary for all seismic active areas to find the most dangerous zone.     

NMR Parameters Determination through ACE Committee Machine with Genetic Implanted Fuzzy Logic and Genetic Implanted Neural Network

Free fluid porosity and rock permeability, undoubtedly the most critical parameters of hydrocarbon reservoir, could be obtained by processing of nuclear magnetic resonance (NMR) log. Despite conventional well logs (CWLs), NMR logging is very expensive and time-consuming. Therefore, idea of synthesizing NMR log from CWLs would be of a great appeal among reservoir engineers. For this purpose, three optimization strategies are followed. Firstly, artificial neural network (ANN) is optimized by virtue of hybrid genetic algorithm-pattern search (GA-PS) technique, then fuzzy logic (FL) is optimized by means of GA-PS, and eventually an alternative condition expectation (ACE) model is constructed using the concept of committee machine to combine outputs of optimized and non-optimized FL and ANN models. Results indicated that optimization of traditional ANN and FL model using GA-PS technique significantly enhances their performances. Furthermore, the ACE committee of aforementioned models produces more accurate and reliable results compared with a singular model performing alone.     

Using airborne geophysical data in identifying tectonic lineaments in east of Iran

In this paper we tried to identify the main tectonic lineaments in Eastern Iran including Lut block and Sistan suture zone from the airborne geomagnetic data together with tilt filter. As the map of obtained lineaments from airborne geomagnetic data has been studied, four distinct set of lineaments has been identified: (i) north–south, (ii) east–west, (iii) northeast–southwest, and (iv) northwest–southwest that are concurrently with structural zones and area’s big faults. New faults which have been identified in this investigation are lineaments with trend northeast–southwest and east–west. The depth of these lineaments has been calculated through Euler modeling. Magnetic lineaments trending east–west have the most depth, so these lineaments are related to basement faults.     

A Geographic Information System‐based site selection experience for the construction of a geomagnetic observatory in Kerman Province,Iran

In recent years, the necessity of constructing new geomagnetic observatories in Iran has been discussed from various aspects. Improper site selection of such important data centres can significantly affect the quality of their recorded data. In this research, site selection studies were performed to find the most favourable location to construct a geomagnetic observatory in Kerman Province, southeast of Iran. Having defined 11 site selection criteria for geomagnetic observatories, all the data layers were prepared for the whole province. After detection of seven promising regions using analytical hierarchy process and fuzzy logic method in geographical information system, Technique for Order of Preference by Similarity to Ideal Solution was used for ranking of the suitable areas. The most favourable region was finally detected southwest of Kerman Province, located between the cities of Baft and Sirjan. Detailed land surveys can be focused in this region to decide on the optimum area for the construction of the geomagnetic observatory.     

Iteratively re‐weighted and refined least squares algorithm for robust inversion of geophysical data

A robust metric of data misfit such as the ?₁‐norm is required for geophysical parameter estimation when the data are contaminated by erratic noise. Recently, the iteratively re‐weighted and refined least‐squares algorithm was introduced for efficient solution of geophysical inverse problems in the presence of additive Gaussian noise in the data. We extend the algorithm in two practically important directions to make it applicable to data with non‐Gaussian noise and to make its regularisation parameter tuning more efficient and automatic. The regularisation parameter in iteratively reweighted and refined least‐squares algorithm varies with iteration, allowing the efficient solution of constrained problems. A technique is proposed based on the secant method for root finding to concentrate on finding a solution that satisfies the constraint, either fitting to a target misfit (if a bound on the noise is available) or having a target size (if a bound on the solution is available). This technique leads to an automatic update of the regularisation parameter at each and every iteration. We further propose a simple and efficient scheme that tunes the regularisation parameter without requiring target bounds. This is of great importance for the field data inversion where there is no information about the size of the noise and the solution. Numerical examples from non‐stationary seismic deconvolution and velocity‐stack inversion show that the proposed algorithm is efficient, stable, and robust and outperforms the conventional and state‐of‐the‐art methods.     

Mélange development in the Neyriz region of Zagros Orogen,Iran: Record of convergence and collision in the Neotethyan Realm

Mélanges are formed by sedimentary, tectonic and diapiric processes and are generally found in collisional belts. The Zagros Orogeny provides an intriguing geological laboratory for the study of mélange-forming processes during the progressive tectonic evolution of the Neotethys Ocean. Different types of tectonic and sedimentary mélanges occur in specific structural positions within the Zagros orogenic belt in the Neyriz Region (Iran). Based on their block-in-matrix fabrics, and tectonostratigraphic positions, we differentiated 14 different mélange types, which mark different episodes of the tectonic evolution of the Neyriz Region from the Cretaceous subduction to the Miocene collision. The Cretaceous subduction stage is recorded by volcanic-sedimentary mélanges (Mv). Sedimentary mélanges characterized by megabreccia from the Cretaceous limestone (Ms1) and Eocene polymictic megabreccia (Ms2) represent epi-nappe mélanges formed during the Palaeocene–Eocene in wedge-top basins. The ophiolite emplacement in the Oligocene resulted in local extensional tectonics in the upper part of the ophiolitic nappe, and deposition of a polymictic megabreccia (Ms3, Ms4). As the final production of the Neotethys Ocean closure and the Eurasian-Arabian collision, the sedimentary mélanges characterized by different types of chaotic rock units (Ms5, Ms6, Ms7 and Ms8 facies) were developed in front of the Cretaceous–Eocene nappes due to growth of the orogenic wedge in the Miocene. Our findings indicate that the recognition and distinction of different types of mélange may provide additional constraints for a better understanding of the tectono-sedimentary evolution of the Neotethyan region.     

The increase of rainfall erosivity and initial soil erosion processes due to rainfall acidification

The drastic growth of population in highly industrialized urban areas, as well as fossil fuel use, is increasing levels of airborne pollutants and enhancing acid rain. In rapidly developing countries such as Iran, the occurrence of acid rain has also increased. Acid rain is a driving factor of erosion due to the destructive effects on biota and aggregate stability; however, little is known about its impact on specific rates of erosion at the pedon scale. Thus, the present study aimed to investigate the effect of acid rain at pH levels of 5.25, 4.25, and 3.75 for rainfall intensities of 40, 60, and 80 mm h^?1 on initial soil erosion processes under dry and saturated soil conditions using rainfall simulations. The results were compared using a two‐way ANOVA and Duncan tests and showed that initial soil erosion rates with acidic rain and non‐acidic rain under dry soil conditions were significantly different. The highest levels of soil particle loss due to splash effects in all rainfall intensities were observed with the most acidic rain (pH = 3.75), reaching maximum values of 16 g m^?2 min^?1. The lowest levels of particle losses were observed in the control plot where non‐acidic rain was used, with values ranging from 3.8 to 8.1 g m^?2 min^?1. Similarly, under saturated soil conditions, the lowest level of soil particle loss was observed in the control plot, and the highest peaks of soil loss were observed for the most acidic rains (pH = 3.75 and pH = 4.25), reaching maximum average values of 40 g m^?2 min^?1. However, for saturated soils with acidic water but with non‐acidic rain, the highest soil particle loss was observed for the control plot for all the rainfall intensities. In conclusion, acidic rain has a negative impact on soils, which can be more intense with a concomitant increase in rainfall intensity. Rapid solutions, therefore, need to be found to reduce the emission of pollutants into the air, otherwise, rainfall erosivity may drastically increase.