Frequency analysis of climate extreme events in Zanjan, Iran

In this study, generalized extreme value distribution (GEV) and generalized Pareto distribution (GPD) were fitted to the maximum and minimum temperature, maximum wind speed, and maximum precipitation series of Zanjan. Maximum (minimum) daily and absolute annual observations of Zanjan station from 1961 to 2011 were used. The parameters of the distributions were estimated using the maximum likelihood estimation method. Quantiles corresponding to 2, 5, 10, 25, 50, and 100 years return periods were calculated. It was found that both candidate distributions fitted to extreme events series, were statistically reasonable. Most of the observations from 1961 to 2011 were found to fall within 1–10 years return period. Low extremal index (θ) values were found for excess maximum and minimum temperatures over a high threshold, indicating the occurrence of consecutively high peaks. For the purpose of filtering the dependent observations to obtain a set of approximately independent threshold excesses, a declustering method was performed, which separated the excesses into clusters, then the de-clustered peaks were fitted to the GPD. In both models, values of the shape parameters of extreme precipitation and extreme wind speed were close to zero. The shape parameter was less negative in the GPD than the GEV. This leads to significantly lower return period estimates for high extremes with the GPD model.     

Estimating the Shapes of Gravity Sources through Optimized Support Vector Classifier (SVC)

In gravity interpretation methods, an initial guess for the approximate shape of the gravity source is necessary. In this paper, the support vector classifier (SVC) is applied for this duty by using gravity data. It is shown that using SVC leads us to estimate the approximate shapes of gravity sources more objectively. The procedure of selecting correct features is called feature selection (FS).In this research, the proper features are selected using inter/intra class distance algorithm and also FS is optimized by increasing and decreasing the number of dimensions of features space. Then, by using the proper features, SVC is used to estimate approximate shapes of sources from the six possible shapes, including: sphere, horizontal cylinder, vertical cylinder, rectangular prism, syncline, and anticline. SVC is trained using 300 synthetic gravity profiles and tested by 60 other synthetic and some real gravity profiles (related to a well and two ore bodies), and shapes of their sources estimated properly.     

Time independent seismic hazard analysis in Alborz and surrounding area

The Bayesian probability estimation seems to have efficiencies that make it suitable for calculating different parameters of seismicity. Generally this method is able to combine prior information on seismicity while at the same time including statistical uncertainty associated with the estimation of the parameters used to quantify seismicity, in addition to the probabilistic uncertainties associated with the inherent randomness of earthquake occurrence. In this article a time-independent Bayesian approach, which yields the probability that a certain cut-off magnitude will be exceeded at certain time intervals is examined for the region of Alborz, Iran, in order to consider the following consequences for the city of Tehran. This area is located within the Alpine-Himalayan active mountain belt. Many active faults affect the Alborz, most of which are parallel to the range and accommodate the present day oblique convergence across it. Tehran, the capital of Iran, with millions of inhabitants is located near the foothills of the southern Central Alborz. This region has been affected several times by historical and recent earthquakes that confirm the importance of seismic hazard assessment through it. As the first step in this study an updated earthquake catalog is compiled for the Alborz. Then, by assuming a Poisson distribution for the number of earthquakes which occur at a certain time interval, the probabilistic earthquake occurrence is computed by the Bayesian approach. The highest probabilities are found for zone AA and the lowest probabilities for zones KD and CA, meanwhile the overall probability is high.     

Support vector machines and feed-forward neural networks for spatial modeling of groundwater qualitative parameters

The present study attempts to model the spatial variability of three groundwater qualitative parameters in Guilan Province, northern Iran, using artificial neural networks (ANNs) and support vector machines (SVMs). Data collected from 140 observation wells for the years 2002–2014 were used. Five variables, X and Y coordinates of the observation well, distance of the observation well from the shoreline, areal average 6-month rainfall depth, and groundwater level at the day of water quality sampling, were considered as primary input variables. In addition, nine qualitative variables were also considered as auxiliary input variables. Electrical conductivity (EC), sodium concentration (Na⁺), and sulfate concentration (SO₄ ^2?) of the groundwater in the region were estimated using ANNs and SVMs with different input combinations. The results showed that both ANNs and SVMs work well when the only primary input variable is the well location. The ANN yielded an RMSE of 1.03 mEq/l for SO₄ ^2?, 1.05 mEq/l for Na⁺, and 203.17 μS/cm for EC, using the X and Y coordinates of the observation wells in the study area. In the case of SVM, these values were, respectively, 0.87, 0.87, and 176.68. Considering the auxiliary input variables (pH, EC, and the concentrations of Na⁺, K⁺, Ca²⁺, Mg²⁺, Cl^?, SO₄ ^2?, and HCO₃ ^?) resulted in a significant decrease in the RMSE of both ANNs (0.22, 0.30, and 33.04) and SVMs (0.26, 0.34, and 36.23). Comparing these RMSE values with those of cokriging interpolation technique (0.59, 0.98, and 177.59) indicated that ANNs and SVMs produced more accurate estimates of the three qualitative parameters. The relative importance of auxiliary input variables was also determined using Gamma test. The output uncertainty of ANNs and SVMs were determined using p-factor and d-factor. The results showed that SVMs have less uncertainty than ANNs.     

Quantitative and qualitative simulation of groundwater by mathematical models in Rafsanjan aquifer using MODFLOW and MT3DMS

Agriculture sector by using 80% of freshwater is the greatest water consumer in Iran. Excessive use of agricultural fertilizers in last decade, caused accumulation of enormous amounts of salts and subsequence declined the physical properties of soil. In desert and dry regions such as Rafsanjan plain, use of the groundwater resources is more than the surface water resources. Therefore, information about the quality of these resources remains a necessary task for optimum management, protection of water resources, and stopping the future damages. In this study, the groundwater quantity and quality of Rafsanjan plain was investigated by MODFLOW and MT3DMS. The presented quantitative model for this aquifer was compared by observed data and calibrated. This model was used to predict a 10-year period. Results show that water elevation decreases approximately 15 m for 10 years to come in this plain. Qualitative model results show that most quality parameters will increase. Electrical conductivity will increase more than other parameters. As values of this parameter will reach 16,000 µs/l for next 5 years. Therefore, we suggest that exploitation of water from these resources should be reduced and discharge from some of agricultural wells stop; also we suggested that recharge to groundwater resources should be increased and agricultural activities should be limited or improved using of modern irrigation systems in this plain.     

Hydraulic Conductivity of Fly Ash-Amended Mine Tailings

The objective of this study was to evaluate the effect of fly ash addition on hydraulic conductivity (k) of mine tailings. Mine tailings used in this study were categorized as synthetic tailings and natural tailings; two synthetic tailings were developed via blending commercially-available soils and natural tailings were collected from a garnet mine located in the U.S. Two fly ashes were used that had sufficient calcium oxide (CaO) content (17 and 18.9 %) to generate pozzolanic activity. Hydraulic conductivity was measured on pure tailings and fly ash-amended tailings in flexible-wall permeameters. Fly ash was added to mine tailings to constitute 10 % dry mass of the mixture, and specimens were cured for 7 and 28 days. The influence of fly ash-amendment on k of mine tailings was attributed to (1) molding water content and (2) plasticity of the mine tailings. Tailings that classified as low-plasticity silts with clay contents less than 15 % exhibited a decrease in k when amended with fly ash and prepared wet of optimum water content (w _opt ). Tailings that classified as low-plasticity clay exhibited a one-order magnitude increase in k with addition of fly ash for materials prepared dry or near w _opt . The decrease in k for silty tailings was attributed to formation of cementitious bonds that obstructed flow paths, whereas the increase in k for clayey tailings was attributed to agglomeration of clay particles and an overall increase in average pore size. The results also indicated that the effect of curing time on k is more pronounced during the early stages of curing (≤7 days), as there was negligible difference between k for 7 and 28-days cured specimens.     

The Arabian Plate: unique fit of the earth's surface jig saw puzzle

The Arabian Plate is important and unique in many ways. The worker wants to highlight the important features characterizing the Arabian Plate. It is a unique fit of the earth's surface jig saw puzzle, different than all other lithospheric plates. It has the three known main tectonic plate boundaries, divergent, convergent and conservative ones. These boundaries are the Red Sea and Gulf of Aden, Zagros-Taurus and Dead Sea, respectively. It has three main well-defined and sharp plate boundaries, and it is surrounded by three major plates, African, Eurasian and Indian plates. The Red Sea and Gulf of Aden form the divergent boundary and spreading center. The Dead Sea Transform Fault (the Gulf of Aqaba Transform Fault) represents the conservative boundary and transform fault system. The Zagros-Taurus Thrust (Zagros-Taurus-Bitlis Thrust and Fold Belt) represents the convergent boundary and collision zone. The Arabian Plate incorporates a wide range and variety and subvariety of all three rock types, igneous, metamorphic and sedimentary rocks, this in addition to all kinds of structures. Among these are folding with major fold belts, faulting, foliation, lineation and diapirism. Transform, transcurrent, normal, graben, reverse, thrust faults are all represented one way or another. The tectonics of the Arabian shield, which forms a major part of the Arabian Plate, has long tectonic history prior to the formation of the Red Sea. After the opening and formation of the latter, the tectonics of the Arabian shield became affected and controlled by its tectonics. The Arabian Plate includes the Arabian Platform which has a relatively different setting of tectonics represented by the Central Arabian Graben. The Arabian Plate contains one of the best representative outcropped ophiolite sequences in the world. The Arabian Plate most importantly incorporates most of world oil reserve. Seismic and volcanic activities are also manifested and affected many areas in the Arabian Plate.     

Microbiostratigraphy of Kazhdumi Formation in the Northwestern Shiraz (Southwest Iran) on the Basis of Foraminifera and Calcareous Algae

The middle Cretaceous Kazhdumi Formation,with a thickness of 222 m,belongs to the Bangestan Group and occurs in the Zagros folded zone in southwest Iran.The lower boundary with the Dariyan Formation is disconformable,which is recognized by iron oxides and glauconite.The recognized microfossils are Valvulammina sp.,Scandonea sp.,Daxia cenomana,Choffatela sp., Pseudolituonella reicheli and calcareous algae-Lithocodium aggregation(which belongs to the Sarvak Formation),representing the beginning of Cenomani...