An SVM-based machine learning method for the separation of alteration zones in Sungun porphyry copper deposit

Sungun porphyry copper deposit is in East Azarbaijan province, NW of Iran. There exist four hypogene alteration types in Sungun: potassic, propylitic, potassic–phyllic, and phyllic. Copper mineralization is essentially associated more with the potassic and less with the phyllic alterations and their separation is, therefore, quite important. This research has tried to separate these two alteration zones in Sungun porphyry copper deposit using the Support Vector Machine (SVM) method based on the fluid inclusion data, and seven variables including homogenization temperatures, salinity, pressure, depth, density and the Cu grade have been measured and calculated for each separate sample. To apply this method, use is made of the radial basis function (RBF) as the kernel function. The best values for λ and C (the most important SVM parameters) that perform well in the training and test data are 0.0001 and 1, respectively. If these values for λ and C are applied, the phyllic and potassic alteration zones in the training and test data will be separated with an accuracy of about 95% and 100%, respectively. This method can help geochemists in separating the alteration zones because classifying and separating samples microscopically is not only very hard, but also quite time and money consuming.     

Sorption of lead by chemically modified rice bran

In this work, the effectiveness of native and chemically modified rice bran to remove heavy metal Pb(II) ions from aqueous solution was examined. Chemical modifications with some simple and low-cost chemicals resulted in enhancement of the adsorption capacities and had faster kinetics than native rice bran. Experiments were conducted in shake flasks to monitor the upshot of parameters over a range of pH, initial Pb(II) concentrations and contact times using a batch model study. The sorption capacities q (mg g^?1) increased in the following order: NaOH (147.78), Ca(OH)₂ (139.08), Al(OH)₃ (127.24), esterification (124.28), NaHCO₃ (118.08), methylation (118.88), Na₂CO₃ (117.12) and native (80.24). The utmost uptake capacity q (mg g^?1) was shown by NaOH-pretreated rice bran. The results showed that, using NaOH-modified rice bran, the chief removal of Pb(II) was 74.54 % at pH 5, primary Pb(II) concentration 100 mg L^?1 and contact time 240 min. Equilibrium isotherms for the Pb(II) adsorption were analyzed by Langmuir and Freundlich isotherm models. The Langmuir isotherm model, showing Pb(II) sorption as accessible through the high value of the correlation coefficient (R ² = 0.993), showed a q _max value of 416.61 mg g^?1. The kinetic model illustrated adsorption rates well, depicted by a second order, which gives an indication concerning the rate-limiting step. Thermodynamic evaluation of the metal ion ?G ^o was carried out and led to the observation that the adsorption reaction is spontaneous and endothermic in nature. NaOH chemically modified rice bran was a superb biosorbent for exclusion of Pb(II) and proved to be excellent for industrial applications.     

Prediction of copper content in waste dump of Sarcheshmeh copper mine using visible and near-infrared reflectance spectroscopy

The pore structure characteristics of soil are closely related to soil engineering properties. For saline soil distributed in seasonally frozen areas, existing studies have focused on the influence of freeze–thaw cycles on pore structure, while the influence of soluble salt in the soil is not well understood. This study aims to explore the influence of salt content and salt type on the pore structure of freeze-thawed soil. Soil samples with different salt contents (0–2%) and types (bicarbonate salt and sulfate salt) were subjected to 10 freeze–thaw tests, and their pore size distributions (PSDs) were obtained by mercury intrusion porosimetry tests. In addition, the PSDs were quantitatively analyzed by fractal theory. For both salts, the PSDs of the tested soil samples were bimodal after the freeze–thaw cycles, and the porosity of saline soil samples increased with increasing salt content overall. However, the contents of various types of pores in soil samples with two salt types were quite different. The variation in bicarbonate salt content mainly affected the mesopore and macropore contents in the soil samples, and their change trends were opposite to each other. For soil samples with sulfate salt, the porosity and macropore content increased significantly when the salt content exceeded 1%. In addition, the pore structures in saline soil presented fractal characteristics after the freeze–thaw cycles, and the fractal dimension was positively correlated with macropore content. This study may provide references for understanding the engineering properties of saline soil in seasonally frozen areas at the microscale.     

Application of different clustering approaches to hydroclimatological catchment regionalization in mountainous regions,a case study in Utah State

With respect to the different hydrological responses of catchments, even the adjacent ones, in mountainous regions, there are a great number of motivations for classifying them into homogeneous clusters. These motivations include prediction in ungauged basins (PUB), model parameterization, understanding the potential impact of environmental changes, transferring information from gauged catchments to the ungauged ones. The present study investigated the similarity of catchments through the hydro-climatological pure time-series of a 14-year period from 2001 to 2015. Data sets encompass more than 13,000 month-station streamflow, rainfall, and temperature data obtained from 27 catchments in Utah State as one of the eight mountainous states of the USA. The identification, analysis, and interpretation of homogeneous catchments were investigated by applying the four approaches of clustering, K-means, Ward, and SOM (Self-Organized Map) and a newly proposed Wavelet-Entropy-based (WE-SOM) clustering method. By using two clustering evaluation criteria, 3, 5, and 6 clusters were determined as the best numbers of clusters, depending on the method employed, where each cluster represents different hydro-climatological behaviors. Despite the absence of geographic characteristics in input data matrix, the results indicated a regionalization in agreement with topographic characteristics. Considering the dependency of the hydrological behavior of catchments on the physiographic field aspects and characteristics, WE-SOM method demonstrated a more acceptable performance, compared to the other three conventional clustering methods, by providing more clusters. WE-SOM appears to be a promising approach in catchment clustering. It preserves the topological structure of data which can, as a result, be proofed in a greater number of clusters by dividing data into higher numbers of distinct clusters with similar altitudes of catchments in each cluster. The results showed the aptitude of wavelets to quantify the time-based variability of temperature, rainfall and streamflow, in the way contributing to the regionalization of diverse catchments.     

Comparative analysis of Lake Urmia and Lake Van water level time series

Recent decline in Lake Urmia water level makes it crucial to consider this issue more seriously. For this purpose, comparison of water level in Lake Urmia with Lake Van in Turkey, which is in relatively similar geographic and climate conditions, can be an effective approach. To follow this objective, trend analysis, regime shift, and coherency analyses are implemented. The results showed negative trend in Lake Urmia water level for the past 20 years, while in Lake Van, the trend is positive. Moreover, correlation of the lake level variations versus the basin rainfall during three common periods, identified by the regime shifts analysis, illustrated a decreasing trend in the correlation. These changes can be attributed to non-climatic factors such as different allocation disciplines in two lake’s catchments. Finally, the coherency analysis showed significant annual and inter-annual frequencies common between the two lake levels. Herein, the short-term period relations are associated with lags, while in long term, they act simultaneously.     

A Comparative Study of Pollutant Removal Stability in Hybrid Wetland Columns

This study investigated the effects of two alternative substrates(wood mulch and zeolite) on the performance of three laboratory-scale hybrid wetland systems that had identical system components and configurations.Each system consisted of a vertical flow(VF) wetland column,followed by a horizontal flow(HF) column and a vertical flow column.The substrates employed were wood mulch,gravel and zeolite,and Phragmites australis were planted in each column.The systems received synthetic wastewater,with pollutant loadings in the range of 8.5-38.0 g/(m2·d) total nitrogen(TN) and 4.0-46.4 g/(m2·d) biological oxygen demand(BOD5).Wood mulch and zeolite substrates showed higher efficiencies in terms of removing nitrogenous compounds and biodegradable organics.The supply of organic carbon from the organic mulch substrates enhanced denitrification,while adsorption of influent ammoniacal nitrogen(NH4-N) in zeolite played a major role in the removal of nitrogenous species in the wetland columns.Overall,the average percentage removals of TN and BOD5 reached >66% and >96% respectively,indicating stable performances by the hybrid wetland systems under the experimental loading ranges.Mathematical models were developed,based on the combination of Monod kinetics and continuously-stirred tank reactor(CSTR) flow patterns to describe the degradation of nitrogenous compounds.Predictions by the models closely matched the experimental data,indicating the validity and potential application of Monod kinetics in the modelling and design of treatment wetlands.     

Prediction of rainfall using artificial neural networks for synoptic station of Mashhad: a case study

In this paper, we have utilized ANN (artificial neural network) modeling for the prediction of monthly rainfall in Mashhad synoptic station which is located in Iran. To achieve this black-box model, we have used monthly rainfall data from 1953 to 2003 for this synoptic station. First, the Hurst rescaled range statistical (R/S) analysis is used to evaluate the predictability of the collected data. Then, to extract the rainfall dynamic of this station using ANN modeling, a three-layer feed-forward perceptron network with back propagation algorithm is utilized. Using this ANN structure as a black-box model, we have realized the complex dynamics of rainfall through the past information of the system. The approach employs the gradient decent algorithm to train the network. Trying different parameters, two structures, M₅₃₁ and M₇₄₁, have been selected which give the best estimation performance. The performance statistical analysis of the obtained models shows with the best tuning of the developed monthly prediction model the correlation coefficient (R), root mean square error (RMSE), and mean absolute error (MAE) are 0.93, 0.99, and 6.02 mm, respectively, which confirms the effectiveness of the developed models.     

Storage dam’s locality placing by MCDM techniques (case study: three dams in Iran)

MCDM (multi-criteria decision making) techniques are used to choose the best alternative among the relevant ones and rank the others. In this research, MCDM techniques were used to choose and rank the best places for constructing storage dams in Iran. To achieve this goal, the relevant information and data about dam construction situations were collected. Then, the recommended places for constructing storage dams were ranked by using MCDM techniques and according to the most suitable criteria which have been chosen based on experts’ opinions. To rank dam constructing project, three MCDM techniques, i.e., TOPSIS, AHP, and DEMATEL, were used. The results showed that the application of MCDM models by putting emphasis on economic, social, political, and technical criteria enables government and watershed managers to choose the best alternative(s) for constructing a storage dam.     

The interannual precipitation variability in the southern part of Iran as linked to large-scale climate modes

The interannual variation of precipitation in the southern part of Iran and its link with the large-scale climate modes are examined using monthly data from 183 meteorological stations during 1974–2005. The majority of precipitation occurs during the rainy season from October to May. The interannual variation in fall and early winter during the first part of the rainy season shows apparently a significant positive correlation with the Indian Ocean Dipole (IOD) and El Ni?o-Southern Oscillation (ENSO). However, a partial correlation analysis used to extract the respective influence of IOD and ENSO shows a significant positive correlation only with the IOD and not with ENSO. The southeasterly moisture flux anomaly over the Arabian Sea turns anti-cyclonically and transport more moisture to the southern part of Iran from the Arabian Sea, the Red Sea, and the Persian Gulf during the positive IOD. On the other hand, the moisture flux has northerly anomaly over Iran during the negative IOD, which results in reduced moisture supply from the south. During the latter part of the rainy season in late winter and spring, the interannual variation of precipitation is more strongly influenced by modes of variability over the Mediterranean Sea. The induced large-scale atmospheric circulation anomaly controls moisture supply from the Red Sea and the Persian Gulf.     

Intercontinental response to variations in the Arabia-Eurasia Plate convergence,calcite e-twin evidence of the Kuhbanan Fault system,Central Iran

Variations in the plate convergence direction have generally reflected on the kinematics of the major fault zones developed in the intercontinental parts of the collision zones. The Kuhbanan Fault system is one of the most important intercontinental faults in the Arabia-Eurasia collision zone with a dextral strike slip mechanism. This fault system is composed of three fault strands including Kuhbanan, Bazargan, and Kerman Faults. Here we used calcite e-twin analysis of the vein samples developed in these fault zones to reconstruct deformation condition and the paleodifferential stress direction and magnitude at the Kuhbanan Fault system. Our results represent 190°C-200°C of the deformation temperature and related 5–6 ± 1 km of deformation depth at the Kuhbanan Fault system. Calculated paleodifferential stress magnitude in the Kuhbanan Fault system using e-twin parameters ranges from 169-196 MPa similar to the inner parts of the orogenic systems. Comparing the data set of the Kuhbanan Fault system with previous studies at the Zagros orogen represents an increase of deformation depth and paleodifferential stress magnitudes from the foreland of the Zagros orogen to its hinterland and finally northward around the Kuhbanan Fault system in the central Iranian blocks. We have also proposed a shift of the stress direction from paleo NE to recent N directed by comparing paleostress direction deduced from the calcite e-twin and recent stress direction calculated from GPS and earthquake data analysis around the Kuhbanan Fault system. This kinematics change due to plate reorganization is in agreement with the observed regional variation in convergence direction all in the Arabia-Eurasia collision zone.