جستجوی مقالات مرتبط با کلیدواژه "ضریب همبستگی" در نشریات گروه "زمین شناسی"

The occurrence of droughts in the past few decades, rising global temperatures, and the exponential growth of population around the world, highlights the need for the quantitative and qualitative study of water resources. On the other hand, the construction of some structures, such as dams, increases the importance of studying the water quality at the construction site of such structures. In this study, using hydrogeochemical methods, the quality of groundwater in the construction site of Shahid Dam (located in the south of Semirom city) was evaluated. For this purpose, the correlation between the parameters was determined, the groundwater type was investigated using diagrams of Piper, Durov, and Stiff, geochemical ion ratios, ionic processes, and ion exchange reverse. The abundance of the main elements in the groundwater of the region includes TDS> HCo3> Ca> So4> Cl> Mg> Na> K. The chemical parameters of water in all cases in terms of drinking are favorable. The results show that there is a direct relationship with a high correlation (0.97) between EC and TDS, while a weak correlation was observed between other parameters. In general, it can be said that the relationship between HCo3 and EC, TDS, and other parameters has a higher correlation. The predominant type of groundwater in the study area is calcium bicarbonate and most of the samples have freshwater facies. According to the diagram (Na / Cl) vs. (EC), reverse ion exchange occurred in 11 samples, and only one sample had a dual origin of clay sediments and saline water intrusion. Based on the Ca + Mg versus HCo3 + So4 diagram, all samples show normal ion exchange.

Precipitation is a favorable phenomenon for human due to the water resources for agriculture, drinking water and health purposes. Because of the importance of precipitation, understanding the mechanism of this phenomenon in synoptic, dynamics and climatology has always been of interest for researchers. Although heavy rainfall is useful for water supply, it has destructive effects, such as floods. Heavy rains show the mechanism of precipitation more clearly because the pressure generating systems are more clearly detectable.    In this study, mean sea level pressure pattern of severe precipitation in southwestern Iran over a period of 30 years was identified and classified. Moreover, the area and time of research were defined, and using the Climate Prediction Center (CPC) precipitation data, the 30-years extreme precipitation with 99th percentiles was determined. There were 64 cases of extreme precipitation from 1989 to 2018 with 99th percentiles.  Classification of extreme precipitation systems based on mean sea level pressure field was performed with a spatial resolution of 2.5° data from the NCEP-NCAR center. Extreme precipitation in southwestern Iran at warm time of year was classified using factor analysis technique. In this study, it was shown that the pressure systems that cause extreme precipitation in southwestern Iran during the warm season are classified into five main patterns: (A) The first dominant pattern is created by the Red Sea trough and the low-pressure center of Saudi Arabia. It should be noted that in this pattern, the role of the Red Sea trough is more prominent than the low-pressure Saudi Arabia. In some cases, Saudi Arabia has formed along the Red Sea trough, reflecting the influence of the Red Sea on creation and development of the Saudi Arabian low-pressure center. (B) The second dominant pattern is formed by the-low pressure of Saudi Arabia and the low-pressure center in eastern Iran. The low-pressure center in the eastern part of Iran has an important role in the precipitation of Iran. It is present in all patterns, but first one. The presence of this low-pressure center has created atmospheric fronts in Iran. The rainfall region of this pattern shows that the cold front activity of this low-pressure center causes precipitation. (C) The third pattern is similar to the second one, but a high-pressure center located in the north and northwest of Iran. The presence of this high-pressure center indicates the cold air advection behind the low-pressure cold front of eastern Iran. (D) The low-pressure center of the eastern part of Iran and the high-pressure center in the north and northwest of Iran exist in the fourth pattern. The difference between this pattern and the third one is elimination of Saudi low-pressure center in this pattern. Therefore, the dynamic effects are similar to the third pattern and the extreme precipitation caused by this pattern is due to the cold front of the low-pressure system of the eastern part of Iran. (E) The fifth pattern, like the third one, consists of low-pressure systems in eastern Iran and Saudi Arabia. The difference between these patterns is presence of low-pressure of Cyprus in the fifth pattern. The low-pressure of Cyprus is cause of classical precipitation pattern (formation of the occluded front) in this pattern. The occluded front in this pattern has expanded from low-pressure eastern of Iran to low-pressure in Cyprus and converted into a secondary cold front over several stages of the frontogenesis process.  In this research, the southwestern precipitation systems of Iran during the warm season are classified into five patterns. The most important factor of precipitation in the southwestern part of Iran is the Red Sea trough with 48% frequency of occurrence. Therefore, it can be concluded that almost half of the extreme precipitation of southwestern Iran during the warm season is related to this area that extends from the Red Sea trough to the west of Iran.

The Chah-Mesi polymetallic vein-type ore deposit, located 40 km north of Shahre-Babak city and 1.5 km southwest of Miduk porphyry copper deposit, is situated in the Dehaj-Sarduieh belt as a part of the Urumieh–Dokhtar magmatic Arc  (UDMA) (Figure 1).
The main objectives of this research study are to investigate: (1) characterization of multi-element distribution associated with Cu mineralization, in order to demonstrate prediction of elemental concentration applied to identify high-grade ore bodies, (2) evaluating the interrelationships between copper, molybdenum, iron, led, zinc, gold and silver.

Petrography and mineralography of the Chah-Mesi ore deposit were carried out using thin and polished sections. More than 980 chemical analyses of samples collected from 35 boreholes of the National Iranian Copper Industry Company (NICICO) were implemented to evaluate the statistical as well as spatial distribution and dispersion of multi-element halos. Geochemical data processing was performed by applying Excel (2010), SPSS (19), Datamine (Studio3.22.84.0) and Surfer10 (2011) software packages.

The Chah-Mesi ore deposit consists of four main and some minor polymetalic (Cu-Pb-Zn-Ag) quartz-sulfide veins, with NE-SW and N-S trending and 65-80 degree dipping, which intersected the Eocene volcanic and pyroclastic sequences (Figure 2). It seems that mineralization has mainly occurred along these quartz-sulfide veins overlaid by Quaternary alluvium. Based on rock outcrops, the prominent mineralization has been controlled by structural features including faults and fractures that provided proper conditions for reaction of hydrothermal fluids with the host rocks.In the Chah-Mesi ore deposit, silicified veins containing poly-metallic mineralization have predominantly occurred along the main faults and shear zones. The intensity of argillic alteration dramatically decreases outward from the mineralized quartz veins (Figure 3). Propylitic alteration which is composed of calcite and chlorite minerals has extended in the peripheral zones and does not represent a clear relationship with Cu mineralization.The main host rocks in the Chah-Mesi ore deposit consist of basalt to basaltic andesite, with porphyry to glomeroporphyry textures, and to a lesser extent of pyroclastic rocks (Figure 4). The ore bodies are mainly composed of pyrite, chalcopyrite, sphalerite and galena. The ore minerals are accompanied with chalcocite, malachite, covellite, azurite and iron hydroxides that have been formed during supergene and weathering processes (Figure 5). According to field surveys, structural controls have played an important role in the mineralization of the Chah-Mesi ore deposit.

Geochemical investigation in the Chah-Mesi ore deposit, using Pearson correlation coefficient of trace elements (Table 1), indicated the highest correlation coefficient (more than 0.7) between Pb-Zn and Ag-Au elements, due to their similar geochemical affinities during epigenetic mineralization. Other significant correlations were observed between Cu-Ag, Cu-Fe, Cu-Au and Fe-Ag with a correlation coefficient of more than 0.6; while the Mo shows weak correlation with other elements. Based on cluster analysis, the trace elements that are associated with mineralization can be classified into four main clusters of Pb-Zn, Mo, Cu-Fe-Ag and Au (Figure 6). Noteworthy, despite the fact that Mo and Au each separately form their individual clusters, Au still shows some proximities with the Cu-Fe-Ag cluster that indicate their genetic relationship. However, Mo displays the most dissimilarity with other clusters, which indicates the role of different processes in its distribution. The results of this analysis are well in line with correlation coefficients.The geochemical vertical zonality of trace elements in the Chah-Mesi ore deposit were studied using four borehole data from different parts of the ore deposit (Figures 7 and 8). This demonstrated that variation of elements at different depths does not follow a uniform pattern due to differences in the type and amount of ore minerals in the veins.The veins containing lead, zinc and gold mineralization are highly abundant at the shallower levels based on geochemical maps of the Chah-Mesi ore deposit (Figure 9). In contrast, the veins containing copper and silver mineralization have been considerably developed in both shallow and deeper levels. The high degree of Mo at shallow levels seems to occur due to either superimposition of primary geochemical haloes of various veins (Li et al., 1995, 2016) and/or the effect of amount of pyrite, pH, and alkalinity contents of hydrothermal fluids (Leanderson et al., 1987).The average value of different elements in intervals of 50 meters from the shallow (2500 meters) to the deep (2300 meters) levels are determined by existence of maximum abundance of lead, zinc and gold elements at surface levels. However, the highest average abundance of copper occurs in the deepest level. The highest average value of silver is also located in the 2450, 2350, and 2500 meters levels, which is economically valuable (Table 2). Therefore, the continuation of drilling in the southern part of the Chah-Mesi ore deposit into deeper levels is strongly recommended as there may still exist more concentrations of copper and silver there.

Edge detection is a fast and qualitative interpretation method to achieve information from potential field (e.g. gravity) anomalies. In the edge detection methods, the separation of overlapping amplitudes of anomalies and accuracy of edge detection are very important. There are various methods for edge detection. Most of these methods are based on the gradients of the potential field data. The gradients are sensitive to noise. Statistical methods have been used to increase the accuracy of edge detection. Normalized standard deviations (NSTD) and correlation coefficient of multidirectional standard deviations (CCMS) are among these methods.

There are several edge detection methods based on gradients of data. Each of these methods has some strengths and some weaknesses. In the selection of these methods for a particular case, simplicity and better performance are considered. These methods include: total horizontal derivative (THD), Theta angle, Tilt angel, hyperbolic tilt angle (HTA) and a new method based on the gradients, called normalized total horizontal derivative (NTHD). In addition, the semi-statistical method of NSTD and statistical method of CCMS are among these methods that have been explained in this paper. The NSTD method is obtained from the standard deviation of the gradients, however, the CCMS method does not use the gradients. This method is completely a statistical method, which is based on correlation coefficient and standard deviation.

In this paper; after examining the above-stated edge detection methods, they have been applied on both synthetic and real data. The performances of these methods are compared in the presence of noisy data, overlapping amplitudes of anomalies and their accuracies in edge detection.

The results of applying the above-stated edge detection methods on the synthetic data show that the gradient-based edge detection methods are sensitive to noise, depths of anomalies and overlapping amplitudes of anomalies. The NTHD, NSTD and CCMS methods are less sensitive to noise than the other edge detection methods. These methods detect anomalies with different depths and separate anomalies with overlapping amplitudes. In all of these methods, as the depths of anomalies increase, the accuracy of edge detection decrease. This study show that the CCMS method has the best result when applied on the synthetic data. Furthermore, applying the CCMS method on the real data yields better results in comparison with the other edge detection methods. The results of edge detection by this method have been shown on the bouguer map. Thus, this method reduces complexities of edge detection that can be useful for the interpreter.

In this research, the possible effects of NAO, on Tehran air quality during 2007-2016 were investigated. First, the daily indices of air quality of Tehran in the autumn and winter seasons for the study period were applied to identify polluted and unpolluted periods. The 1th ,5th and 9th deciles of the air quality indices were chosen as the indicator for good, middle and bad air qualities. Based on these indices, five polluted and eight unpolluted periods were identified. Then, the daily indices of NAO and air quality of Tehran were used to calculate the Pearson correlation coefficients and discuss the relationships between air quality and the NAO indices. In this regard, we attempted to find out the optimum time lag for each case by examining different times that there was maximum correlation between air quality index and the NAO indices. For dynamical study, the European Centre for Medium-Range Weather Forecasts (ECMWF) (ERA- Interim) reanalysis data set including mean sea level pressure, wind, temperature, geopotential height, and specific humidity in a time period from 1979 to 2017 were used. The horizontal resolution of the initial data is 0.75°×0.75° in longitudinal and latitudinal directions prepared operationally every six hours at 60 levels.  The statistical analysis of the NAO indices shows that in the polluted periods, the positive phase of NAO is dominant, while there is no significant statistical difference between the positive and negative phases of NAO in the unpolluted periods. In general, the unpolluted periods (five cases) are associated mostly with the negative phase of NAO. Because of this limitation, we decided to analyze the synoptic-dynamic situations of all cases using the anomaly maps of the quantities relative to their long means. Thus, it is possible to improve the reliability of the results concerning the the effects of NAO on air quality in Tehran. Synoptic-dynamic analysis of the cases with the highest correlation between Tehran air quality index and NAO daily indices indicates that in the positive phase of NAO, there was advection of warm and humid air to the study area, while the Middle East region had a cold and dry conditions. On the other hand, when NAO was in the negative phase, advection of moist and colder air from the Atlantic Ocean toward the east occurred, thereby existing better air quality in the region. Besides, when polluted air period coincided with the negative phase of NAO, in contrast to the normal situation, the deviation of the Siberian high-pressure axis into the meridian and adhering to the Azores high-pressure created a barrier against the westerly winds causing their meridional deviations. In the unpolluted air periods associated with the positive phase of NAO, in contrast to the normal situation, the positioning of the Atlantic high-pressure at higher latitudes, with respect to the mean state, and joining with the Siberian high-pressure make them act as a barrier in the middle latitudes, thereby existing zonal winds in the study area.

Quality of recorded information in a monitoring network plays an important role in sustainable design and operation of water resources systems. For an optimal monitoring network design, they should be evaluated periodically based on the information needs and future water resources development plans. In this study, regional values of groundwater quality monitoring network stations in Khanmirza plain were investigated using the discrete entropy theory. Discrete entropy can overcome the limitations regarding data normality assumption in past research. Several entropy parameters such as marginal entropy, joint entropy, information send and received by each station and transinformation index between stations, were calculated to identify essential stations and poor regions based on the amount of information exchanges. Sensitive analysis to number of discrete intervals shows that the entropy indices are sensitive to change of interval length, but the ranks of stations appear to be less sensitive. Validation result confirms that the entropy has a good performance in quantifying the regional values of sampling wells in a monitoring network and comparison with the correlation coefficient of information between stations shows that this coefficient can be used for determining the essential and unnecessary stations in the region.

In this study, the optimized DRASTIC model parameters and land use layer (LU) were used to assess specific vulnerability in Kashan aquifer using statistical methods. Information layers were prepared, rated (deterministic and fuzzy-statistical), weighted (original and statistical) and combined (by Index-Overlay method) in GIS environment. For optimization of DRASTIC model, nonlinear regression for fuzzy-statistical rating (scaling) and Pearson correlation coefficients between nitrate concentrations and scaling parameters of DRASTIC model and sensitivity analysis (removal and single-parameter) were performed to determine and modify weighted parameters. As a result, RASIC-LU model with statistical rating and weighting, single-parameter sensitivity analysis, determined the best selection model based on correlation coefficient = 61.1%, P-Value= 0.001 and with parameters of net recharge, aquifer media, soil media, impact of vadose zone, hydraulic conductivity and land use with weight values of 2.50, 4.63, 4.15, 3.03, 1.96 and 2.00 respectively. According to this model, western and southern parts of the aquifer has a high and very high pollution risk due to high net recharge, pollutant land use and coarse-grain material in the impact of vadose zone, soil and aquifer media. In addition, sensitivity analysis based on mean squares error (MSE) indicated that this model is more sensitive to removal and increase of parameters weight of land use, soil media, impact of vadose zone, aquifer media, net recharge and hydraulic conductivity, and shows a decreasing ternd, respectivily.