دکتر ابوالقاسم کامکار روحانی

Chahmusa area, with a surface area of 28.54 square kilometers, is located in Semnan Province. Chahmusa mine is located in the south of Shahrood city and the northwest of Troud village. This research aims to do mineral Reserve modeling and estimation in the Chahmusa area. Additional exploration studies have been carried out in a limited area with a surface of 56 hectares northwest of the area. These exploration studies in the area include 1:1000 topographic mapping, preparation of 1:1000 mineralogical and tectonic maps, core drilling, logging, sampling, and reserve estimation. From the geological point of view, this area includes all types of volcanic rocks, such as pyroclastic and volcanoclastic rocks, with intermediate to acidic compositions that can be seen in some parts of the dike that occurred in the area. Economic and geological studies of mineralization type in the Chahmusa area place the mineralization in the category of copper deposits of manto type. In order to obtain the geometry of the deposit and estimate the reserve, 66 cored boreholes with a total length of 13360.50 meters, of which 22 cored boreholes with a total length of 3826 meters, have been used in reserve evaluation. In addition to lithological and mineralogical logging. Were carried out in the area. In this study, the estimation space of the grade-structural model based on the information on mineralization-controlling fault in the area was constructed, and the grade information of boreholes with a copper grade of more than 0.1% was obtained using different software packages. Reserve estimation was made using search ellipse specifications, optimized estimation parameters, block model, and ordinary kriging and inverse distance square methods. Due to the better results of the ordinary kriging method, these results were presented in this paper. In order to control the calculated reserve estimation, vertical sections were also used to calculate reserve estimation. The results imply that the estimation accuracy was achieved using the ordinary kriging geostatistical method. The oxide zone was separated based on the grade of copper oxide and considering the oxide ratio of 30%. The amount of geological resources with a copper grade of 0.1% is 4.4 million tons with an average copper grade of 0.74%. From this amount, 1.3 million tons with an average grade of copper of 0.75% are the reserves of copper oxide type, and 1.3 million tons with an average grade of copper of 0.73% are the reserves of copper sulfide type. The measured resource (i.e., definite reserve) is 2.3 million tons with an average copper grade of 0.77% (the copper oxide reserve part is 2.2 million tons with a copper grade of 0.78%, and the copper sulfide reserve part is 950 thousand tons with a copper grade of 0.75%).

[1] Corresponding Author Human activities, such as mining, constructing highways, and building infrastructures like dams and industrial facilities, have caused significant damage to many natural ecosystems. In addition to disrupting the balance of these ecosystems, some of these activities have led to considerable pollution. Traditional methods, such as geostatistics and geophysics, while helpful info helpful in identifying contaminated areas and measuring the extent of pollution, are often costly, time-consuming, and come with helpful in identifying areas and measuring the extent of pollution, are often expensive, time-consuming and come with various limitations. To address these limitations, remote sensing data can provide an effective solution. The foundation of remote sensing lies in the spectral frequencies or images captured through satellite or drone equipment. Remote sensing data processing methods for identifying the type and estimating the extent of soil contamination fall into three main categories: physical models, mathematical models, and physics-based mathematical models. Given the various challenges associated with remote sensing of pollution in mining areas and their surroundings and the limited research conducted—particularly in Iran—this study addresses a critical important important important necessary conducted undertaken—particularly in Iran—this study addresses the essential gap. Iran hosts numerous mining sites in or near critical environmental ecosystems, making pollution management in these areas a pressing issue. This research proposes a method combining fuzzy clustering and edge-based features to identify surface and physical soil contamination caused by mining activities and coal-washing waste from the eastern Alborz coal preparation plant. This approach uses Sentinel-2 satellite imagery at a 1:100,000 scale for the studied mining area. The study focuses on the eastern Alborz coal mining region in Semnan Province, Iran. This area lies 140 kilometers from the provincial capital, 25 kilometers northeast of Damghan, and 75 kilometers from Shahroud.

This study investigates the efficiency of different geophysical methods for detecting contaminated zones as well as hidden pipes. There are a number of geophysical techniques that can be useful and beneficial for achieving these purposes. Ground penetrating radar (GPR) and electrical resistivity methods are the most useful approaches for identifying polluted areas and buried features, causing us to utilize such methods in the area. Although GPR and electrical resistivity methods are solely effective for mapping subsurface targets, the integration of these methods might provide us valuable information and valid outcomes. In this paper, electrical resistivity and GPR surveys are conducted and acquired data are modelled to investigate the pollution leakage in the ground. To achieve this aim, a polyethylene pipe with inlet and outlet valves is considered as a tank buried underground in the geophysical test site of Shahrood University of Technology. In the first step of the study, the electrical properties of the empty pipe were measured and modelled using electrical resistivity and GPR methods. In the next step, the pipe was filled by the cupric sulfate solution and electrical measurements were performed again. In addition, the electrical properties were investigated by means of electrical resistivity and GPR methods in another area, sitting on alluvial soil, after and before injecting the cupric sulfate solution. It is worth mentioning that the measurements were performed after drying the surface which was humid due to the injection of cupric sulfate to avoid false conductivity on the ground. The designed profiles include four lines on a buried reservoir and five profiles on alluvial soil. However, the 2D modeling results and interpretation of the acquired data along with two (on the buried target) and three (on alluvial soil) survey lines are just presented in this paper. After collecting and interpreting the electrical resistivity and GPR data in the study area, the results are in the form of two-dimensional models of electrical resistivity and GPR cross sections, which have been obtained by use of RES2DINV and Prism2 softwares, respectively. The obtained results revealed that the electrical resistivity method enjoys a relatively good performance in detailed detection. It is also shown that the GPR method is not able to work properly in alluvial soils with high clay and it suffers from the unsuitability of the transmitter antenna with a frequency of 150 MHz and the destructive effect of moisture on the performance. Regarding the obtained outcomes and using electrical resistivity data, ground details such as polyethylene reservoir, loose and porous soil parts and separation of different areas according to the relative humidity in them have been revealed.

Nowadays, the use of new methods to estimate hydraulic parameters such as soil moisture characteristic curve is considered. The aim of this study was to determine the effective factors in modeling of moisture characteristic curve parameters, from conveniently available, by the decision tree and error estimator cross validation and resub stitution were used. In this study, 72 soil samples were collected from six different tissues from the village of Margalomk and Shahrekord city. Conveniently available soil properties were introduced into software in 2 scenarios (the first scenario %sand, %clay, OM%, CaCO3, BD, pH, EC, mean weight diameter of dry aggregate (MWD dry), mean weight diameter of wet aggregate (MWD wet) and θs, the second scenario %sand, %clay, OM%, CaCO3, BD, %gravel, electrical resistivity, dielectric constant, root penetration resistivity). The results showed that the correlation coefficient for the PWP target variables in the first scenario is 0.88 and in the second scenario the maximum value for the FC target variable is 0.93. By replacing, geophysical and mechanical properties in the second scenario, the correlation coefficient for the variables FC and α Which are affected by the structure and texture of the soil increased, and decreased for PWP, n and m variables, which are more affected by soil texture. %RMSE was also slightly lower for the FC and α variables in the second scenario than in the first scenario, but in general according to% RMSE, modeling for all variables was successful in both scenarios.

Basic approach for investigation of Khazar fault, due to covered areas by quaternary deposits and absence of the fault outcrop in some of areas in the region, is to use the subsurface exploration methods, and especially, high resolution geophysical methods. In this study, we calculated the subsurface geometric parameters of Khazar fault, geological model, and especially, the Khazar fault borders in Khalilshahr region by comparison of GPR and resistivity profiles, and combining the results with geological results, and then, we made forward and inverse modeling of the resistivity and GPR data.

Increasing demands of raw materials and energy resources has led to a fast growth in the geophysical studies. Due to the properties of minerals and geological conditions, there are various geophysical methods. Among these methods, magnetic method is capable of exploring the magnetic mineralization of rocks with relatively high or low magnetic properties. In this method, the magnetic field variations of the ground are measured. Sonajeel is located 17 kilometers from Harris, East Azarbaijan Province. The main stone units in this area are from the old to the new: volcanic and volcanoclastic rocks, Sonajeel porphyry stock, Incheh granitoid stock, and Okuzdaghi volcanic rocks. In this study, the magnetic method is used as an indirect method for identification of copper ore deposits. Based on the magnetic method, information can be obtained about the gradient, depth, shape, and extension of the source of anomalies. There are several examples for using this method (especially the airborne magnetic method) to explore the copper deposits. Including the copper project in the Cadia region of Australia, as well as the use of magnetism to explore the mineralization of copper and gold in the polymetal exploration area of Bashmaq Hashtrood. For the aim of identification of copper mineralization in the study area, the magnetic data along 19 survey lines were carried out. The length of each line was considered to be1000 meters and magnetic measurements were made at magnetic stations having distance intervals of 20 meters. The distance between the successive survey lines was 50 meters, except the distance between survey lines 19 and 18 that were located 30 meters from each other. The total survey area was about 1 km2. After applying diurnal correction on the magnetic data, the processing of the data was made by applying various filters such as reduction to the pole (RTP) to remove the effect of the inclination angle and to locate the subsurface position of the anomaly that is assumed to be symmetrically placed on the creator mass, upward continuation filter to study the process of mineralization in depth, and also, vertical derivatives and analytical signal processing methods were used to estimate the anomalous boundaries. Three-dimensional (3D) modeling of the magnetic data was also carried out using the Mag3d software. The results indicated that the mineralization process was extended in the north and north-east to the south-east of the study area. Upward continuation filtering was applied to the data at altitudes of 20, 40, 80 meters. The maps resulting from this filtering represented the root of the subsurface anomaly in the southeastern of the region. As a result of comparison of the various magnetic images with the 3D model, obtained from modeling the magnetic data using the Mag3d software, we found out that the copper mineralization in the study area is scattered but covers a large range of the area. Moreover, according to the results of 3D modeling of the data, the magnetite susceptibility in north and northeast of the study area is more than that in south and southeast of the area. The contrast of the magnetic susceptibility in north of the study area from the depth of 100 m to 270 was high, however, in the east and southeastern parts of the study area, from the depth of more than 100 meters, there was a high magnitude of magnetic susceptibility. Hence, it can be concluded that in the northern parts of the study area, potassic alteration was closer to the ground surface. It should be mentioned that the potassic alteration is a good place for copper and magnetite mineralization as the copper and magnetite mineralization is located in the center or middle of the potassic alteration. By comparing and interpreting the magnetic results and assessing these results with the geological data or information from the study area, the probability of occurrence of the magnetite mineral and, consequently, the copper mineralization or deposits in the Sonajeel area is highly indicated.

OOne of the most important hydraulic parameters affecting soil quality is the infiltration of water into the soil. That, the direct measurement of infiltration process is difficult, time spending and expensive. Infiltration models play the main role in managing watershed. Therefore, it is necessary to study different infiltration models in order to compare and achieve the best infiltration model in the area. This research determined the best infiltration estimation model in the pasture, garden, agricultural land uses (in two textures of silty clay loam and clay loam), in the Charmahal and Bakhtiari province. In this study, infiltration measurements were carried out using the infiltrometer single ring (to the inner diameter 35 cm). The initial humidity measured were respectively in pasture land use in silty clay loam and clay loam tissues (3.71, 4.27), in garden land use (2.18, 3.46) and, in agriculture land use (1, 2.25). and then infiltration models of Philip, Kostiakov and Soil Conservation Service of America (SCS), used and thus evaluated by the coefficient of determination (R2), Nash-Sutcliffe sufficiency score (NSSS), root mean squared error (RMSE) and mean error (ME). The results of this study showed that in rangeland use, the infiltration of all parameters (cumulative infiltration, the final infiltration rate and infiltration rate), is less than the garden and agriculture land use. It also compares the models, in the rangeland, but Kostiakov Model was accepted as the appropriate model in the garden, pasture and agricultural land use (in two soil texture), by Nash-Sutcliffe efficiency coefficient 0.99 and R2 (0.99) and a smaller error than other models. The next good models that had high efficiency were the Philip model by Nash-Sutcliffe efficiency coefficient and (R2=0.99) and an error of (0.15) in garden land use in silty clay loam texture, and the SCS model in pasture land (in SCL texture) with an error of 0.18.

Chahar-Gonbad region of Kerman province is geologically located in the southern part of central Iran zone, dominantly in Uromieh-Dokhtar volcanic belt. In this region, many high potential prospects, specially Cu-Au mineralization, have been detected during large scale exploration and reconnaissance phases. In this paper, remote sensing and field geophysics were used for alteration mapping on the surface and ore body delineation on the subsurface, respectively. To this end, we used an ASTER satellite image and different maps were generated by spectral technics such as false color composites and spectral ratios. Results showed argillic (and phillic) alteration in Bab-Zangoeie area is surrounded by propylitic alteration, which could be a promising evidence for Cu mineralization. Integrating these results with previous exploration studies led to selecting target area selection for ground study and field geophysics. We used both induced polarization (IP) and resistivity (RS) methods as two powerful geoelectrical methods by a pole-dipole array along four profiles. After preprocessing analysis, forward and inverse models were constructed in 2D section and 3D overlay model of joint IP/RS anomalies were constructed. Based on the obtained results, the deposit in depth where we proposed drilling targets. Further drilling operation have proved the mineralization in our proposed targets..

Independent component analysis (ICA) is a relatively new multivariable statistical method originally devised for the blind source separation (BSS) problem, where there is no information on how to mix primary sources (mixed signals) and only the necessary condition is independence of the primary signals. Hence, ICA can be used in mineral potential modeling where several independent mineralization processes result in observed variables such as geophysical and geochemical information, and we do not know how the geophysical and geochemical effects of different mineralization processes are mixed together. In this study, we tried to introduce the ICA method as a knowledge-driven method of mineral potential modeling. To this end, an area of 4800 square kilometers in south of Neyshabur, northeast of Iran, was investigated to map the mineral potential of podiform chromite deposits. In this regard, geochemical stream sediment sampling data, ophiolitic facies map, structural pattern of fractures and serpentinite alteration location in the region were used for this study. Finally, the results of mineral potential modeling by the ICA method were compared with the results of univariate and multivariate geochemical studies and were also validated by using locations of the known mineral prospects in the region and receiver operating characteristic (ROC) method. As a result, the area under the ROC curve was marked by 0.967, indicating the outstanding performance of the ICA modeling.

"Sulfide-carbonate" deposit is a term, which comprises a series of sulfide minerals such as Zn-Pb ore minerals, mainly considered as related to weathering of Zn-Pb sulfide concentrations and influence in sedimentary hosts (carbonate). There are more than 350 Zn-Pb deposits located in Iran, including world-class deposits such as Angouran, Mehdiabad and Irankouh. Due to the mining activity of these deposits, it creates a significant amount of mine waste that releases of these wastes in the environment causing severe problems. One of the main problems is the formation of Acid Mine Drainage (AMD). AMD is produced by oxidation of sulphide minerals, particularly pyrite (FeS2) in waste dump. Due to low pH and the ability to dissolve metals and other compounds, it can host a number of environmental problems. A phenomenon known as natural or alkaline mine drainage (NAMD) occurs at high pH values ​​when the neutralizing minerals are significantly present in the mine waste or when the oxidation of the sulfide minerals is poor. However, the metals and cationic species, such as Cu, Pb and Cd, are more soluble at low pH. In contrast, elements that form anionic species, such as Se, Cr, V, and Mo, tend to be more soluble at high pH and Ni, Zn, Co, As, and Sb, are soluble at near-neutral pH, and can potentially contaminate mine effluents, even without acidic conditions. Therefore Acid or Neutralization potential (AP&NP) of waste dump is significantly affects on the composition, transfers and fates of contaminations transmitted from waste dump. The aim of this study was to monitoring heavy metals concentrations and assessments of pollution potential of waste dumps in Anguran mine by static method and has been compared by mineralogical approach.

The Angouran Zn-Pb deposit is located in the 135 kilometers southwest part of Zanjan Province, NW Iran. This area belongs to the northwestern part of the Sanandaj-Sirjan Zone, a metamorphic belt related to the Zagros orogeny. Angouran mine is one of the most important carbonate hosted Zn-Pb deposits in Iran that mining activity has been created a significant amount of waste dump in around pit. To achieve the goals, the 47 samples taken from different surficial parts of the waste dump were analyzed by using the ICP-MS method to determine the concentration of elements and heavy metals. These elements and metals includes: Ca, Mg, S and As, Cd, Cr, Cu, Ni, Pb, Zn. The pollution index (PI) were modeled for heavy metal contamination risk zoning then modified Acid Base Accounting (ABA) static method was used to evaluate of acid and neutralization potential (AP&NP) of the waste dump samples and the results were modeled by Kriging method. At the end, mineralogical approach (Mg + Ca concentration) was used to determine the source of neutralization and to better interpret the static results.

The results of contamination index showed that zinc, arsenic and cadmium had the highest average contamination index (18.89, 12.13 and 5.8, respectively) and the trend of total metal changes in the region as Zn> As> Cd> Pb > Ni> Cr> Cu was rated.Datas measured in modified ABA method were modeled in 2D maps using the Kiriging method. Due to the low total sulfur content (less than 1%), all of the samples were Net Neutralization Potential (NNP) with a range of 49- 990 kg calcium carbonate per ton, and the study area was classified into three neutralization potential (NP), High (NP) and Very High (NP) levels. The mineralogical approach (Mg + Ca concentration) was used as a useful tool for better interpretation of modified ABA results and determines the neutralizing source. Mineralogical approach results indicate that calcite species are the main source of neutralization and have high correlation coefficient (R = 0.99) with the modified ABA method. In order to validate the results, the presence of mineral calcite was confirmed by XRD analysis on 4 samples.Assessment of AP and NP of sulfide – carbonate waste dump in this research can be used as a basis model for other similar mines to control environmental problems and to identify the behavior and to transfer heavy metals in mine drainage in the future. Mineralogical approach results show that neutralizing potential and neutralizing source can be obtained without using expensive mineralogy analyses in this type of carbonate-sulfide deposit

Soft computational techniques have been widely used in scientific research and engineering in recent decades. Since the measurement of hydraulic properties by direct laboratory methods is hard, time consuming and expensive, Thus, there is need to use alternative methods based on conveniently available soil properties to estimate it with less effort, time and cost. One of the new methods for estimating soil hydraulic properties, such as soil moisture characteristic curve, is non-parametric methods. This study was performed to determine the efficiency of the decision tree method in separation of effective properties in estimating soil moisture characteristic curve parameters.

To perform this study, number of 72 points were selected in the village of Marghmalek and Sharekord city. Samples were collected from depth of 0-20 cm and then were transferred to the laboratory for required measurements. Some properties such as pH, EC, saturated moisture, calcium carbonate, organic matter, clay and sand, bulk density, mean weight diameter of dry aggregate, mean weight diameter of wet aggregate, geometric mean and standard deviation of particle diameter were measured in the laboratory. Also, the moisture characteristic curves were determined at 0, 1, 3, 5, 10, 30, 50, 100, 150, 1000, 1500 kPa suctions and were fitted to the van Genuchten model. The input variables were introduced into the MATLAB software in two scenarios (first scenario: pH, EC, %clay and sand, organic matter, calcium carbonate, mean weight diameter of wet and dry aggregate, bulk density, saturated moisture and the second scenario: pH, EC, geometric mean and standard deviation of particle diameter, organic matter, calcium carbonate, mean weight diameter of wet and dry aggregate, bulk density, saturated moisture) and modeled by decision tree and error estimators of cross validation and resub stitution. Evaluation statistics of each model including R2, RMSE and %RMSE were calculated.

The results obtained from decision tree modeling showed that the most important factors affecting moisture content in PWP suction, were saturated moisture and clay. The PWP target variable has the highest correlation in the first scenario (0.88) and in the second scenario )0.91( and the least error rate among the other variables, and after that, FC has the highest correlation (0.86) in the second scenario. Target variables n had the highest error rate and α the lowest correlation in both scenarios. Generally, the second scenario performed better than the first scenario by replacing the geometric mean and standard deviation of particle diameter with the percentage of clay and sand. The sensitivity analysis showed that PWP was the most sensitive among the input parameters to pH, BD, calcium carbonate and organic matter and FC was the most sensitive to geometric standard deviation of particle and MWDwet.

In general, modeling has been successful in both scenarios. But by substituting geometric mean and standard deviation of particle diameter instead of clay and sand percentage, a better performance was obtained in estimating moisture characteristic curve variables in the second scenario.

Soil water is an important factor in the growth of the plant. There are different methods for soil moisture estimation. It is time-consuming to obtain volumetric soil moisture in a laboratory. This study was performed to evaluate estimate of soil moisture by different in situ methods including the electrical resistance of Werner electrode arrangement and ground penetration radar (GPR) from 700 MHz antenna, and two humidity sensors, namely, thetaml2 and sm300. These were used in 72 soil samples with different textures (loam, sandy clay loam and silty loam, silty clay, silty clay loam, clay loam) in parts of Shahrekord Watershed.The results showed that the coefficient of correlation between soil moisture and electrical resistance was 0.85. Also, the correlation coefficient between the values obtained from subsurface radar method, sm300 sensor and thetaml2 with the results obtained from laboratory measurements were 0.86, 0.94, 0.86, with CRM index values of -0.52, -0.75 and –1.22. By comparing the results of electrical resistivity, moisture from the GPR and the sm300 and thetaml2 sensors with volumetric moisture, the Root Mean Squared Error (RMSE) values were 8.41, 4, 5.3 and 8.6; and RRMSE were 10, 31, 29, and 26, respectively. Duncan test of moisture content showed that the difference between the sensors and the laboratory moisture content was significant at 5% level (p<0.05). According to the value of RRMSE All sensors had a good estimate of soil moisture. In conclusion, electrical resistivity and GPR method, due to higher sampling density, could be used as a rapid, cost effective, and non-destructive technique to estimate profile of soil water content at scales of field to sub-watershed.

Project time and cost are one of the issues and challenges that employers and contractors are facing whit them especially in the forest area. One of the most effective tools that used in prediction and risk analysis is Monte Carlo analysis that Based on the production of random numbers, the number of single components of a set is computed and find out their effect on the whole set. In the traditional approach to project control that still dominates in most national projects, estimating the probable time and budget of the project is still unpredictable to managers and experts. In this work, we tried to present a model for considering the probability and risk in estimating the probability of completion of the project by given time and cost of project termination in a forest area using a case study and software capabilities (Primavera Pertmaster). The results of the probability distribution revealed that the probability of reaching the predicted budget was approximately 13% according to the Monte Carlo simulation. However, the difference between the maximum and minimum values varies from 39 to 650 million IRR, which results in a high risk of the operation of the land operations, which indicates the high risk of the earthwork operation. The real cost of earthwork (570 million IRR) in the study area at the cost allocation chart is estimated at 90%, which also confirms the riskiness of the road earthwork project. Finally, the Monte Carlo simulation method, with the successful prediction of the risk of earthwork operation project, showed that there is an acceptable way for contractors and forest road designers to deal with the negative aspects of the project. The results of this research can be used as a guide to better management of forest for future operations.

For designing forest roads that in addition to minimize the cost of constructing, satisfy environmentalists, it is necessary to provide designers and contractors accurate data from surface and subsurface conditions of the road area due to the large-scale of data using of optimization methods (metaheuristic algorithms) with the help of computers is necessary. For this purpose, this research was carried out on a proposed forest road whit length of 1 km in the forests of the district 4 of Babakoh in the city of Siahkal in Guilan province. The cycle of all earthwork work was studied by continuous time study method and the information of the subsurface layers terms of digging was carefully recorded. The results of comparing the method of the ant colony with the hand-made design scenario showed that the multi-objective algorithm presented in this study has great potential for reducing the cost of earthwork operations and its volume. Based on the results, the algorithm is able to reduce 58.55 and 64 percent the cost of earthwork operations and the volume of operations, respectively. Finally, the results of this research can be used as a guide to better management of forest areas, especially forest roads with the development of efficient methods in all forestry forests.

Soil saturated hydraulic conductivity is one of the most important physical characteristics of soils that affects water movement in soil. . The aim of this study was to determine the most important parameters in prediction and modeling of saturated hydraulic conductivity from conveniently available parameters, using the decision tree and error estimator cross validation and re- substitution. In this study, 72 soil samples with six different textures were collected from the village of Morgmalek and Shahrekord District. Conveniently available soil properties were introduced into software in 4 scenarios (the first scenario: pH, EC, % sand, % clay, OM%, CaCO3, mean weight diameter of dry aggregate (MWD dry), mean weight diameter of wet aggregate (MWD wet), BD; the second scenario: CaCO3 , OM%, % sand, % clay, BD, % gravel, electrical resistivity, dielectric constant, root penetration resistivity; the third scenario: pH, EC, Geometric mean diameter )dg(, Geometric standard  deviation )σg(, OM%, CaCO3, mean weight diameter of dry aggregate (MWD dry), mean weight diameter of wet aggregate (MWD wet), BD; and the fourth scenario: CaCO3, OM%, dg, σg BD, % gravel, electrical resistivity, dielectric constant, root penetration resistivity). Saturated hydraulic conductivity was measured with single ring. The results showed that moisture followed by structural features such as (σg) in the first scenario, and OM and BD in the second scenario, BD and MWD in the third scenario, and OM and BD in the fourth scenario were the most important parameter affecting saturated hydraulic conductivity. Correlation between predicted data by decision tree and measured data in the second and fourth scenarios were 0.83 and 0.82, respectively, and 0.79 in the first and third scenarios. All four scenarios were successful in modeling with respect to error rate and %RMSE. However, the %RMSE in the second and fourth scenarios was lower and the correlation coefficient was higher than the other two scenarios. The RMSE values in the four scenarios were 0.79, 0.83, 0.79, and 0.82, respectively.

Heavy metal pollution is one of the main environmental problems associated with mineral, industrial and agricultural activities in the world. Due to the long life of these toxic metals and the degree of solubility in acidic and even non acidic conditions, they can have destructive effects on water, soil and humans life in the long time. The lead-zinc mine of Anguran is one of the largest world-class sulfide-carbonate reserves, which, due to mining, has produced a significant amount of mineral wastes, which can be the source of heavy metals to the water and soil of the downstream areas. Therefore, the use of quick and cost-effective methods to classify the risk of contamination of this type of waste can be a useful tool for monitoring, recovery and reconstruction programs in the future. The purpose of this research is to use multivariate statistical techniques, such as discriminant analysis (DA) method and utilize of artificial intelligence technique in order to classify and predict the potential of pollution in mining wastes. To achieve the goals, the samples taken from different surficial parts of the waste dump were analyzed by using the ICP-MS method to determine the concentration of heavy metals. These metals includes: Al, As, Cd, Co, Cr, Cu, Fe, Mn, Mo, Ni, Pb, Sb and Zn. The environmental risk assessment indices (ERAI) and potential load index (PLI) were then modelled. At the end, by using the DA and neural network (NN) methods, potential risk of contamination on the damp surface was classified in three low, medium and high levels with the accuracy of 91.49 and 93.6 percent respectively. The results also showed that these techniques can be used as effective tools for classifying new waste dumps and designing of new constructing dumps based on their contamination level.

The host rock in Chumalu area includes the Eocene volcanic rocks and the Oligocene monzonite intrusive mass that have undergone propylitic-carbonate, silica, and silica-argillic hydrothermal alterations. The hydrothermal activities resulting from the injection of intrusive mass have produced two types of mineralization in the region: the first mineralization type is a silica-shear zone having N70E trend, and the second type is in the form of a bunch of veins with an approximate trend of northwest to southeast, located in the north of the first mineralization type. The mineralization is of the form of vein, veinlet, massive, scattered and replaced, and follows the trend of the faults. The ore contains lead, zinc and fluorine, along with copper, gold and silver, which are formed of chalcopyrite, pyrite, galena, sphalerite, cerussite, calcite and fluorite minerals. Based on the results of the geological studies conducted in this study, the mineralization characteristics of Chumalu area are of the type of lead and zinc hydrothermal deposits. Induced polarization (IP) and resistivity data acquisition were first designed and carried out using rectangular array to determine the anomalous zones, and then, using dipole- dipole array to determine the lateral and depth limits of these anomalies. Then, modeling of IP and resistivity data was done using smooth inversion method. For better representation of the results, all two-dimensional (2D) sections were combined and as a result, a three-dimensional (3D) model was presented. Consequently, an anomaly with an approximate east-west orientation in the south of the area has been extended on the silica-shear zone, and some anomalies with an approximate north-south orientation in the north of the area, in relation to the fractures of the basaltic deposits, which can be linked with metallic mineralization in the area. Anomalous areas with high chargeability and medium to low resistivity values have been determined. High chargeability values for some anomalies in the north of the area are probably due to the presence of scattered pyrites in depth. Finally, 6 points were proposed for drilling.

Application of IP and resistivity geophysical methods and their integration with geological studies is of great importance in the exploration of sulfide metal deposits. The Chumalu area is located 70 km northwest of Zanjan in the Tarom-Hashtjin metallogenic zone, which has possible potential for metal reserves and mineral resources. The purpose of this research is to collect and process raw IP and resistivity data using the smooth inverse modeling, interpretation of the results based on geological studies and finally determining the anomalous limits, depth and thickness of probable mineral masses in the area and at the end, suitable locations for drilling are suggested.

This research is based on field and laboratory studies. In order to conduct geological studies, alteration, mineralization and determination of the genesis of the mineralization, 8 thin sections and 9 polished sections of surface and subsurface samples from the mineralization ore and host rock were prepared and studied. Moreover, field operations of IP and resistivity data acquisition were first made in the form of 4 networks using rectangular array in order to determine the anomalous limits with a current line of 800 meters long, electrode spacing of 20 meters, and the distance between the lines 50 meters. Then, 6 lines using dipole-dipole array were surveyed in order to explore the lateral and depth limits of these anomalies with electrode spacing of 20 meters. Then, modeling of IP and resistivity data was made by 2D smooth inversion method using RES2DINV and ZondRes2D software packages. Furthermore, all 2D sections were combined using RockWorks software and a 3D model was presented. Ultimately, possible mineralization limits were identified and suitable sites for drilling were proposed.

Based on the geological studies, lead and zinc mineralization in olivine basalt volcanic host rock and part of the monzonitic intrusive mass in Chumalu area occurs during hydrothermal processes and in the form of veins along fault structures. Chumalu mineralization is of hydrothermal lead and zinc type. Based on geophysical and geological studies, anomalies have been introduced that have high chargeability and medium to low resistivity, as probable mineralization. Finally, 6 locations were proposed for drilling.