Wood chips as soil conservation in field conditions

The soil conditioner in processes of soil conservation is important especially in heavily eroded areas. Because in this study done in Educational and Research Forest Watershed of Tarbiat Modares University, north of Iran, the experiments created four treatments of control and different wood chips with rates of 0.5, 1, and 1.5 kg m^?2, by rainfall simulation in rainfall intensity of 60 mm h^?1, and plot scale of 1 m² on changing ponding time, runoff coefficient, sediment concentration, and soil loss. The results showed that the average change ponding time in control treatment and wood chip treatments with rates of 0.5, 1, and 1.5 kg m^?2 were 4.25, 7.48, 11.63, and 12.45 min. Also, the average change runoff coefficient in control treatment and wood chip treatments with rates of 0.5, 1, and 1.5 kg m^?2 were 50.03, 26.27, 15.28, and 13.17 %. The results also indicated that the wood chips could decrease average soil loss with the rates of ?52.15, ?82.18, and ?89.35 % compared with control treatment for 0.5, 1, and 1.5 kg m^?2 of wood chips, respectively. The one-way ANOVA results showed that the runoff coefficient, sediment concentration, and soil loss decreased with increasing wood chip amount, and the effect of conservation treatment was significant on study variables (R ² = 0.99). But, the ponding time increased with increasing wood chip amount, and this effect was significant on study variables (R ² = 0.99).     

Geochemistry and Genesis of Iron-apatite Ore in the Khanlogh Deposit, Eastern Cenozoic Quchan-Sabzevar Magmatic Arc, NE Iran

The Khanlogh deposit in the Cenozoic Quchan-Sabzevar magmatic belt, NE Iran, is hosted by Oligocene granodioritic rock. The Khanlogh intrusive body is I-type granitoid of the calc-alkaline series. The orebodies are vein, veinlet, massive, and breccia in shape and occur along the fault zones and fractures within the host rock. Ore minerals dominantly comprise magnetite and apatite associated with epidote, clinopyroxene, calcite, quartz, and chlorite. Apatites of the Khanlogh deposit have a high concentration of REE, and show a strong LREE/HREE ratio with a pronounced negative Eu anomaly. Magnetites have a high concentration of REE and show weak to moderate LREE/HREE fractionation. They are comparable to the REE patterns in Kiruna-type iron ores and show an affinity to calc-alkaline magmas. The Khanlogh deposit is similar in the aspects of host rock lithology, alteration, mineralogy, and mineral chemistry to the Kiruna-type deposits. Field observations, hydrothermal alteration halos, style of mineralization, and the geochemical characteristics of apatite, magnetite, and host rock indicate that these magnetite veins have hydrothermal origin similar to Cenozoic Kiruna-type deposits within the Tarom subzone, NW Iran, and are not related to silica-iron oxide immiscibility, as are the major Precambrian magnetite deposits in central Iran.     

Tracing water resources flows by complementary use of hydrological and water accounting models

Historically, there has been a dispute over water allocation between users and policymakers in Iran's Zayandeh-Roud Basin (ZRB). In this study, we used the “System of Environmental-Economic Accounting for Water” (SEEAW) framework in combination with the hydrologic model “Soil and Water Assessment Tool” (SWAT) to achieve the water balance in ZRB. We used SEEAW to combine a wide range of water-related statistics across stakeholders and SWAT to evaluate the unknown agricultural water use. The SWAT model is calibrated based on the stream flows and crop yields in the basin. The model assess the renewable water of the basin into two components, about 363 and 70 mm as green and blue water, respectively. Also results from the physical water supply and water use tables demonstrates that the agricultural sector uses 78% of the total renewable freshwater, followed by the residential, 16%, and the industrial sector, 6%. The flows of water from source to services in ZRB are traced based on the water supply and water use tables. The flow diagram shows that 8 MCM of industrial reused water was transferred to the agricultural sector, and 137 MCM and 18 MCM of water from the wastewater treatment plants to the agricultural and industrial sectors, respectively. Furthermore, the results show that the index of the basin dependence on groundwater resources is high (61%), the value of water stress is high (0.88) and the dependence of the basin on transboundary water resources is 30%. Therefore, this method is highly beneficial for achieving a conceptual water balance in disputed basins without enough agricultural water uses data.     

Specification and prediction of nickel mobilization using artificial intelligence methods

Groundwater and soil pollution from pyrite oxidation, acid mine drainage generation, and release and transport of toxic metals are common environmental problems associated with the mining industry. Nickel is one toxic metal considered to be a key pollutant in some mining setting; to date, its formation mechanism has not yet been fully evaluated. The goals of this study are 1) to describe the process of nickel mobilization in waste dumps by introducing a novel conceptual model, and 2) to predict nickel concentration using two algorithms, namely the support vector machine (SVM) and the general regression neural network (GRNN). The results obtained from this study have shown that considerable amount of nickel concentration can be arrived into the water flow system during the oxidation of pyrite and subsequent Acid Drainage (AMD) generation. It was concluded that pyrite, water, and oxygen are the most important factors for nickel pollution generation while pH condition, SO₄, HCO₃, TDS, EC, Mg, Fe, Zn, and Cu are measured quantities playing significant role in nickel mobilization. SVM and GRNN have predicted nickel concentration with a high degree of accuracy. Hence, SVM and GRNN can be considered as appropriate tools for environmental risk assessment.     

U–Pb geochronology,Sr–Nd isotopic compositions,geochemistry and petrogenesis of Shah Soltan Ali granitoids,Birjand, Eastern Iran

The Shah Soltan Ali area (SSA) is located in the eastern part of the Lut Block metallogenic province. In this area different types of sub-volcanic intrusions including diorite porphyry, monzonite porphyry and monzodiorite porphyry have intruded into basaltic and andesitic rocks. Zircon U–Pb dating and field observations indicate that intermediate to mafic volcanic rocks (38.9 Ma) are older than subvolcanic units (38.3 Ma). The subvolcanic intrusions show high-K calc-alkaline to shoshonitic affinity and are metaluminous. Based on mineralogy, high values of magnetic susceptibility [(634 to 3208) × 10^?5 SI], and low initial ⁸⁷Sr/⁸⁶Sr ratios, they are classified as belonging to the magnetite-series of oxidant I-type granitoids and are characterized by an enrichment in LREEs relative to HREEs, with negative Nb, Ti, Zr and Eu anomalies. These granitoids are related to volcanic arc (VAG) and were generated in an active continental margin. Low initial ⁸⁷Sr/⁸⁶Sr ratios (0.7043 to 0.7052) and positive εNd values (+1.48 to +3.82) indicate that the parental magma was derived from mantle wedge. Parental magma was probably formed by low degree of partial melting and metasomatized by slab derived fluids. Then assimilation and fractional crystallization processes (AFC) produced the SSA rocks. This magma during the ascent was contaminated with the crustal material.All data suggest that Middle-Late Eocene epoch magmatism in the SSA area, occurred during subduction of Neo-Tethys Ocean in east of Iran (between Afghan and Lut Blocks).     

Improved RMR Rock Mass Classification Using Artificial Intelligence Algorithms

Rock mass classification systems such as rock mass rating (RMR) are very reliable means to provide information about the quality of rocks surrounding a structure as well as to propose suitable support systems for unstable regions. Many correlations have been proposed to relate measured quantities such as wave velocity to rock mass classification systems to limit the associated time and cost of conducting the sampling and mechanical tests conventionally used to calculate RMR values. However, these empirical correlations have been found to be unreliable, as they usually overestimate or underestimate the RMR value. The aim of this paper is to compare the results of RMR classification obtained from the use of empirical correlations versus machine-learning methodologies based on artificial intelligence algorithms. The proposed methods were verified based on two case studies located in northern Iran. Relevance vector regression (RVR) and support vector regression (SVR), as two robust machine-learning methodologies, were used to predict the RMR for tunnel host rocks. RMR values already obtained by sampling and site investigation at one tunnel were taken into account as the output of the artificial networks during training and testing phases. The results reveal that use of empirical correlations overestimates the predicted RMR values. RVR and SVR, however, showed more reliable results, and are therefore suggested for use in RMR classification for design purposes of rock structures.     

A two-step wavelet-based regularization for linear inversion of geophysical data

Regularization methods are used to recover a unique and stable solution in ill-posed geophysical inverse problems. Due to the connection of homogeneous operators that arise in many geophysical inverse problems to the Fourier basis, for these operators classical regularization methods possess some limitations that one may try to circumvent by wavelet techniques.
In this paper, we introduce a two-step wavelet-based regularization method that combines classical regularization methods with wavelet transform to solve ill-posed linear inverse problems in geophysics. The power of the two-step wavelet-based regularization for linear inversion is twofold. First, regularization parameter choice is straightforward; it is obtained from a priori estimate of data variance. Second, in two-step wavelet-based regularization the basis can simultaneously diagonalize both the operator and the prior information about the model to be recovered. The latter is performed by wavelet-vaguelette decomposition using orthogonal symmetric fractional B-spline wavelets.
In the two-step wavelet-based regularization method, at the first step where fully classical tools are used, data is inverted for the Moore-Penrose solution of the problem, which is subsequently used as a preliminary input model for the second step. Also in this step, a model-independent estimate of data variance is made using nonparametric estimation and L-curve analysis. At the second step, wavelet-based regularization is used to partially recover the smoothness properties of the exact model from the oscillatory preliminary model.
We illustrated the efficiency of the method by applying on a synthetic vertical seismic profiling data. The results indicate that a simple non-linear operation of weighting and thresholding of wavelet coefficients can consistently outperform classical linear inverse methods.     

Geometric and kinematic analysis of structural elements along north front of Bagharan Kuh Mountain,NE Iran

At the end of the western part of Bagharan Kuh Mountain in the northeast of Iran, mountain growth has been stopped toward the west because of the stress having been consumed by the thrusting movements and region rising instead of shear movement. Chahkand fault zone is situated at the western part of this mountain; this fault zone includes several thrust sheets that caused upper cretaceous ophiolite rocks up to younger units, peridotite exposure and fault related fold developing in the surface. In transverse perpendicular to the mountain toward the north, reduction in the parameters like faults dip, amount of deformation, peridotite outcrops show faults growth sequence and thrust sheets growth from mountain to plain, thus structural vergence is toward the northeast in this fault zone. Deformation in the east part of the region caused fault propagation fold with axial trend of WNW-ESE that is compatible with trending of fault plane. In the middle part, two types of folds is observed; in the first type, folding occurred before faulting and folds was cut by back thrust activity; in the second type, faults activity caused fault related folds with N60-90W axial trend. In order to hanging wall strain balance, back thrusts have been developed in the middle and western part which caused popup and fault bend folds with N20-70E trend. Back thrusts activity formed footwall synclines, micro folds, foliations, and uplift in this part of the region. Kinematic analysis of faults show stress axis σ₁ = N201.6, 7, σ₂ = N292.6, 7.1, σ₃ = N64.8, 79.5; stress axis obtained by fold analysis confirm that minimum stress (σ₃) is close to vertical so it is compatible with fault analysis. Based on the results, deformation in this region is controlled by compressional stress regime. This stress state is consistent with the direction of convergence between the Arabian and Eurasian plates. Also study of transposition, folded veins, different movements on the fault planes and back thrusts confirm the progressive deformation is dominant in this region that it increases from the east to the west.