The Gol-e-Zard Zn-Pb Deposit,Lorestan Province,Iran: a Metamorphosed SEDEX Deposit

The Gol-e-Zard Zn-Pb deposit is one of several sediment-hosted Zn-Pb deposits found in the central part of the Sanadaj-Sirjan Zone, known as the Isfahan-Malayer belt, western Iran. Mineralization occurs in Upper Triassic to Jurassic phyllites and meta-sandstones. Sphalerite and galena are the most abundant metallic ores, with minor chalcopyrite. Calcite and quartz are the main gangue minerals. Fissure filling, replacement textures and especially mineralized faults, suggest an epigenetic stage in the Gol-e-Zard deposit formation. Geochemical studies of mineralized rocks show high concentrations of Zn, Pb and Cu, (Zn and Pb > 10000 ppm and Cu average 3000 ppm). LREE enrichment (LREE>HREE, La/Lu average 1.44) and positive Eu anomalies (Eu/Eu*>1 average 1.67) indicate reducing conditions during the deposition of deposit. However, some samples do not display negative Ce anomalies, which indicate that localized oxidizing conditions are also present. This study indicates that the Gol-e-Zard deposit formed due to circulating hydrothermal fluids in a marine environment. A SEDEX-type genesis, which is defined by circulating hydrothermal fluids through sediments in a marine environment, and syngenetic precipitation of Zn and Pb sulphides, is suggested for the Gol-e-Zard deposit. Emplacement of some granitoid intrusions such as the Aligudarz granitoid intrusion remobilized mineralizing fluids and metamorphosed the Gol-e-Zard deposit.     

Applying different scenarios for landslide spatial modeling using computational intelligence methods

Landslides every year impose extensive damages to human beings in various parts of the world; therefore, identifying prone areas to landslides for preventive measures is essential. The main purpose of this research is applying different scenarios for landslide susceptibility mapping by means of combination of bivariate statistical (frequency ratio) and computational intelligence methods (random forest and support vector machine) in landslide polygon and point formats. For this purpose, in the first step, a total of 294 landslide locations were determined from various sources such as aerial photographs, satellite images, and field surveys. Landslide inventory was randomly split into a testing dataset 70% (206 landslide locations) for training the different scenarios, and the remaining 30% (88 landslides locations) was used for validation purposes. To providing landslide susceptibility maps, 13 conditioning factors including altitude, slope angle, plan curvature, slope aspect, topographic wetness index, lithology, land use/land cover, distance from rivers, drainage density, distance from fault, distance from roads, convergence index, and annual rainfall are used. Tolerance and the variance inflation factor indices were used for considering multi-collinearity of conditioning factors. Results indicated that the smallest tolerance and highest variance inflation factor were 0.31 and 3.20, respectively. Subsequently, spatial relationship between classes of each landslide conditioning factor and landslides was obtained by frequency ratio (FR) model. Also, importance of the mentioned factors was obtained by random forest (RF) as a machine learning technique. The results showed that according to mean decrease accuracy, factors of altitude, aspect, drainage density, and distance from rivers had the greatest effect on the occurrence of landslide in the study area. Finally, the landslide susceptibility maps were produced by ten scenarios according to different ensembles. The receiver operating characteristics, including the area under the curve (AUC), were used to assess the accuracy of the models. Results of validation of scenarios showed that AUC was varying from 0.668 to 0.749. Also, FR and seed cell area index indicators show a high correlation between the susceptibility classes with the landslide pixels and field observations in all scenarios except scenarios 10_RF and 10_SVM. The results of this study can be used for landslides management and mitigation and development activities such as construction of settlements and infrastructure in the future.     

An evolutionary approach to modelling the thermomechanical behaviour of unsaturated soils

A new data‐mining approach is presented for modelling of the stress–strain and volume change behaviour of unsaturated soils considering temperature effects. The proposed approach is based on the evolutionary polynomial regression (EPR), which unlike some other data‐mining techniques, generates a transparent and structured representation of the behaviour of systems directly from raw experimental (or field) data. The proposed methodology can operate on large quantities of data in order to capture nonlinear and complex relationships between contributing variables. The developed models allow the user to gain a clear insight into the behaviour of the system. Unsaturated triaxial test data from the literature were used for development and verification of EPR models. The developed models were also used (in a coupled manner) to produce the entire stress path of triaxial tests. Comparison of the EPR model predictions with the experimental data revealed the robustness and capability of the proposed methodology in capturing and reproducing the constitutive thermomechanical behaviour of unsaturated soils. More importantly, the capability of the developed models in accurately generalizing the predictions to unseen data cases was illustrated. The results of a sensitivity analysis showed that the models developed from data are able to capture and represent the physical aspects of the unsaturated soil behaviour accurately. The merits and advantages of the proposed methodology are also discussed. Copyright © 2014 John Wiley & Sons, Ltd.     

Hydrothermal alteration and mineralisation of the Glen Eden Mo-W-Sn deposit: a leucogranite-related hydrothermal system,Southern New England Orogen,NSW, Australia

The Glen Eden Mo-Sn-W deposit in north-eastern New South Wales, Australia, is an example of a leucogranite-related, low-grade, large-tonnage hydrothermal system. It occurs in the southern part of the New England Orogen and is hosted within Permian felsic volcanic rocks, intruded at depth by dykes of porphyritic microleucogranite (Glen Eden Granite). The deposit is hosted within a pipe-like quartz-rich greisen breccia body about 500 m in diameter, surrounded by a greisen zone several hundred metres across, zoning out into altered volcanic rocks. The dominant ore minerals, largely hosted as open space fillings and disseminations in quartz and quartz-rich greisen, are molybdenite, wolframite and cassiterite; they are accompanied by minor to trace amounts of muscovite, fluorite, topaz, siderite, pyrrhotite, arsenopyrite, chalcopyrite, sphalerite, bismuth, bismuthinite, joseite A, cosalite, galenobismutite, beryl, anatase and late-stage dickite and kaolinite. Two types of breccia are recognised: (1) greisenised volcanic rock fragments (quartz + muscovite), cemented by hydrothermal quartz ± K-feldspar ± ore minerals, and (2) fragments of hydrothermal quartz ± cassiterite ± wolframite enclosed in quartz ± clay. In both types of breccia and in stockwork veins, there is evidence of early precipitation of Mo-Sn-W phases, followed by Bi minerals and base metal sulfides (± fluorite, siderite).Breccia formation and associated hydrothermal alteration (greisen, potassic, argillic, propylitic) are interpreted to be related to devolatilisation of the highly fractionated Glen Eden Granite of early Triassic age (240±1 Ma based on ⁴⁰Ar/³⁹Ar geochronology of greisen muscovite) as well as to fluid mixing with meteoric waters. The breccia pipe could have formed in part by rock dissolution and collapse, as well as by explosive degassing of boiling fluids. Fluid inclusion evidence is consistent with boiling, with breccia pipe formation and mineralisation having mainly occurred at 250–350 °C from fluids with salinity of 0.4–9 wt% NaCl equivalent in the dilute types and 30–47 wt% NaCl equivalent in the hypersaline types. Stable isotopic evidence (O, D, C, S) indicates a strong magmatic contribution to the hydrothermal fluids and metals in the breccia. The ¹⁸O values of quartz decrease outward from the breccia pipe (10.6–12.3 in the pipe to 3.4–8.7 in the peripheral quartz) indicating that there has been mixing with isotopically light (high latitude) meteoric fluids, mainly after formation of the breccia pipe.     

Assessing the impacts of climate and land use change on streamflow,water quality and suspended sediment in the Kor River Basin,Southwest of Iran

This research addressed the separate and combined impacts of climate and land use change on streamflow, suspended sediment and water quality in the Kor River Basin, Southwest of Iran, using (BASINS–WinHSPF) model. The model was calibrated and validated for hydrology, sediment and water quality for the period 2003–2012. The model was run under two climate changes, two land use changes and four combined change scenarios for near-future period (2020–2049). The results revealed that projected climate change impacts include an increase in streamflow (maximum increases of 52% under RCP 2.6 in December and 170% under RCP 8.5). Projected sediment concentrations under climate change scenarios showed a monthly average decrease of 10%. For land use change scenarios, agricultural development scenario indicated an opposite direction of changes in orthophosphate (increases in all months with an average increase of 6% under agricultural development scenario), leading to the conclusion that land use change is the dominant factor in nutrient concentration changes. Combined impacts results indicated that streamflows in late fall and winter months increased while in summer and early fall decreased. Suspended sediment and orthophosphate concentrations were decreased in all months except for increases in suspended sediment concentrations in September and October and orthophosphate concentrations in late winter and early spring due to the impact of land use change scenarios.     

A new indicator of elastic spectral shape for the reliable selection of ground motion records

How to select a limited number of ground motion records (GMRs) is an important challenge for the non‐linear analysis of structures. Since epsilon (ε_Sa) is an indicator of spectral shape, which has a significant correlation with the non‐linear response of a structure, the selection of GMRs based on the hazard‐related target ε_Sa is a reasonable approach. In this paper, an alternative indicator of spectral shape is proposed, which results in a more reliable prediction of the non‐linear response for the structures with the natural period of 0.25 to 3.0 s. This new parameter, named eta (η), is a linear combination of ε_Sa and the peak ground velocity epsilon (ε_PGV). It is shown that η, as a non‐linear response predictor, is remarkably more efficient than the well‐known and convenient parameter ε_Sa. The influence of η‐filtration in the collapse analysis of an eight‐story reinforced concrete structure with special moment‐resisting frames was studied. Statistical analysis of the results confirmed that the difference between ε‐filtration and η‐filtration can be very significant at some hazard levels. In the case of this structure, the resulting annual frequency of collapse was found to be lower in the case of η‐based record selection, in comparison with the ε‐based record‐selection approach. Copyright © 2011 John Wiley & Sons, Ltd.     

Development of fragility curves by incorporating new spectral shape indicators and a weighted damage index: case study of steel braced frames in the city of Mashhad,Iran

In this study, strong ground motion record(SGMR) selection based on Eta(η) as a spectral shape indicator has been investigated as applied to steel braced frame structures. A probabilistic seismic hazard disaggregation analysis for the definition of the target Epsilon(ε) and the target Eta(η) values at different hazard levels is presented, taking into account appropriately selected SGMR's. Fragility curves are developed for different limit states corresponding to three representative models of typical steel braced frames having significant irregularities in plan, by means of a weighted damage index. The results show that spectral shape indicators have an important effect on the predicted median structural capacities, and also that the parameter η is a more robust predictor of damage than searching for records with appropriate ε values.     

Integration of the MODIS Snow Cover Produced Into Snowmelt Runoff Modeling

Because of the difficulty of monitoring and measuring snow cover in mountainous watersheds, satellite images are used as an alternative to mapping snow cover to replace the ground operations in the watershed. Snow cover is one of the most important data in simulation snowmelt runoff. The daily snow cover maps are received from Moderate Resolution Imaging Spectroradiometer (MODIS), and are used in deriving the snow depletion curve, which is one of the input parameters of the snowmelt runoff model (SRM). Simulating Snowmelt runoff is presented using SRM model as one of the major applications of satellite images processing and extracting snow cover in the Ghara - Chay watershed. The first results of modeling process show that MODIS snow covered area product can be used for simulation and forecast of snowmelt runoff in Ghara - Chay watershed. The studies found that the SCA results were more reliable in the study area.