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.     

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.     

Regionalization of potential evapotranspiration using a modified region of influence

Theoretical and Applied Climatology - This study examined the effect of different attributes on regionalization of potential evapotranspiration (ETp) in Urmia Lake Basin (ULB), Iran, using the...     

Using high-resolution satellite imagery to provide a relief priority map after earthquake

After the earthquake occurrence, collecting correct information about the extent of damage is essential for managing critical conditions and allocating limited resources. The prepared building damage maps sometimes bring about waste of time required for rescuing individuals under the rubble by wrongly conducting rescue teams toward regions with a lower rescue priority. In this research, an algorithm based on using a proposed standard at database level was developed to prioritize damaged buildings by considering five key elements of land use type, the degree of damage to buildings, the land use differentiation index, time of the highest population density in each land use, and time of disaster’s incidence. The steps of the proposed method which was implemented in the MATLAB environment include: detecting buildings on the pre- and post-event imagery, implementing texture features for each candidate building, choosing the optimal features by genetic algorithm, determining the degree of building damage in three classes of negligible damage, substantial damage, and heavy damage by using the difference between chosen features as inputs of the designed neurofuzzy inference system. Data collected from field observations were compared to the output obtained from the proposed algorithm. This comparison presented a general accuracy of 88% and Kappa coefficient of 79% in the classification of buildings into three damage classes. The proposed standard then was used for classifying damaged buildings into relief priorities of high, medium, and low. Findings revealed that the relief priority map could be a basis for correct guidance of relief and rescue teams during crucial times following earthquakes.     

Joint inversion of groundwater flow,heat, and solute state variables: a multipurpose approach for characterization and forecast of karst systems

Characterization of karst systems and forecast of their state variables are essential for groundwater management and engineering in karst regions. These objectives can be met by the use of process-based discrete-continuum models (DCMs). However, results of DCMs may suffer from inversion nonuniqueness. It has been demonstrated that the joint inversion of observations regulated by different natural processes can tackle the nonuniqueness issue in groundwater modeling. However, this has not been tested for DCMs thus far. This research proposes a methodology for the joint inversion of hydro-thermo-chemo-graphs, applying to two small-scale sink-to-spring experiments at Freiheit Spring, Minnesota, USA. In order to address conceptual uncertainty, a multimodel approach was implemented, featuring seven mutually exclusive variants. Spring hydro-thermo-chemo-graphs, for all the variants simulated by MODFLOW-CFPv2, were jointly inverted using a weighted least squares algorithm. Subsequently, models were compared in terms of inversion and forecast performances, as well as parameter uncertainties. Results reveal the suitability of the DCM approach for simultaneous inversion and forecast of hydro-physico-chemical behavior of karst systems, even at a scale of meters and seconds. The estimated volume of the tracer conduit passage ranges from approximately 46–51 m³, which is comparable to the estimate from the flood-pulse method. Moreover, it was demonstrated that the thermograph and hydrograph contain more information about aquifer characteristics than the chemograph. However, this finding can be site-specific and should depend on the analysis scale, the considered conceptual models, and the hydrological state, which are potentially affected by minor unaccountable processes and features.