Shigar valley gemstones,their chemical composition and origin,Skardu, Gilgit-Baltistan,Pakistan

A variety of gemstones is being mined in the Shigar valley, Skardu, Pakistan. These include beryl (goshenite and aquamarine), tourmaline (schorl), garnet (almandine–spessartine), apatite, topaz, fluorite, zoisite, clinozoisite, and axinite, mostly occurring in complex or zoned pegmatites and metamorphic rocks. These have been analyzed using electron probe micro-analyzer and X-ray diffractometer. The mineral chemistry of each gemstone is similar to its respective typical gemstone variety with homogenous chemical composition. Field and chemical characteristics suggest that beryl, tourmaline, garnet, apatite, topaz, and fluorite are occurring in zoned pegmatites which are largely formed by magmatic hydrothermal fluids in the cavities and vugs within the intermediate zone. However, zoisite, clinozoisite, and axinite may have a metamorphic and/or metasomatic origin.     

Estimation and validation of atmospheric water vapor content using a MODIS NIR band ratio technique based on AIRS water vapor products

Atmospheric water vapor validation needs simultaneous, well-defined, and independent information which are not easily available causing limitations in the development of remote sensing water vapor retrieval algorithms. This study is concerned with the retrieval of total atmospheric water vapor content and its validation. A band ratio method has been used to estimate the water vapor content based on Moderate Resolution Imaging Spectroradiometer (MODIS) Near InfraRed (NIR) data. The method uses MODIS bands 17, 18, and 19 as NIR bands and band 2 to remove the land cover reflectance. Furthermore, the Atmospheric Infrared Sounder (AIRS) has been used for both algorithm development and analysis of the results. The method has been modified to take into account the dry condition of the central parts of Iran. Using some various datasets, the method is implemented and evaluated quantitatively. The validation of the water vapor estimates has been undertaken by an analysis of AIRS data. The validation results shows error as low as 9 % for the estimated water vapor using the MODIS NIR band ratio method.     

Investigation of Failed Slopes Based on a New Method of Back Analysis in Rock Masses: A Case Study

Geotechnical and Geological Engineering - Small variation in shear strength parameters results in remarkable changes in the safety factor (SF) of a rock slope. In this regard, rock mass strength of...     

Time independent seismic hazard analysis in Alborz and surrounding area

The Bayesian probability estimation seems to have efficiencies that make it suitable for calculating different parameters of seismicity. Generally this method is able to combine prior information on seismicity while at the same time including statistical uncertainty associated with the estimation of the parameters used to quantify seismicity, in addition to the probabilistic uncertainties associated with the inherent randomness of earthquake occurrence. In this article a time-independent Bayesian approach, which yields the probability that a certain cut-off magnitude will be exceeded at certain time intervals is examined for the region of Alborz, Iran, in order to consider the following consequences for the city of Tehran. This area is located within the Alpine-Himalayan active mountain belt. Many active faults affect the Alborz, most of which are parallel to the range and accommodate the present day oblique convergence across it. Tehran, the capital of Iran, with millions of inhabitants is located near the foothills of the southern Central Alborz. This region has been affected several times by historical and recent earthquakes that confirm the importance of seismic hazard assessment through it. As the first step in this study an updated earthquake catalog is compiled for the Alborz. Then, by assuming a Poisson distribution for the number of earthquakes which occur at a certain time interval, the probabilistic earthquake occurrence is computed by the Bayesian approach. The highest probabilities are found for zone AA and the lowest probabilities for zones KD and CA, meanwhile the overall probability is high.     

Diagenetic evolution vis-a-vis reservoir characteristics of Dhosa sandstones,Ler dome,Kachchh, western India

The detrital mineralogy as well as diagenetic characters of the Dhosa Sandstone Member of Chari Formation exposed at the Lerdome, south of Bhuj was studied. In order to assess the potential of the Dhosa Sandstone as a reservoir, it is substantial to understand the diagenetic processes that are controlled largely by post-depositional cementation and compaction in addition to framework composition and original depositional textures. The petrologic analysis of 33 thin sections was carried out to discern primary composition and diagenetic features including primary and secondary porosity patterns. Monocrystalline quartz dominates the detrital mineralogy followed by polycrystalline quartz. Among the polycrystalline variety recrystallized metamorphic quartz surpasses stretched metamorphic quartz in terms of abundance. Feldspars comprise microcline and plagioclase where the former is dominant over the latter. Orthoclase too comprises a very small percentage. Mica, chert, rock fragments, and heavies form the remaining detrital constituent in descending order of their constituent percentage. The diagenetic precipitates are mainly carbonate (8.30%) and iron (7.80%) followed by clay (0.66%) and silica (0.88%) that are minor constituent of the total cementing material. The main paragenetic events identified are early cementation, mechanical compaction, late cementation, dissolution, and authigenesis of clays. The overall reservoir quality seems to be controlled by compaction and authigenic carbonate cementation. The minus cement porosity average 29.4%. The porosity loss due to compaction is 21.92% and by cementation is 29.71%. The loss of original porosity was due to early cementation followed by moderate mechanical compaction during shallow burial. Preservation of available miniscule primary porosity was ascribed to dissolution of carbonates and quartz overgrowth which resisted chemical compaction during deep burial. The studied sandstones may have low reservoir quality owing to existing porosity of less than 9%. More carbonate dissolution and its transformation in dolomite in sub-surface condition and macro-fracture porosity may result in enhanced secondary porosity and good diagenetic traps.     

Petrogenesis and tectonic association of rift-related basic Panjal dykes from the northern Indian plate,North-Western Pakistan: evidence of high-Ti basalts analogous to dykes from Tibet

Mineralogy and Petrology - Rift related magmatism during Permian time in the northern margin of Indian plate is represented by basic dykes in several Himalayan terranes including north western...     

A new empirical equation for predicting the maximum initial amplitude of submarine landslide-generated waves

Landslides - The accurate prediction of landslide tsunami amplitudes has been a challenging task given large uncertainties associated with landslide parameters and often the lack of enough...     

Microbiostratigraphy of Kazhdumi Formation in the Northwestern Shiraz (Southwest Iran) on the Basis of Foraminifera and Calcareous Algae

The middle Cretaceous Kazhdumi Formation,with a thickness of 222 m,belongs to the Bangestan Group and occurs in the Zagros folded zone in southwest Iran.The lower boundary with the Dariyan Formation is disconformable,which is recognized by iron oxides and glauconite.The recognized microfossils are Valvulammina sp.,Scandonea sp.,Daxia cenomana,Choffatela sp., Pseudolituonella reicheli and calcareous algae-Lithocodium aggregation(which belongs to the Sarvak Formation),representing the beginning of Cenomani...     

Support vector machines and feed-forward neural networks for spatial modeling of groundwater qualitative parameters

The present study attempts to model the spatial variability of three groundwater qualitative parameters in Guilan Province, northern Iran, using artificial neural networks (ANNs) and support vector machines (SVMs). Data collected from 140 observation wells for the years 2002–2014 were used. Five variables, X and Y coordinates of the observation well, distance of the observation well from the shoreline, areal average 6-month rainfall depth, and groundwater level at the day of water quality sampling, were considered as primary input variables. In addition, nine qualitative variables were also considered as auxiliary input variables. Electrical conductivity (EC), sodium concentration (Na⁺), and sulfate concentration (SO₄ ^2?) of the groundwater in the region were estimated using ANNs and SVMs with different input combinations. The results showed that both ANNs and SVMs work well when the only primary input variable is the well location. The ANN yielded an RMSE of 1.03 mEq/l for SO₄ ^2?, 1.05 mEq/l for Na⁺, and 203.17 μS/cm for EC, using the X and Y coordinates of the observation wells in the study area. In the case of SVM, these values were, respectively, 0.87, 0.87, and 176.68. Considering the auxiliary input variables (pH, EC, and the concentrations of Na⁺, K⁺, Ca²⁺, Mg²⁺, Cl^?, SO₄ ^2?, and HCO₃ ^?) resulted in a significant decrease in the RMSE of both ANNs (0.22, 0.30, and 33.04) and SVMs (0.26, 0.34, and 36.23). Comparing these RMSE values with those of cokriging interpolation technique (0.59, 0.98, and 177.59) indicated that ANNs and SVMs produced more accurate estimates of the three qualitative parameters. The relative importance of auxiliary input variables was also determined using Gamma test. The output uncertainty of ANNs and SVMs were determined using p-factor and d-factor. The results showed that SVMs have less uncertainty than ANNs.