One main problem in the modeling of mineral deposits is to design a block model that divides the deposit into homogeneous subdomains. The spatial uncertainty in the geological boundaries becomes a critical factor prior to the modeling of the ore properties. For this reason, reducing the uncertainty of geological models leads to an improved mineral resource evaluation. This research work addresses the problem of updating the geological models by using actual online-sensor measurement data. A novel algorithm is provided, which integrates the discrete wavelet transform to the Ensemble Kalman Filter for assimilating online-sensor production data into geological models. The geological realizations in each time step are transformed to frequency coefficients and, after each assimilation step, the updated realizations are back-transformed to the original categorical distribution. Furthermore, a reconciliation process is performed to compare the online-sensor data derived from the production blocks and the updated realizations in each time step. The algorithm is illustrated through an application to the Golgohar iron deposit located in SW of Sirjan, Iran, and proves to reproduce the statistical parameters and connectivity values of the primary geological realizations.
The Multan district is mainly prone to riverine floods but has remained understudied. Chenab flood-2014 was the worst flood that this district experienced in recorded history. This study applies remote sensing (RS) techniques to estimate the extent, calculate duration, assess the major causes and resulting impacts of the flood-2014, using Landsat-8 OLI images. These images were obtained for pre-flood, during-flood and post-flood instances. Secondary data of flood causing factors were obtained for comprehensive analysis. Spatially trained and validated datasets were obtained through Google Earth platform and Global positioning system. The supervised classification with maximum likelihood algorithm was used to classify land use and land cover of the study area. The Modified Normalized Difference Water Index was utilized to detect flood inundation extent and duration, and Normalized Difference Vegetation Index was utilized to monitor vegetation coverage and changes. The analysis allowed us to assess flood causes, and calculate the extent of the flooded areas with duration and recession, as well as damages to standing crops and built-up areas. The results revealed that the flood-2014 occurred due to heavy rains in early September in upper Chenab catchment. The flood inundation continued for around two months, which heavily affected agriculture and built-up areas. The present study introduces practical use of RS techniques to provide basis for effective flood inundation mapping and impact assessment, as an application for early flood response and recovery in the world.
The numerous non-sulfide zinc ore deposits were the historical basis for the development of zinc mining in Iran.They include the Mehdiabad,Irankouh and Angouran world-class deposits,as well as the Zarigan and Haft-har deposits.These deposits were formed by supergene oxidation of primary sulfide minerals during the complex interplay of tectonic uplift,karst development,changes in the level of the water table,and weathering.Zn(Pb)carbonates,Zn-hydrosilicates and associated hydrated phases directly replace the primary ore bodies or fill cavities along fractures related to uplift tectonics.Direct replacement of primary sulfides is accompanied by distal precipitation of zinc non-sulfide minerals in cavities or internal sediments filling.The mineralogy of the non-sulfide mineralization in all six deposits is generally complex and consists of smithsonite,hydrozincite,and hemimorphite as the main economic minerals,accompanied by iron and manganese oxy-hydroxides and residual clays.Commonly,non-sulfide minerals in these deposits consist of two types of ore:red zinc ore(RZO),rich in Zn,Fe,Pb-(As)and white zinc ore(WZO),typically with very high zinc grades but low concentrations of iron and lead.Typical minerals of the RZO are Fe-oxyhydroxides,goethite,hematite,hemimorphite,smithsonite and/or hydrozincite and cerussite.Common minerals of the WZO are smithsonite or hydrozincite and only minor amounts of Fe-oxyhydroxides and hemimorphite. 相似文献
Black shale samples were collected from Chimiari Khyber Pakthunkhawa region of Pakistan and were analyzed for elemental compositions. Atomic Absorption Spectrophotometry (AAS) was utilized for the determination of elements in the digested solutions. The analysis of black shale was performed precisely with relative standard deviation (RSD) lower than 2%. Results showed that the samples contained high concentrations of Ca (11.98 %), Al (7.09%), Fe (3.03%), Mg (0.59%) and Ti (0.58%). 相似文献
The study explored potential of groundwater in the Lower Barpani watershed of Assam, India. Ten site-specific groundwater factors in the watershed were assigned weights through analytical hierarchy process. The weighted factors were integrated to prepare groundwater potential zones in GIS environment. Results revealed that the northern and northwestern parts of the study area have high groundwater potential. Gentle slope, flood plain, monsoon rainfall and location of numerous wetlands were found to be the major factors of high potential of groundwater in these parts. Medium groundwater potential was found in the southern part of the watershed. High drainage density but comparatively steeper slopes, nature of rocks and low water table have made this part of the watershed to have medium potential for groundwater. Low groundwater potential zone was identified mostly in the southwestern parts of the study area. Steep slope, high rate of runoff and low permeability due to hard rocks were found to be the main factors of low groundwater potential in these parts. Validation of groundwater potential zones with water yield revealed a strong positive relationship. Density of population and groundwater potential were positively correlated, and about 93% variation (r2 = 0.937) in density of population is explained by variation in groundwater potential. A linear correlation between groundwater zones and density of population suggests dependence of population on availability of groundwater. The methodology adopted in this study can be used for monitoring groundwater prospects for sustainable development and management of water resources in different geographical regions at various scales. 相似文献
This study presents a method to incorporate uncertainty of climate variables in climate change impact assessments, where the uncertainty being considered refers to the divergence of general circulation model (GCM) projections. The framework assesses how much bias occurs when the uncertainties of climate variables are ignored. The proposed method is based on the second-order expansion of Taylor series, called second-order approximation (SOA). SOA addresses the bias which occurs by assuming the expected value of a function is equal to the function of the expected value of the predictors. This assumption is not valid for nonlinear systems, such as in the case of the relationship of climate variables to streamflow. To investigate the value of SOA in the climate change context, statistical downscaling models for monthly streamflow were set up for six hydrologic reference stations in Australia which cover contrasting hydro-climate regions. It is shown that in all locations SOA makes the largest difference for low flows and changes the overall mean flow by 1–3%. Another advantage of the SOA approach is that the individual contribution of each climate variable to the total difference can be estimated. It is found that geopotential height and specific humidity cause more bias than wind speeds in the downscaling models considered here. 相似文献
This study aimed to (1) investigate microrubbers (MRs) for the first time and identify microplastics (MPs) in street dust, (2) determine the physicochemical and mineralogical characteristics and morphology of dust particles, (3) understand the concentration and the possible source(s) of heavy metals/metalloids, (4) identify the chemical speciation and mobility potential of trace metals in urban street dusts, and (5) determine adverse health effects of street dust on children and adults living in the city of Bushehr in southwestern Iran. Generally, twenty four street dust samples were collected and analyzed. Calculated enrichment factors indicate high levels of contamination. Statistical analysis reveals that the two main sources of trace elements include road traffic emissions (Cu, Zn, Sb, Hg, Pb, Mo) and re-suspended soil particles (Al, Mn, Ni, Ti, Cd, Co). BCR sequential extraction results indicated that As, Zn, Cu, and Pb mainly occur in the exchangeable fraction and hence are highly bioavailable. X-ray powder diffraction analysis revealed the presence of calcite, dolomite, quartz, and magnetite. The size distribution of dust particles was also investigated using a scanning electron microscope (SEM), while elemental distribution was analyzed using an attached energy dispersive X-ray spectrometer (SEM–EDS) unit. Dust particles from heavy traffic areas are much finer compared with other investigated areas. MPs and MRs, mostly fibers and fragments, were detected in all samples [ranging from 210 to 1658 (MPs) and 44 to 782 (MRs) items/10 g dust] using fluorescence microscopy. The hazard index for As is higher than 10?4 for children and adults indicative of high risk. According to the calculated potential ecological risk index, Hg indicated moderate ecological risk in the street dust of the study area. 相似文献
Few approaches exist that explicitly use the uncertainty associated with the spread of climate model simulations in assessing climate change impacts. An approach that does so is second-order approximation (SOA). This incorporates quantification of uncertainty to ascertain its impact on the derived response using a Taylor series expansion of the model. This study uses SOA in a statistical downscaling model of monthly streamflow, with a focus on the influence of dependence in the uncertainty of multiple atmospheric variables. Uncertainty is quantified using the square root error variance concept with a new extension that allows the inter-dependence terms among the atmospheric variable uncertainty to be specified. Applying the model to selected point locations in Australia, it is noted that the downscaling results differ considerably from downscaling that ignores uncertainty. However, when the effects of dependence in uncertainty are incorporated, the results differ according to the regional variations in dependence structure. 相似文献
