Uncertainty and Reliability Analysis Applied to Slope Stability: A Case Study From Sungun Copper Mine

Nowadays, there are many new methods for slope stability analysis; including probabilistic methods assessing geotechnical uncertainties to develop safety factors. In this paper, a reliability index analysis for the Sungun copper mine slope stability is evaluated based on three methods of uncertainties consisting Taylor series method, Rosenblueth point estimate method and Monte-Carlo simulation method. Sungun copper mine will be one of the Iran’s biggest mines with final pit’s height of 700 meters. For this study two of its main slopes were assessed, one dipping to the NE (030) and the other to the SE (140). Probability density function of cohesion and angle of friction for the slopes were developed using limit equilibrium methods. These shear strengths were then used to determine the probability density function of safety factor and reliability index using the probabilistic methods. Results of the probabilistic analysis indicate that with ascending values of the uncertainties the reliability index decreases. Furthermore, it was determined that with the Monte Carlo simulation the seed number used has little effect on the reliability index of the safety factor especially with seed numbers in excess of 1200. Variations in the overall reliability index of safety factor were observed between the two slopes and this difference is explained by the differences in complexities of the geology within the cross-section.     

Prediction of climate change in Brunei Darussalam using statistical downscaling model

Theoretical and Applied Climatology - Climate is changing and evidence suggests that the impact of climate change would influence our everyday lives, including agriculture, built environment,...     

Application of the strain energy to estimate the rock load in squeezing ground condition of Eamzade Hashem tunnel in Iran

Estimation of rock load is a very important issue because the selection of a support system is highly related to this parameter. Several methods are used to estimate this parameter such as experimental, empirical, and numerical methods. This study propose a new empirical method to estimate the rock load in squeezing ground condition using actual collapses data of Emamzade Hashem tunnel of Iran based on the ration of the post-failure residual strain energy to the pre-failure stored strain energy. Prediction of squeezing ground condition in this study is performed based on Jethwa, Singh, and Hoek criterions. Results show that some sections in shale and sandstone of the Shemshak formation are prone to squeezing. Finally, the relation between the rock load and the ratio of the post-failure residual strain energy to the pre-failure stored strain energy, Ψ, in squeezing ground condition is estimated. Based on the statistical analysis, the maximum correlation between both parameters is achieved when Alejano’s equations are used to estimate the drop modulus. As the rock mass behavior changes from elastic–plastic to elastic–brittle, the drop modulus changes from 0 to infinite. The reason is that by increasing the quality of rock mass and reducing the minimum principal stresses, the ratio of post-failure residual strain energy to pre-failure stored strain energy and rock load height (H _p) reduce. So, regression analysis is used to investigate the relation between the rock load height and the ratio of post-failure residual strain energy to pre-failure stored strain energy, and finally, a formulation is presented to determine rock load height based on power function.     

Assessment of heavy metal contamination in the surficial sediments from the lower Meghna River estuary,Noakhali coast,Bangladesh

Sediment samples were collected from ten selected sites of the lower Meghna River estuary,and six heavy metals were analyzed with Atomic Absorption Spectrophotometry(AAS)to assess the contamination level and the metals’association with sediment grain size.The current results revealed that the mean concentrations of the studied metals were ranked in descending order of iron(Fe)(1.29×103 mg/kg)>zinc(Zn)(42.41 mg/kg)>lead(Pb)(12.48 mg/kg)>chromium(Cr)(10.59 mg/kg)>copper(Cu)(6.22 mg/kg)>cadmium(Cd)(0.28 mg/kg).The geo-accumulation,contamination,and pollution load indexes suggested that the lower Meghna river estuary was not contaminated by Fe,Zn,Pb,Cr,and Cu.The mean size of the sediment ranged from 28.92 to 126.2 mm,and the Pearson correlation coefficient showed a significant association between Fe and Pb(coefficient of determination,r2=0.836;p<0.05),and no significant correlation was found between individual metals and grain size,indicating no or low influence on the metals distribution.     

Life cycle greenhouse gas footprint of shale gas: a probabilistic approach

With the increase in natural gas (NG) production in recent years, primarily from shale gas, some sources, including the US Environmental Protection Agency (EPA), have suggested that upstream methane emissions are increasing. Much of the recent controversy has centered on emissions during well drilling, testing, and completion even though emissions downstream of the wellhead are also of concern. The study critically assessed the current state of knowledge about the life cycle GHG footprint of NG, analyzed the assumptions, data and analysis methodologies used in the existing literature. This study comprehensively analyzed the emission of methane from different stage of the life of well for conventional and unconventional NG using the EPA’s revised 2011 estimates as well as other existing literature and publicly available government data. The study proposed a probabilistic model to estimate the range of total GHG footprint of NG with varying probabilities. Through the bottom up approach starting from the well construction to the delivery of NG to the small user and using Monte Carlo simulation, the study identified the critical sources of fugitive emissions from the NG. As expected, emissions from well completion and periodic emissions (e.g. liquid unloading in the case of onshore conventional wells and workovers in the case of unconventional wells) are significant contributors to the overall GHG footprint of NG, and possess large opportunity for reduction. Finally the application of probabilistic model is demonstrated through a case study using the data from the Montney and Horn River shale gas basins in the Northern British Columbia to estimate the range of total GHG footprint of shale gas with varying probabilities. The study found that the GHG footprint of Montney and Horn River wells are much smaller than that of Barnett shale (which is representative of US shale gas) due to strict flaring regulations followed in BC. The study also undercuts the outcome of Howarth et al. (Clim Chang Lett 106:679–690, 2011), which states that the GHG footprint of shale gas is at least 20 % greater than coal.     

Climate change and water resources in the Bagmati River Basin,Nepal

This paper characterizes potential hydrological impact of future climate in the Bagmati River Basin, Nepal. For this research, basinwide future hydrology is simulated by using downscaled temperature and precipitation outputs from the Hadley Centre Coupled Model, version 3 (HadCM3), and the Hydrologic Engineering Center's Hydrologic Modeling System (HEC-HMS). It is predicted that temperature may rise maximally during the summer rather than winter for both A2 and B2 Special Report on Emissions Scenarios (SRES) scenarios. Precipitation may increase during the wet season, but it may decrease during other seasons for A2 scenario. For B2 scenario, precipitation may increase during all the seasons. Under the A2 scenario, premonsoon water availability may decrease more in the upper than the middle basin. During monsoons, both upper and middle basins show increased water availability. During the postmonsoon season, water availability may decrease in the upper part, while the middle part shows a mixed trend. Under the B2 scenario, water availability is expected to increase in the entire basin. The analysis of the projected hydrologic impact of climate change is expected to support informed decision-making for sustainable water management.     

Remote sensing-based geostatistical hot spot analysis of Urban Heat Islands in Dhaka,Bangladesh

Urban Heat Island (UHI) refers to a phenomenon whereby urban areas experience higher temperatures compared to the surrounding areas. Remote sensing-based Land Surface Temperature (LST) measurements can be utilized to measure UHI. This study emphasized on geostatistical remote sensing-based hot spot analysis ($G_i^{*}$) of UHI in Dhaka, Bangladesh as a way of examining the influences of Land Use Land Cover (LULC) on UHI from 1991 to 2015. Landsat 5 and 7 satellite-based remote sensing indices were used to explore LULC, UHI and environmental footprints during the study period. The Urban Compactness Ratio (C_oR) was used to calculate the urban form and augmented characteristics. The Surface Urban Heat Island (SUHI) intensity (ΔT) was also used to explore the effects of UHI on the surrounding marginal area. Based on our investigations into LULC, we discovered that around 71.34 per cent of water bodies and 71.82 percent of vegetation cover decreased from 1991 to 2015 in Dhaka city. Contrastingly, according to C_oR readings, 174.13 km² of urban areas expanded by 249.77 per cent. Our hot spot analysis also revealed that there was a 93.73 per cent increase in hot concentration zones. Furthermore, the average temperature of the study area had increased by 3.26°C. We hope that the methods and results of this study can contribute to further research on urban climate.