Vulnerability of Kuwait coast to sea level rise

Assessing coastal vulnerability to sea level rise (SLR) at local and regional scales is a fundamental step for designing successful long-term coastal management plans. This study was thus designed to assess Kuwait coastal vulnerability to SLR at four scenarios (.5, 1, 1.5 and 2 m). Potential inundated areas and the number of people at risk were estimated based on these SLR scenarios. A coastal vulnerability index (CVI) map of Kuwait was then computed based on the lowest scenario using eight parameters: elevation, coastal slope, geomorphology, distance to 20-m isobath, population, land use, cultural heritage and transportation. The geographic distribution of inundated areas at an SLR of .5 m revealed that the northern islands of Kuwait and coastal areas along Kuwait Bay would be highly impacted, whereas the coastal area near Shuaibah Port was the most influenced among the southern coasts. Most of the coastal area exhibited a moderate vulnerability to SLR, especially the northern islands. This study presented an initial vulnerability assessment for Kuwait coasts to SLR, which can be extended with more variables. The integrated remote sensing and geographic information system methodology demonstrated in this study can be applied in similar studies elsewhere.     

Analysis of soil nail walls performance - Case study

This study surveys the performance of temporary soil nail walls with a maximum height of 29.3 m in the Yas project, located in Tehran. Some numerical models, with various modelling approaches, were developed using finite element software and the proper modelling approaches were specified and verified.The modelling results were analysed and compared with the in situ monitored data. The results demonstrate the model’s horizontal deformations are generally greater than the in situ monitored values. To decrease the differences between models and monitored results, the effect of variations of the soil parameters had been surveyed and the limits of needed variations were specified.     

Prediction of ground vibration due to quarry blasting based on gene expression programming: a new model for peak particle velocity prediction

Blasting is a widely used technique for rock fragmentation in opencast mines and tunneling projects. Ground vibration is one of the most environmental effects produced by blasting operation. Therefore, the proper prediction of blast-induced ground vibrations is essential to identify safety area of blasting. This paper presents a predictive model based on gene expression programming (GEP) for estimating ground vibration produced by blasting operations conducted in a granite quarry, Malaysia. To achieve this aim, a total number of 102 blasting operations were investigated and relevant blasting parameters were measured. Furthermore, the most influential parameters on ground vibration, i.e., burden-to-spacing ratio, hole depth, stemming, powder factor, maximum charge per delay, and the distance from the blast face were considered and utilized to construct the GEP model. In order to show the capability of GEP model in estimating ground vibration, nonlinear multiple regression (NLMR) technique was also performed using the same datasets. The results demonstrated that the proposed model is able to predict blast-induced ground vibration more accurately than other developed technique. Coefficient of determination values of 0.914 and 0.874 for training and testing datasets of GEP model, respectively show superiority of this model in predicting ground vibration, while these values were obtained as 0.829 and 0.790 for NLMR model.     

Reflectance spectroscopy and remote sensing data for finding sulfide-bearing alteration zones and mapping geology in Gilgit-Baltistan,Pakistan

Gilgit-Baltistan region is covering the northern most part of Pakistan where the rocks of the Kohistan-Ladakh island arc and Karakoram plate are exposed. The area has greater potential for precious and base metals deposits which are needed to be explored through spectroscopy and remote sensing techniques. Minerals and rocks can nowadays be identified through the measurement of their absorption and reflectance features by spectroscopic analysis. Spectral reflectance analysis is also very important in selecting the appropriate spectral bands for remote-sensing data analysis of unknown or inaccessible areas. In this study, reflectance spectra in the spectral range of 0.35–2.5 μm of different types of unaltered and altered rocks found in the Machulu and Astor areas of northern Pakistan were obtained using an ASD spectroradiometer. The fresh rock samples showed low spectral reflectance as compared to the altered rock samples. The minerals jarosite, goethite, and hematite showed depth of absorption minima in the range of 0.4–1.15 μm due to the presence of iron (Fe), while jarosite and limonite showed absorption depth at 2.2 μm due to the presence of hydroxyl ions (OH^¯). The clay minerals montmorillonite and illite showed absorption depth at 1.93 and 2.1 μm, respectively. Muscovite showed depth of absorption minima at 1.4 and 1.9 μm in some samples. Calcite showed deep absorption minima at 2.32 μm, while anorthite showed absorption features at 1.4, 1.9, 2.24, and 2.33 μm. Olivine showed a slight depressed absorption feature at 1.07 μm. The copper-bearing phases malachite, chrysocolla, and azurite showed, respectively, a broad absorption feature in the range of 0.6–0.9 μm, a small absorption at 1.4 μm, and a deep absorption at 1.93 μm. The unmineralized samples exhibited high reflectance in the wavelength ranges of 0.6–0.8, 1.6–1.9, 2.0–2.3, 2.1–2.25, and 2.4–2.5 μm, respectively, while the mineralized samples showed reflectance bands in the wavelength ranges of 0.4–0.6, 1.3–1.8, and 2.1–2.2 μm. On this basis, the band ratio combinations 7/5–4/3–6/3 and 7/5–6/3–4/3 of Landsat 8 and 4/7–4/3–2/1 for ASTER data were found to be very effective in the lithological differentiation of major rock units.