Probabilistic seismic hazard analysis and spectral accelerations for United Arab Emirates

In recent years, the United Arab Emirates (UAE) has experienced an unprecedented growth which is coupled with the increase in seismic activity in the surroundings. Previous studies presents significant variations in their results whereas some recent studies although very detailed focus on only few cities. This study reviews the results of previous studies and presents new findings for the whole of UAE based on the improved source model and use of next generation attenuation (NGA) equations. The peak ground accelerations, spectral accelerations and deaggregation of hazard for major cities are presented. Moreover, the breakdown of the range of mapped spectral accelerations (S _0.2 and S ₁) is proposed to form the basis for the development of site amplification factors in subsequent studies. The results of this study indicate almost similar values of ground motion compared to some recently published studies and smaller values compared to some earlier studies.     

Empirical constraints for the magnitude and composition of galactic winds

Galactic winds are a key physical mechanism for understanding galaxy formation and evolution, yet empirical and theoretical constraints for the character of winds are limited and discrepant. Recent empirical models find that local star-forming galaxies have a deficit of oxygen that scales with galaxy stellar mass. The oxygen deficit provides unique empirical constraints on the magnitude of mass loss, composition of outflowing material and metal reaccretion onto galaxies. We formulate the oxygen deficit constraints so they may be easily implemented into theoretical models of galaxy evolution. We parameterize an effective metal loading factor which combines the uncertainties of metal outflows and metal reaccretion into a single function of galaxy virial velocity. We determine the effective metal loading factor by forward-fitting the oxygen deficit. The effective metal loading factor we derive has important implications for the implementation of mass loss in models of galaxy evolution.     

Correlations between SPT,CPT, and Vs for Reclaimed Lands near Dubai

Geotechnical and Geological Engineering - Artificial islands near Dubai were constructed with geomaterials of significant gravel content from other areas of the United Arab Emirates (UAE). The...     

Stepwise,earthquake-driven coastal subsidence in the Ganges–Brahmaputra Delta (Sundarbans) since the eighth century deduced from submerged in situ kiln and mangrove remnants

Natural Hazards - This study reconstructs the coastal subsidence over the past 1300 years in a mangrove region along the coast of the Ganges–Brahmaputra Delta, an area not affected...     

A wavelet based approach for combining the outputs of different rainfall–runoff models

The rainfall–runoff modelling being a stochastic process in nature is dependent on various climatological variables and catchment characteristics and therefore numerous hydrological models have been developed to simulate this complex process. One approach to modelling this complex non-linear rainfall–runoff process is to combine the outputs of various models to get more accurate and reliable results. This multi-model combination approach relies on the fact that various models capture different features of the data, and hence combination of these features would yield better result. This study for the first time presented a novel wavelet based combination approach for estimating combined runoff The simulated daily output (Runoff) of five selected conventional rainfall–runoff models from seven different catchments located in different parts of the world was used in current study for estimating combined runoff for each time period. Five selected rainfall–runoff models used in this study included four data driven models, namely, the simple linear model, the linear perturbation model, the linearly varying variable gain factor model, the constrained linear systems with a single threshold and one conceptual model, namely, the soil moisture accounting and routing model. The multilayer perceptron neural network method was used to develop combined wavelet coupled models to evaluate the effect of wavelet transformation (WT). The performance of the developed wavelet coupled combination models was compared with their counterpart simple combination models developed without WT. It was concluded that the presented wavelet coupled combination approach outperformed the existing approaches of combining different models without applying input WT. The study also recommended that different models in a combination approach should be selected on the basis of their individual performance.