Elastoplastic model with loading memory surfaces (LMS) for monotonic and cyclic behaviour of geomaterials

A new elastoplastic model called loading memory surface based on the critical state concept and the multi‐surface framework is proposed for geomaterials. The model uses a hypoelastic formulation and two plastic mechanisms. The formulations of the model are made in three‐dimensional stress–strain space and work under both monotonic and cyclic loadings. A newly introduced formalism makes it possible to obtain the cyclic response directly from the monotonic loading one. This formalism gives a three‐dimensional generalization of the well‐known Masing rule. The model has been validated against test results of Hostun sand under several conditions: monotonic and cyclic, drained and undrained, tests in compression and in extension, and at different confining pressures and different densities. Copyright © 2014 John Wiley & Sons, Ltd.     

Hydrology and geomorphology of the Upper White Nile lakes and their relevance for water resources management in the Nile basin

Remote sensing data and digital elevation models were utilized to extract the catchment hydrological parameters and to delineate storage areas for the Ugandan Equatorial Lakes region. Available rainfall/discharge data are integrated with these morphometric data to construct a hydrological model that simulates the water balance of the different interconnected basins and enables the impact of potential management options to be examined. The total annual discharges of the basins are generally very low (less than 7% of the total annual rainfall). The basin of the shallow (5 m deep) Lake Kioga makes only a minor hydrological contribution compared with other Equatorial Lakes, because most of the overflow from Lake Victoria basin into Lake Kioga is lost by evaporation and evapotranspiration. The discharge from Lake Kioga could be significantly increased by draining the swamps through dredging and deepening certain channel reaches. Development of hydropower dams on the Equatorial Lakes will have an adverse impact on the annual water discharge downstream, including the occasional reduction of flow required for filling up to designed storage capacities and permanently increasing the surface areas of water that is exposed to evaporation. On the basis of modelling studies, alternative sites are proposed for hydropower development and water storage schemes. Copyright © 2012 John Wiley & Sons, Ltd.     

Curve matching approaches to waveform classification: a case study using ICESat data

Light Detection and Ranging (LiDAR) waveforms are being increasingly used in many forest and urban applications, especially for ground feature classification. However, most studies relied on either discretizing waveforms to multiple returns or extracting shape metrics from waveforms. The direct use of the full waveform, which contains the most comprehensive and accurate information has been scarcely explored. We proposed to utilize the complete waveform to test its ability to differentiate between objects having distinct vertical structures using curve matching approaches. Two groups of curve matching approaches were developed by extending methods originally designed for pixel-based hyperspectral image classification and object-based high spatial image classification. The first group is based on measuring the curve similarity between an unknown waveform and a reference waveform, including curve root sum squared differential area (CRSSDA), curve angle mapper (CAM), and Kullback–Leibler (KL) divergence. The second group assesses the curve similarity between an unknown and reference cumulative distribution functions (CDFs) of their waveforms, including cumulative curve root sum squared differential area (CCRSSDA), cumulative curve angle mapper (CCAM), and Kolmogorov–Smirnov (KS) distance. When employed to classify open space, trees, and buildings using ICESat waveform data, KL provided the highest average classification accuracy (87%), closely followed by CCRSSDA and CCAM, and they all significantly outperformed KS, CRSSDA, and CAM based on 15 randomized sample sets.     

Petrography and geochemistry of the Upper Cretaceous Nubia sandstones,Eastern Desert,Egypt: implications for provenance,paleoweathering, and tectonic setting

The provenance of the Upper Cretaceous Nubia sandstones from four vertical sections along Qena-Safaga and Qena-Quseir roads in central Eastern Desert of Egypt was investigated based on their modal composition and geochemical data. The Nubia sandstone samples are abundant in quartz content with low feldspar and lithic fragments. Their average modal composition (Q_94.2F_1.3R_4.5) classifies them as quartz arenites with subordinate quartz wackes which is consistent with geochemistry data. The average CIA, CIW, PIA, and Th/U ratio values revealed that the intensity of weathering in the studied areas was similar, varying from moderate to intensive weathering, and may reflect low-relief and warm humid climatic conditions in the source area. The ICV (<?1) and SiO₂/Al₂O₃ ratio (>?5) indicate that the Nubia sandstones are texturally and mineralogically mature. The petrographical and geochemical analyses suggest that the Nubia sandstones were mainly derived from felsic (granitic) and/or recycled sand sources. The major element-based multidimensional tectonic discrimination diagrams suggested the Nubia sandstones were deposited in a passive continental margin of a syn-rift basin. This result agreed with the general geology of central Eastern Desert of Egypt during the Upper Cretaceous.     

Analysis of physical factors of climate and bioclimate and their effects on almonds production to increase the economy in Hebron area of Palestine

For the 1993–2009 period, we analyzed the relationship between almond yield and three climatic variables (mean annual temperature, soil water reserve, and precipitation), and four bioclimatic variables (annual ombrothermic index, water deficit, simple continentality index, and compensated thermicity index), for one major Hebron crop (soft and hard almonds). Moreover, we obtained data almond production from the Palestinian Central Bureau of Statistics, while the climate data from the Palestinian meteorological station during the study period from 1993 to 2009, and analysis is it by using bioclimatic classification of the Earth of Salvador Rivas-Martinez to study the relationship between the almond yield and climate and bioclimate factors (variables). The climatic and bioclimate variables of greatest importance to almond were used to develop regressions analysis relating yield to climatic conditions. Hebron was positively affected by annual ombrothermic index, simple continentality index, precipitation, water soil reserve, and mean annual temperature, but negatively affected by water deficit, with a large proportion of the variance explained by axis F1 (72.48%), F2 (22.38%), and axes F1and F2 (94. 86%). However, in order to produce a high amount of almonds and quality, it can be grown in the regions of the mesomediterranean region, with the value of annual ombrothemic index more than 3, compensated thermicity index between 220/220 to 350/350, simple continentality index between 14 and 20, and in areas where the average annual temperature is between 15 and 20 °C.