Modelling of Soil Degradation in Semi-arid Area Using Remote Sensing and GIS Techniques,Southern Jordan As Case Study

Doklady Earth Sciences - This research dealt with the topic of modeling the soil lost in a semi-arid desert area in the Ma’an watershed and its surroundings in Ma’an Governorate using...     

Development of a Compressibility Prediction Model Based on Soil Index Properties and Area Under/Bounded by Consolidation and Rebound Curves

Geotechnical and Geological Engineering - In any geotechnical design, knowing the magnitude of the compression of the loaded soil layer is essential. This can be achieved by determining the value...     

Volatility modeling of rainfall time series

Networks of rain gauges can provide a better insight into the spatial and temporal variability of rainfall, but they tend to be too widely spaced for accurate estimates. A way to estimate the spatial variability of rainfall between gauge points is to interpolate between them. This paper evaluates the spatial autocorrelation of rainfall data in some locations in Peninsular Malaysia using geostatistical technique. The results give an insight on the spatial variability of rainfall in the area, as such, two rain gauges were selected for an in-depth study of the temporal dependence of the rainfall data-generating process. It could be shown that rainfall data are affected by nonlinear characteristics of the variance often referred to as variance clustering or volatility, where large changes tend to follow large changes and small changes tend to follow small changes. The autocorrelation structure of the residuals and the squared residuals derived from autoregressive integrated moving average (ARIMA) models were inspected, the residuals are uncorrelated but the squared residuals show autocorrelation, and the Ljung–Box test confirmed the results. A test based on the Lagrange multiplier principle was applied to the squared residuals from the ARIMA models. The results of this auxiliary test show a clear evidence to reject the null hypothesis of no autoregressive conditional heteroskedasticity (ARCH) effect. Hence, it indicates that generalized ARCH (GARCH) modeling is necessary. An ARIMA error model is proposed to capture the mean behavior and a GARCH model for modeling heteroskedasticity (variance behavior) of the residuals from the ARIMA model. Therefore, the composite ARIMA–GARCH model captures the dynamics of daily rainfall in the study area. On the other hand, seasonal ARIMA model became a suitable model for the monthly average rainfall series of the same locations treated.     

Pan African layered diorite-tonalite-granodiorite from Sinai massif: an open system fractionation at a subduction zone

This paper reports on the occurrence of layered Pan African dioritetonalite-granodiorite (DTG) rocks. The layering is marked by alternation of melanocratic (M) layers (diorites and tonalites) and leucocratic (L) layers (tonalites and granodiorites). M-samples have cumulus biotite+hornblende+relict pyroxene+plagioclase+K-feldspars+magnetite+apatite, and have transitional calc-alkaline and metaluminous affinities. They were derived from subduction-related magma enriched in Rb, Ba, K and LREE and depleted in Sr and Nb. L-samples have cumulus plagioclase+hornblende. They are enriched in Sr and depleted in Rb, Ba, K, Nb and LREE. They have calc-alkaline and peraluminous affinites.
The formation of the rhythmic layers of DTG composition can be attributed to periodical replenishment of pulses of basic magma into a more evolved acidic magma chamber under open system conditions. Field relations, mineralogy and element concentration among the M- and L-layers indicate that at the subduction zone, the ascending magma was contaminated with lower crustal materials (marginal basin metasediments) which led to LILE-enrichment, Nb-depletion and transition from calc-alkaline to alkaline and from metaluminous to peraluminous affinities as well.     

Study of the Messinian carbonate-evaporite lithofacies offshore Western Libya

This study represents a preliminary investigation of the late Messinian subsurface Marsa Zouaghah Formation in the Western Libyan Offshore, Central Mediterranean Sea. The formation was deposited in three major environmental settings: (a) Marginal Sabkha; (b) Open Lagoon; and (c) Hypersaline Lagoon. The marginal sabkha and open lagoonal settings are locally interrupted by intertidal oolitic shoal deposits. The marginal sabkha facies is replaced in central parts of the Libyan offshore by a narrow zone of aeolian-fluvial facies, the distribution and thickness of which is entirely controlled by a local uplift, the Tripoli Nose'. The marginal sabkha facies broadly defines the late Messinian palaeoshoreline lying parallel to, and north of, the E-W Jifarah fault system which dominated the southern part of the Libyan offshore. This fades is, thus, interpreted as being structurally controlled by fault systems. The hypersaline lagoonal facies is developed in areas of relatively higher rates of subsidence than that of adjacent facies belts. It is therefore, related to restriction formed by continuous subsidence and evaporation. The Marsa Zouaghah Formation constitutes saltern evaporates deposited over a wide platform in sabkha and lagoonal settings, forming part of the 'basin-wide-evaporites' of the Mediterranean Basin deposited during the Messinian salinity crisis. The evaporites formed during a major relative sea-level fall within a subsiding basin situated on the northern continental margin of the African plate. Local, vertical and lateral variations in lithofacies and thickness within the Messinian deposits of the north-west Libyan offshore were controlled by contemporaneous strike-slip movements in addition to sea-level change.     

Interpreting rural change in Malaysia

Relatively little in the literature on rural change in Southeast Asia engages with Malaysia, where the population is becoming urban‐based more rapidly than in many countries in the region. The literature on change in rural Malaysia during the past 40 years, supplemented by our own research, is used to identify key features of such change, which are considered in the context of existing interpretations to arrive at deeper understandings of rural change. Existing conceptualizations of rural change, it is suggested, must account for the diversity of roles taken by individuals daily, seasonally and at different life stages, as well as in multiple locations. Further attention needs to be paid to gender, generation and class among those experiencing change. Processes of rural (and urban) changes will continue and their complexity will reflect cultural and technological evolutions that affect individuals, households and communities throughout the world.     

Fitting optimum order of Markov chain models for daily rainfall occurrences in Peninsular Malaysia

The analysis of the daily rainfall occurrence behavior is becoming more important, particularly in water-related sectors. Many studies have identified a more comprehensive pattern of the daily rainfall behavior based on the Markov chain models. One of the aims in fitting the Markov chain models of various orders to the daily rainfall occurrence is to determine the optimum order. In this study, the optimum order of the Markov chain models for a 5-day sequence will be examined in each of the 18 rainfall stations in Peninsular Malaysia, which have been selected based on the availability of the data, using the Akaike’s (AIC) and Bayesian information criteria (BIC). The identification of the most appropriate order in describing the distribution of the wet (dry) spells for each of the rainfall stations is obtained using the Kolmogorov-Smirnov goodness-of-fit test. It is found that the optimum order varies according to the levels of threshold used (e.g., either 0.1 or 10.0 mm), the locations of the region and the types of monsoon seasons. At most stations, the Markov chain models of a higher order are found to be optimum for rainfall occurrence during the northeast monsoon season for both levels of threshold. However, it is generally found that regardless of the monsoon seasons, the first-order model is optimum for the northwestern and eastern regions of the peninsula when the level of thresholds of 10.0 mm is considered. The analysis indicates that the first order of the Markov chain model is found to be most appropriate for describing the distribution of wet spells, whereas the higher-order models are found to be adequate for the dry spells in most of the rainfall stations for both threshold levels and monsoon seasons.