Seasonal Changes in Mayfly Communities and Abundance in Relation to Water Physicochemistry in Two Rivers at Different Elevations in Northern Peninsular Malaysia

A field study was performed at rivers in Gunung Jerai forest reserve(Kedah,Malaysia) to assess seasonal changes in mayfly community structure and abundance in relation to altitude and water physicochemistry.Rivers at lower(Batu Hampar River) and higher(Teroi River) elevations were visited through dry and wet seasons in September 2007 to August 2008.Monthly visits were made to 20 sites on each river,and water and aquatic insects were sampled using D-pond aquatic nets.Water was warmer,more acid,and more turbid in Teroi River during wet season.Ammonia was the only nutrient exhibiting significant seasonal variations(greater during wet season).Chemical oxygen demand content was higher in Teroi River where biochemical oxygen demand content was low during wet season.Species richness was higher in Batu Hampar River,but displayed seasonal variations only in Teroi River.Among the eight families encountered,Baetidae was the commonest.Baetid abundance was usually high during wet season,and those belonging to the dominant genus(Baetis) were more abundant in Teroi River.Heptageniidae was the second commonest family;its predominant genus,Thalerospyrus was more abundant in Teroi River during dry season.Caenidae,Leptophlebiidae and Oligoneuriidae were only found in Batu Hampar River where their abundances peaked during dry season,i.e.,Habrophlebiodes sp.and Isonychia sp.Ephemerellidae and Teloganodidae occurred only in Teroi River,with the first found only during dry season.Mayflies were recorded under very distinct physicochemical conditions,illustrating their potential usefulness for assessing water quality.Caenids,leptophlebids,oligoneurids ephemerellids and teloganodids seem to be particularly sensitive to temperature,acidity,turbidity,chemical oxygen demand and biochemical oxygen demand,parameters that varied with river altitude.     

Hydrothermal alteration and evolution of Zr-Th-U-REE mineralization in the microgranite of Wadi Ras Abda,North Eastern Desert,Egypt

Ras Abda plutonic suite, North Eastern Desert of Egypt, consists predominantly of Neoproterozoic calc-alkaline older granites. Minor exposures of pink microgranite are occurring along Wadi Ras Abda within the older granites. Previous studies on this area demonstrated that the microgranite is altered in some parts and contains anomalous concentrations of rare metal elements (Zr, Th, and U). These altered and mineralized zones are re-assessed using field observations, chemical analysis, and by the application of various transmitted light and electron microscopic techniques. The rare metals exist as mineral segregation grew freely into open cavities of the microgranite and concordant with the NNE strike-slip fault movement. The mineralized zones contain an assemblage of secondary magnetite, zircon, uranothorite, columbite-(Mn), fergusonite-(Y), and allanite-(Ce). The extreme abundance of zircon in the mineralized zone, along with other evidence, indicates a hydrothermal origin of this zircon together with associated rare metals. The geochemical investigation and mass balance calculations revealed extreme enrichment of Zr, Th, U, Y, Nb, Ta, and REE. Post-magmatic hydrothermal alterations resulted in such pronounced chemical and mineralogical heterogeneity. The hydrothermal fluids are thought to be oxidizing, alkaline and of medium temperature (>?250 °C). The average contents of the elements Zr (1606 ppm), Th (1639 ppm), U (306 ppm), Nb (955 ppm), and REE (1710 ppm) in the mineralized microgranite reach sub-economic levels and could be a potential source of these elements.     

Forecasting monthly inflow with extreme seasonal variation using the hybrid SARIMA-ANN model

The optimal operation of dam reservoirs can be programmed and managed by predicting the inflow to these structures more accurately. To this end, there are various linear and nonlinear models. However, some hydrological problems like inflow with extreme seasonal variation are not purely linear or nonlinear. To improve the forecasting accuracy of this phenomenon, a linear Seasonal Auto Regressive Integrated Moving Average (SARIMA) model is combined with a nonlinear Artificial Neural Network (ANN) model. This new model is used to predict the monthly inflow to the Jamishan dam reservoir in West Iran. A comparison of the SARIMA and ANN models with the proposed hybrid model’s results is provided accordingly. More specifically, the models’ performance in forecasting base and flood flows is evaluated. The effect of changing the forecasting period length on the models’ accuracy is studied. The results of increasing the number of SARIMA model parameters up to five are investigated to achieve more accurate forecasting. The hybrid model predicts peak flood flows much better than the individual models, but SARIMA outperforms the other models in predicting base flow. The obtained results indicate that the hybrid model reduces the overall forecast error more than the ANN and SARIMA models. The coefficient of determination of the hybrid, ANN and SARIMA models were 0.72, 0.64 and 0.58, and the root mean squared error values were 1.02, 1.16 and 1.27 respectively, during the forecast period. Changing the forecasting length also indicated that these models can be used in the long term without increasing the forecast error.     

Investigation of surface and subsurface displacements due to multiple tunnels excavation in urban area

Underground structures are currently widely used and are built as urbanism develops. The interactions between perpendicularly crossing and parallel tunnels in the Tehran region are investigated by using a full three-dimensional (3D) finite difference analysis with elastic-plastic material models. Special attention is paid to the effect of subsequent tunneling on the support system, i.e., the shotcrete lining and rock bolts of the existing tunnel. Eventually, as the tunnels are excavated at certain levels, the interaction between the tunnels will certainly have a significant influence on both stress distribution and consequently deformations. Since multilayer tunneling is a three-dimensional phenomenon in nature, 3D numerical solutions must be utilized for analyzing effect of perpendicularly crossing tunnels at various levels. As Tohid twin tunnels and Line 7 pass beneath the Line 4 metro tunnel, changes in stress distribution, deformations, and surface settlements are studied for various conditions and the results are presented in this paper. Consequently, it is shown that there is a significant interaction between tunnels that necessitate certain preventive measures to maintain a stable tunneling operation.     

Spatial Distribution of Fractures in the Asmari Formation of Iran in Subsurface Environment: Effect of Lithology and Petrophysical Properties

The distribution of fractures and its dependence on lithology and petrophysical properties of rock in the Asmari Formation were examined using three wells data of one of the largest oil fields of southwestern Iran. Fractures were measured on cut cores. Mineral content and petrophysical data were obtained through thin section study and core plug measurement respectively. Influence of mineral composition and petrophysical property of rocks on fracture density was explored statistically. Increasing quartz (sand) and anhydrite content of rocks decrease and dolomite increases the threshold of fracture densities, however no significant relation was observed between calcite content of rock and fracture density. Increasing porosity and permeability of rock decrease the threshold of fracture density in some of the defined lithology groups. There are significant differences between the lithology groups in terms of fracture density, although the results in the three wells are not the same. In whole data, the highest fracture density can be observed in dolostone. Limestone and impure carbonates hold broader spaced fractures and sandstones display the least fracture density. The average fracture densities in the wells are strictly different. These differences are the result of the structural position of the wells and also the trend of the well and fractures. The distribution of fractures in most lithology groups can be explained by the function: , where F is relative frequency, D is fracture density and a, b, and c are constants.     

Cylindrical and spherical electron acoustic solitary waves in the presence of superthermal hot electrons

Propagation of cylindrical and spherical electron-acoustic solitary waves in unmagnetized plasmas consisting of cold electron fluid, hot electrons obeying a superthermal distribution and stationary ions are investigated. The standard reductive perturbation method is employed to derive the cylindrical/spherical Korteweg-de-Vries equation which governs the dynamics of electron-acoustic solitons. The effects of nonplanar geometry and superthermal hot electrons on the behavior of cylindrical and spherical electron acoustic soliton and its structure are also studied using numerical simulations.     

Investigation of SVM and Level Set Interactive Methods for Road Extraction from Google Earth Images

Currently, methods of extracting spatial information from satellite images are mainly based on visual interpretations and drawing the consequences by human factor, which is both costly and time consuming. A large volume of data collected by satellite sensors, and significant improvement in spatial and spectral resolution of these images require the development of new methods for optimal use of these data in order to produce rapid economic and updating road maps. In this study, a new automatic method is proposed for road extraction by integrating the SVM and Level Set methods. The estimated probability of classification by SVM is used as input in Level Set Method. The average of completeness, correctness, and quality was 84.19, 88.69 and 76.06% respectively indicate high performance of proposed method for road extraction from Google Earth images.     

Automatic urban building boundary extraction from high resolution aerial images using an innovative model of active contours

To present a new method for building boundary detection and extraction based on the active contour model, is the main objective of this research. Classical models of this type are associated with several shortcomings; they require extensive initialization, they are sensitive to noise, and adjustment issues often become problematic with complex images. In this research a new model of active contours has been proposed that is optimized for the automatic building extraction. This new active contour model, in comparison to the classical ones, can detect and extract the building boundaries more accurately, and is capable of avoiding detection of the boundaries of features in the neighborhood of buildings such as streets and trees. Finally, the detected building boundaries are generalized to obtain a regular shape for building boundaries. Tests with our proposed model demonstrate excellent accuracy in terms of building boundary extraction. However, due to the radiometric similarity between building roofs and the image background, our system fails to recognize a few buildings.     

Consistency of precipitation products over the Arabian Peninsula and interactions with soil moisture and water storage

The regional-scale consistency between four precipitation products from the GPCC, TRMM, WM, and CMORPH datasets over the Arabian Peninsula was assessed. Their macroscale relationships were inter-compared with soil moisture and total water storage (TWS) estimates from AMSR-E and GRACE. The consistency analysis was studied with multivariate statistical hypothesis testing and Pearson correlation metrics for the period from January 2000 to December 2010. The products and GRACE estimates were assessed over a representative sub-domain (United Arab Emirates) with available in situ well observations. Next, geographically temporally weighted regression (GTWR) was employed to examine the interdependencies among the peninsula’s hydrological components. The results showed GPCC-TRMM recording the highest correlation (0.85) with insignificant mean differences over more than 90% of the peninsula. The highest GTWR predictive performance of TWS (R² = 0.84) was achieved with TRMM forcing, which indicates its potential to monitor changes in TWS over the arid peninsular region.