3D inversion of DC data using artificial neural networks

In this paper, we investigate the applicability of artificial neural networks in inverting three-dimensional DC resistivity imaging data. The model used to produce synthetic data for training the artificial neural network (ANN) system was a homogeneous medium of resistivity 100 Ωm with an embedded anomalous body of resistivity 1000 Ωm. The different sizes for anomalous body were selected and their location was changed to different positions within the homogeneous model mesh elements. The 3D data set was generated using a finite element forward modeling code through standard 3D modeling software. We investigated different learning paradigms in the training process of the neural network. Resilient propagation was more efficient than any other paradigm. We studied the effect of the data type used on neural network inversion and found that the use of location and the apparent resistivity of data points as the input and corresponding true resistivity as the output of networks produces satisfactory results. We also investigated the effect of the training data pool volume on the inversion properties. We created several synthetic data sets to study the interpolation and extrapolation properties of the ANN. The range of 100–1000 Ωm was divided into six resistivity values as the background resistivity and different resistivity values were also used for the anomalous body. Results from numerous neural network tests indicate that the neural network possesses sufficient interpolation and extrapolation abilities with the selected volume of training data. The trained network was also applied on a real field dataset, collected by a pole-pole array using a square grid (8 ×8) with a 2-m electrode spacing. The inversion results demonstrate that the trained network was able to invert three-dimensional electrical resistivity imaging data. The interpreted results of neural network also agree with the known information about the investigation area.     

The Effects of Hydrophilic Polymer and Soil Salinity on Corn Growth in Sandy and Loamy Soils

The interaction effects of different applied ratios of a hydrophilic polymer (Superab A200) (0, 0.2, 0.6% w/w) under various soil salinity levels (initial salinity, 4 and 8 ms/cm) were evaluated on available water content (AWC), biomass, and water use efficiency for corn grown in loamy sand and sandy clay loam soils. The results showed that the highest AWC was measured at the lowest soil salinity. The application of 0.6% w/w of the polymer at the lowest salinity level increased the AWC by 2.2 and 1.2 times greater than those of control in the loamy sand and sandy clay loam soils, respectively. The analysis of variance of data showed that the effect of salinity was significant on biomass and water use efficiency of corn in the loamy sand and sandy clay loam soils. The highest amounts of these traits were measured in soils with the lowest salinity level. Application of polymer at the rate of 0.6% in the loamy sand soil and at the rate of 0.2% in the sandy clay loam soil resulted in the highest aerial and root biomass and water use efficiency for corn. At these polymer rates the amounts of water use efficiency for corn were 2.6 and 1.7 times greater than those of control in the loamy sand and sandy clay loam soils, respectively. Thus, the use of hydrophilic polymer in soils especially in the sandy soils increases soil water holding capacity, yield, and water use efficiency of plant. On the other hand, decreases the negative effect of soil salinity on plant and helps for irrigation projects to succeed in arid and semi‐arid areas.     

Application of various methods for 2D inverse modeling of residual gravity anomalies

This paper presents a neural network approach to determine 2D inverse modeling of a buried structure from gravity anomaly profile. The results of the applied neural network method are compared with the results of two other methods, least-squares minimization and the simple method. Sphere, horizontal cylinder and vertical cylinder and their gravity effects are considered as the synthetic models and the synthetic data, respectively. The synthetic data are also corrupted with noise to evaluate the capability of the methods. Then the Dehloran bitumen map in Iran is chosen as a real data application. Anomaly value of the cross-section, which is taken from the gravity anomaly map of Dehloran bitumen, is very close to those obtained from these methods.     

2.5-D Gravity/Magnetic Model Studies in Sahl El Qaa Area, Southwestern Sinai, Egypt

The 2.5-D gravity-magnetic models of the upper crustal structures of Sahl El Qaa Area, Southwestern Sinai were constructed along seven profiles, focusing on the uppermost crustal layers to a depth of 4–5 km. In addition separation filtering process; spectral analysis and trend analysis were used to investigate the Bouguer and total intensity aeromagnetic field maps qualitatively and quantitatively. The study showed that the regional structures consist of tilted blocks in the form of a major NW-synclinal feature with an axis dipping northward. This feature is dissected by the NE trending cross faults forming horsts, grabens and step-fault structures. The tilted blocks are controlled by a major normal fault system and are greatly modified in the dip regime from north to south. They show a regional NW dip regime in northern and southern parts, where the depth to the basement reaches about 2–3 km in the down dip. In the central portion, the basin is dipping steeply to the east, with maximum depths attaining about 4–5 km.     

Climatic prediction of the terrestrial and coastal areas of Iraq

Climatic data from four meteorological stations in Iraq (Mosul, Baghdad, Basra, and Rutba) were obtained. The recorded temperature data since 1960 till 2007 and rainfall and evaporation data since 1960 till 2008 and 1970 till 2008, respectively, were used and interpreted. This study showed an increase in temperature of about 5°C/47?years and an increase in evaporation rate with a decrease in the rainfall rate. Carbon dioxide in the atmosphere appears to be a factor controlling climate change. Basra climate, due to its location which is nearest to the Arabian Gulf, is expressed as a coastal climate and has a different behavior from Mosul, Baghdad, and Rutba, which are considered as terrestrial climates.     

Drought analysis in Jordan under current and future climates

Droughts have adverse socioeconomic, agricultural, and environmental impacts that can be reduced by assessing and forecasting drought behavior. The paper presents detailed analyses of both meteorological and vegetative droughts over the period from 1970 to 2005. Standardized Precipitation Index (SPI) and Normalized Difference Vegetation Index (NDVI) have been used to quantify drought according to severity, magnitude and spatial distribution at the Hashemite Kingdom of Jordan. Results suggest that the country faced during the past 35 years frequent non-uniform drought periods in an irregular repetitive manner. Drought severity, magnitudes and life span increased with time from normal to extreme levels especially at last decade reaching magnitudes of more than 4. Generated NDVI maps spatial analyses estimate crop-area percentage damage due to severe and extremely severe drought events occurred during October, December, and February of 2000 to be about 10%, 45%, and 30%, respectively. In response to drought spatial extent, the paper suggest the presence of two drought types, local drought acting on one or more geographical climatic parts and national drought, of less common but more severe, that extend over the whole country. Droughts in Jordan act intensively during January, February and March and tend to shift position with time by alternative migrations from southern desert parts to northern desert parts and from the eastern desert parts to highlands and Jordan Rift Valley (JRV) at the west. The paper also investigates the potential use of Global Climate Model’s (GCM) to forecast future drought events from 2010 till 2040. Tukey HSD test indicates that ECHAM5OM GCM is capable to predicted rainfall variation at the country and suggests future droughts to become more intensive at the northern and southern desserts with 15% rainfall reduction factor, followed by 10% reduction at the JRV, and 5% at the highlands.     

ANALYSIS OF FOLDS SOUTH OF MALAKAND AND ADJOINING AREAS, NORTH PAKISTAN

ANALYSIS OF FOLDS SOUTH OF MALAKAND AND ADJOINING AREAS, NORTH PAKISTAN1　Can啨ｒｏｔＪ,QuG .CuadernosdeGeologiaiberica ,1998,2 4:311～ 331. 2　DebelmasJ,MascleG .EnsSciencesdelaTerre[M ].Masson ,ed .1991.2 99.3　GaetaniM ,GarzantiE .AAPGBull ,1991,75 (9) :142 7～ 144 6 . 4　HendrixMS ,GrahamSA ,CarrollAR ,etal.GeolSocAmBull,1992 ,10 4:5 3～ 79.. 5　Jia ,Coll.PetroleumIndustryPress,Beijing .1997,2 95 . 6　JiaD ,LuHCaiD ,etal.AAPGBull ,8…     

Understanding nesting ecology and behaviour of green marine turtles at Setiu,Terengganu, Malaysia

In this paper, we emphasize the importance of understanding the nesting ecology and nesting behaviour of green marine turtles (Chelonia mydas). Data were collected from 2007 until 2012 from nesting beaches at Setiu Terengganu, Malaysia. We focused on one of the beaches, Telaga Papan, based on data collected in 2012. We recorded the distribution of nesting areas, the emergence hour and the correlation between successful nesting attempts and false crawls. Telaga Papan had a significantly higher distribution of green marine turtle nesting compared with the other five beaches (ANOVA, F_5,42 = 8.874, P < 0.01, mean = 36.750 ± 3.727). The highest number of successful nesting attempts was recorded in 2012 (mean = 28.714). A majority of the species landed between 22:00 and 23:59 h (25%). There was a strong correlation between successful nesting attempts and false crawls (r_s = 0.883, P = 0.02). Based on these findings on the nesting ecology and nesting behaviour of green marine turtles, we suggest that scientific research, strict monitoring, awareness programs and policy implementation should be carried out proactively. Such activities are necessary to reduce the anthropogenic pressures at the nesting beaches as well as to ensure more successful nesting attempts of green marine turtles in Setiu.