Morphed block-crack preferential sedimentation in a reservoir bed: a smart design and evolution in nature

Abstract

A pedological study of the reservoir bed of Al-Khoud Dam, Oman, revealed an unusual sedimentation pattern which evolved into an intricate composition of silt blocks surrounded by vertical cracks and horizontal layers filled with a “proppant” sand. The discovered soil morphology reflects the complex topology of water motion (infiltration–seepage–evaporation) through the sand-filled cracks/layers and blocks during both the rare flood events and ensuing periods of ponding, and the long, intervening dry periods. These naturally formed soils demonstrate an ability to preserve a large quantity of water inside the silty blocks at depths of 0.5 to 1.5 m, despite the high temperature and dryness of the topsoil. The hydrological optimality and “smartness” of these soils is attributed to the unique block-crack system. Natural, lush vegetation was found in adjacent zones of the reservoir bed, and acted as a footprint of the shallow “fractured perched aquifer”. Planted “ivy” (Convolvulaceae) in the vertical face of one pedon showed intensive growth without irrigation. Soil moisture content data confirmed the hydrological immobility of water in the blocks if not depleted by transpiration. The novel phenomena reported unveil the possible alteration of soil heterogeneity for optimization of the soil–water system in arid zone soils.

Editor D. Koutsoyiannis; Associate editor F.F. Hattermann

Citation Al-Ismaily, S.S., Al-Maktoumi, A.K., Kacimov, A.R., Al-Saqri, S.M., Al-Busaidi, H.A., and Al-Haddabi, M.H., 2013. Morphed block-crack preferential sedimentation in a reservoir bed: a smart design and evolution in nature. Hydrological Sciences Journal, 58 (8), 1779–1788.     

Development of A Three-Dimensional Guidance System for Long-Range Maneuvering of A Miniature Autonomous Underwater Vehicle

The present paper introduces a three-dimensional guidance system developed for a miniature Autonomous Underwater Vehicle（AUV）. The guidance system determines the best trajectory for the vehicle based on target behavior and vehicle capabilities. The dynamic model of this novel AUV is derived based on its special characteristics such as the horizontal posture and the independent diving mechanism. To design the guidance strategy, the main idea is to select the desired depth, presumed proportional to the horizontal distance of the AUV and the target. By connecting the two with a straight line, this strategy helps the AUV move in a trajectory sufficiently close to this line. The adjacency of the trajectory to the line leads to reasonably short travelling distances and avoids unsafe areas. Autopilots are designed using sliding mode controller. Two different engagement geometries are considered to evaluate the strategy＇s performance： stationary target and moving target. The simulation results show that the strategy can provide sufficiently fast and smooth trajectories in both target situations.     

Sensitivity of a regional climate model on the simulation of high intensity rainfall events over the Arabian Peninsula and around Jeddah (Saudi Arabia)

As a step towards the adoption and use of the regional climate model (RegCM3) for the simulation of intense rainfall events over the Arabian Peninsula, this study examines its sensitivity to domain size, boundary location, forcing fields, and resolution. In the climatological results, RegCM3 performs well in reproducing the annual and the seasonal mean precipitation as well as the contrast between wet and dry years in terms of the amounts and locations of the rainbands. In addition, simulations are performed for two cases of intense rainfall events in the Jeddah area and surroundings using a combination of three domains and two boundary forcings at 50?km. The results show that different combinations of these parameters provide different skills for the regional model. However, RegCM3 performs relatively better when ERA40 (NNRP2) is used at the boundaries in the smaller domain (larger domain), indicating the importance of the stronger (relatively weaker) influence of boundary forcing needed to capture these intense rainfall events around Jeddah. This may be explained by the fact that around that region, RegCM3 produces, in the smaller domain, higher relative humidity and stronger wind vectors closer to the reanalyses when nested within the ERA40, while it shows its best performance with the larger domain when driven by NNRP2. It is also shown that the use of high resolution does not systematically improve the simulation of such events, although some encouraging results were produced.     

On the application of GPR for locating underground utilities in urban areas

With the rapid growth of complex network of different types of underground utility under large cities, the need of a noninvasive technique capable of swiftly and precisely detecting these utilities in such a noisy urban environment increases. Ground-penetrating radar (GPR) is considered one of the most promising techniques in this field. This study presents the experience of GPR data acquisition, processing, and interpretation in three cities located along the coast of the Red Sea. These cities are Jeddah in Saudi Arabia and Sharm El-Sheikh and Qusier in Egypt. Data acquisition parameters varied in the three cities based on site conditions, target characteristics, and equipment availability. The processing flows were kept simple to avoid introducing artifacts to the collected data. The results show that despite the difference in site conditions and survey parameters among the three cities, with the exception of fiber optic cable, GPR technique is capable of detecting different kinds of underground utilities and precisely determine the extension, diameter, and depth of burial of these utilities.     

Neuro-fuzzy modeling based genetic algorithms for identification of geochemical anomalies in mining geochemistry

A genetic algorithm (GA)-based neuro-fuzzy approach is used for identification of geochemical anomalies by implementing a Takagi, Sugeno and Kang (TSK) type fuzzy inference system in a 5-layered feed-forward adaptive artificial neural network. This paper investigates the effectiveness of GA-based neuro-fuzzy for separating zone dispersed mineralization (ZDM) from blind mineralization, and its application for identification of geochemical anomalies in the arid landscape of the Lut metallogenic province in eastern Iran. Other classification algorithms such as metallometry, zonality, criteria, and back-propagation artificial neural network classifiers are also used for comparison. The genetic operators are carefully designed to optimize the artificial neural network, avoiding premature convergence and permutation problems. The results show that the GA-based hybrid neuro-fuzzy model can provide accurate results in comparison with those results obtained by other techniques. Neuro-fuzzy and GA-based neuro-fuzzy techniques appear to be well-suited for routine exploration geochemistry applications. In conjunction with statistics and conventional mathematical methods, hybrid approaches can be developed and may prove a step forward in the practice of applied geochemistry.     

Geochemical and mineralogical pattern recognition and modeling with a Bayesian approach to hydrothermal gold deposits

The Bayesian approach is an effective method of identifying the probability of mineralogical and geochemical type (MGT) mineralization of trace elements in galena, pyrite and other distributions in ore mineralization. Monomineralic samples have been identified using a computer-based Bayesian method and exploration geochemical techniques of Au deposits for MGT. In order to employ the method, a data bank was used consisting of the results of analysis of more than 12,000 monomineralic samples collected from the main hydrothermal Au deposits in Tajikistan (a territory of CIS). The Bayesian approach applied to geochemical data, such as posterior probabilities and discriminant analysis, provide numerical and graphical means through which the relationships between the trace elements and samples can be studied. The method used here, along with GIS, to find MGT can be used as geochemical indicators of regions with Au mineralization. The results of analyzing 100 monomineralic samples of pyrite from the Au–Ag Shkolnoe deposit (Tajikistan) show a multi-MGT anomaly superposition which is a combination of three MGT: (1) Au–Ag type (85% and more), (2) Au–sulfide-polymetallic type (46%), and (3) Au–sulfide type (40%). Mineralogical and geochemical maps (MGM) can be drawn based on results of MGT anomalies in a GIS environment. These maps can replace traditional metallogenic maps. The advantage of MGM substitutions is that a qualitative tool is replaced by a quantitative one. This helps one to make optimal managerial and more economical decisions.     

Interpretation of some magnetic bodies using neural networks inversion

Magnetic surveys have been used for mineral exploration where different data processing techniques were used to derive the parameters of causative targets. In this respect, the neural network (NN) technique was used to estimate the magnetic causative target parameters. Examples of NN inversion have been tested on synthetic examples where the NN was trained well using forward models of the vertical magnetic effect of a vertical sheet and a horizontal circular cylinder. Specifically, modular neural network (MNN) inversion has been used for the parameter estimation of the causative targets, where the sigmoid function was used as the activation function. The effect of random noise and the error estimation of the horizontal location have been analyzed. When NN is applied to real data, it estimates successfully the parameters of the causative targets such as burial depths, magnetic constants, and angle of polarization. Hilbert transform has been used to locate the source origin, which is important for the NN inversion. This approach has more advantages than the conventional data inversions in terms of its efficiency and flexibility. It also gives fast solutions. The MNN approach has been applied to the Kursk and Manjampalli anomalies, where the results were shown to be in good agreement with the other techniques published in the literature.     

Leaching of Lisan Marl and its consequences on the engineering behavior of dikes,studied by finite elements modeling

Leaching of Lisan Marl, Dead Sea, Jordan increased the soil compressibility and cohesion intercept. Back analysis using the Plaxis finite element code was successfully implemented. The Finite element modeling of dike construction showed a significant increase of total settlement and negligible effect on the strength as calculated by the φ/c reduction method. The height of dikes to be constructed on Lisan Marl as foundation material, should be optimized to account for the effect of soluble salts leaching. For this to take place, an accurate calculation of settlement is crucial.