Empirical modeling of plate load test moduli of soil via gene expression programming

New empirical models were developed to predict the soil deformation moduli using gene expression programming (GEP). The principal soil deformation parameters formulated were secant (E_s) and reloading (E_r) moduli. The proposed models relate E_s and E_r obtained from plate load-settlement curves to the basic soil physical properties. The best GEP models were selected after developing and controlling several models with different combinations of the influencing parameters. The experimental database used for developing the models was established upon a series of plate load tests conducted on different soil types at depths of 1–24 m. To verify the applicability of the derived models, they were employed to estimate the soil moduli of a part of test results that were not included in the analysis. The external validation of the models was further verified using several statistical criteria recommended by researchers. A sensitivity analysis was carried out to determine the contributions of the parameters affecting E_s and E_r. The proposed models give precise estimates of the soil deformation moduli. The E_s prediction model provides considerably better results in comparison with the model developed for E_r. The simplified formulation for E_s significantly outperforms the empirical equations found in the literature. The derived models can reliably be employed for pre-design purposes.     

Non-stationary extreme value analysis in a changing climate

This paper introduces a framework for estimating stationary and non-stationary return levels, return periods, and risks of climatic extremes using Bayesian inference. This framework is implemented in the Non-stationary Extreme Value Analysis (NEVA) software package, explicitly designed to facilitate analysis of extremes in the geosciences. In a Bayesian approach, NEVA estimates the extreme value parameters with a Differential Evolution Markov Chain (DE-MC) approach for global optimization over the parameter space. NEVA includes posterior probability intervals (uncertainty bounds) of estimated return levels through Bayesian inference, with its inherent advantages in uncertainty quantification. The software presents the results of non-stationary extreme value analysis using various exceedance probability methods. We evaluate both stationary and non-stationary components of the package for a case study consisting of annual temperature maxima for a gridded global temperature dataset. The results show that NEVA can reliably describe extremes and their return levels.     

Evaluation of four supervised learning methods for groundwater spring potential mapping in Khalkhal region (Iran) using GIS-based features

One important tool for water resources management in arid and semi-arid areas is groundwater potential mapping. In this study, four data-mining models including K-nearest neighbor (KNN), linear discriminant analysis (LDA), multivariate adaptive regression splines (MARS), and quadric discriminant analysis (QDA) were used for groundwater potential mapping to get better and more accurate groundwater potential maps (GPMs). For this purpose, 14 groundwater influence factors were considered, such as altitude, slope angle, slope aspect, plan curvature, profile curvature, slope length, topographic wetness index (TWI), stream power index, distance from rivers, river density, distance from faults, fault density, land use, and lithology. From 842 springs in the study area, in the Khalkhal region of Iran, 70 % (589 springs) were considered for training and 30 % (253 springs) were used as a validation dataset. Then, KNN, LDA, MARS, and QDA models were applied in the R statistical software and the results were mapped as GPMs. Finally, the receiver operating characteristics (ROC) curve was implemented to evaluate the performance of the models. According to the results, the area under the curve of ROCs were calculated as 81.4, 80.5, 79.6, and 79.2 % for MARS, QDA, KNN, and LDA, respectively. So, it can be concluded that the performances of KNN and LDA were acceptable and the performances of MARS and QDA were excellent. Also, the results depicted high contribution of altitude, TWI, slope angle, and fault density, while plan curvature and land use were seen to be the least important factors.     

Application of a 3D photorealistic model for the geological analysis of the Permian carbonates (Khuff Formation) in Saudi Arabia

Three dimensional (3D) photorealistic models of geological outcrops have the potential to enhance the teaching of earth sciences by providing scale models in a virtual reality environment. These models can be run on low-cost desktop computers. Photorealistic models for geological outcrops are a digital illustration of outcrop photographs with either a point cloud representation or Triangular Irregular Network (TIN) mesh of the outcrop surface. The level of detail for these models is dependent on the target resolutions (physical and optical) that were used during data acquisition. In addition, the technique in which the data is rendered as a digital model affects the level of detail that can be observed by the geologists. A colored point cloud representation is suitable for large-scale features, but fine details are lost when the geologist zooms in to view the model close up. In contrast, a photorealistic model that is constructed from photographs draped onto a triangle mesh surface derived from Light Detection and Ranging (LiDAR) point clouds provides a level of detail that is restricted only by the resolution of the photographs.     

Evaluation of distributed recharge in an upland semi-arid karst system: the West Bank Mountain Aquifer,Middle East

Assessment of recharge in a structurally complex upland karst limestone aquifer situated in a semi-arid environment is difficult. Resort to surrogate indicators such as measurement of spring outflow and borehole discharge, is a common alternative, and attempts to apply conventional soil moisture deficit analysis may not adequately account for the intermittent spate conditions that arise in such environments. A modelling approach has been made using the West Bank Mountain Aquifer system in the Middle East as a trial. The model uses object oriented software which allows various objects to be switched on and off. Each of the main recharge processes identified in the West Bank is incorporated. The model allows either conventional soil moisture deficit analysis calculations or wetting threshold calculations to be made as appropriate, and accommodates both direct recharge and secondary recharge. Daily time steps enable recharge and runoff routing to be calculated for each node. Model runs have enabled a series of simulations for each of the three aquifer basins in the West Bank and for the whole of the West Bank. These provide recharge estimates comparable to those prepared by earlier workers by conventional means. The model is adaptable and has been successfully used in other environments.     

Ground roll attenuation using the S and x-f-k transforms

Ground roll, which is characterized by low frequency and high amplitude, is an old seismic data processing problem in land‐based seismic acquisition. Common techniques for ground roll attenuation are frequency filtering, f‐k or velocity filtering and a type of f‐k filtering based on the time‐offset windowed Fourier transform. These techniques assume that the seismic signal is stationary. In this study we utilized the S, x‐f‐k and t‐f‐k transforms as alternative methods to the Fourier transform. The S transform is a type of time‐frequency transform that provides frequency‐dependent resolution while maintaining a direct relationship with the Fourier spectrum. Application of a filter based on the S transform to land seismic shot records attenuates ground roll in a time‐frequency domain. The t‐f‐k and x‐f‐k transforms are approaches to localize the apparent velocity panel of a seismic record in time and offset domains, respectively. These transforms provide a convenient way to define offset or time‐varying reject zones on the separate f‐k panel at different offsets or times.     

Artificial neural network inversion of magnetic anomalies caused by 2D fault structures

A new approach is proposed to interpret magnetic anomalies caused by 2D fault structures. This approach is based on the artificial neural network inversion, utilizing particularly modular neural network algorithm. The inversion process is implemented to estimate the parameters of 2D fault structures where it has been verified first on synthetic models. The results of the inversion show that the parameters derived from the inversion agree well with the true ones. The analysis of noise has been studied in order to investigate the stability of the approach where it has been tested for contaminated anomalies with 5 and 10 % of white Gaussian noise. The results of the inversion provide satisfactory results even with contaminated signals.The validity of the approach has been demonstrated through real data taken from New South Wales, Australia. A comparable and satisfactory agreement is shown between the inversion results of the neural network and those from techniques published in literatures.     

Magnetic and DC resistivity investigation for groundwater in a complex subsurface terrain

Subsurface structures associated with hard rocks are very important for groundwater. Wadi Fatima runs through the volcanic and metamorphic rocks of the Arabian Shield which are characterized by higher magnetization than the overlaying alluvium sediments. Magnetic and direct current (DC) resistivity methods have been used for groundwater exploration in the northern part of Wadi Fatima. The magnetic survey was used mainly to map the subsurface structures, using analytic signal algorithm, of the study area. The DC resistivity method was applied to describe the lithologic domain as a function of depth, depending on their electrical property contrasts where it provided a good indication for water bearing formations. The magnetic and DC resistivity interpretations were confirmed by drilling which have provided a clear idea about the hydrogeological regime of the study area. The selected drilled well is successfully productive and it produces 30 m³/h.     

Geochemistry and zircon U-Pb geochronology of Aligoodarz granitoid complex, Sanandaj-Sirjan Zone, Iran

The Aligoodarz granitoid complex (AGC) is located in the Sanandaj-Sirjan Zone (SSZ), western Iran and consists of quartz-diorites, granodiorites and subordinate granites. Whole rock major and trace element data mostly define linear trends on Harker diagrams suggesting a cogenetic origin of the different rock types. (⁸⁷Sr/⁸⁶Sr)_i and εNd_t ratios are in the ranges 0.7074-0.7110 and −3.56 to −5.50, respectively. The trace elements and Sr-Nd isotopic composition suggest that the granitoids from the AGC are similar to crustal derived I-type granitoids of continental arcs. The whole rock suite was produced by assimilation and fractional crystallization starting from a melt with intermediate composition likely possessing a mantle component. In situ zircon U-Pb data on the granites with LA-ICP-MS yield a crystallization age of ∼165 Ma. Inherited grains spanning in age from ∼180 Ma up to 2027 Ma were also found and confirm that assimilation of country rock has occurred.Chemical and chronological data on the AGC were compared with those available for other granitoid complexes of the central SSZ (e.g., Dehno, Boroujerd and Alvand). The comparison reveals that in spite of the different origins that have been proposed, all these granitoid complexes are likely genetically related. They share many chemical features and are derived from crustal melts with minor differences. Alvand granites have the most peculiar compositions most likely related to the presence of abundant pelitic component. All these intrusions are coeval and reveal the presence of an extensive magmatic activity in the central sector of the SSZ during middle Jurassic.     

Estimation of viscoelastic attenuation of real seismic data by use of ray tracing software: Application to the detection of gas hydrates and free gas

Analysis of P wave velocity profiles and seismic data recorded over the 2002 Hydratech cruise conducted in the Storegga region, North of Norway, has shown the existence of anomalies (a velocity decrease) in some layers of the medium. An elastic propagation model is not sufficient to explain clearly these anomalies, since the viscoelastic attenuation, represented by the quality factor Q_P, is sensitive to physical phenomena of geological media. The combination of the quality factor profile with the velocity profile leads to realistic explanations of these anomalies. In this article, we explain the procedure which we developed for determining the Q_P profile from the P wave velocity profile and the seismic data recorded during Hydratech cruise. Both the Q_P and velocity profiles indicate anomalies in the same layers. Based on previous studies, we interpret that these anomalies are being due to existence of gas hydrates and free gas within these layers.