Issues in Eulerian–Lagrangian modeling of sediment transport under saltation regime

The saltation regime is very important for understanding the sediment transport mechanism. However,there is no consensus on a model for the saltation regime. This study answers several questions raised with respect to the Eulerian-Lagrangian modeling of sediment transport. The first question is why the previous saltation models that use different combinations of hydrodynamic forces yielded acceptable results? The second question is which shear lift model(i.e. a shear lift expression and its coefficient) is more appropriate? Another important question is which hydrodynamic forces have greater contributions to the saltation characteristics of a sediment particle? The last question is what are the contributions of the turbulence fluctuations as well as effects of using two-and three-dimensional(2 D and 3 D) models on the simulation results? In order to fairly answer these questions, a systematic study was done by considering different scenarios. The current study is the first attempt to clearly discuss these issues. A comprehensive 3 D saltation model for non-cohesive sediment was developed that includes all the hydrodynamic forces acting on the particle. The random nature of sediment transport was included using turbulent flow and bed-particle collision models. The eddy interaction model was applied to generate a3 D turbulent flow field. Bed-particle collisions were considered using the concept of a contact zone and a corresponding contact point. The validation of the model was done using the available experimental data for a wide range of sediment size(0.03 to 4.8 cm). For the first question, the results indicated that some of the hydrodynamic effects show opposing trends and some have negligible effects. With these opposing effects it is possible to adjust the coefficients of different models to achieve acceptable agreement with the same experimental data while omitting some aspects of the physics of the process. A suitable model for the shear lift force was developed by linking the lift coefficient to the drag coefficient and the contributions of the hydrodynamic forces and turbulence fluctuations as well as the consequences of using of 2 D and 3 D models were studied. The results indicate that the shear lift force and turbulent flow fluctuations are important factors for the saltation of both sand and gravel, and they cannot be ignored.     

The transverse dynamics of flow in a tidal channel within a greater strait

Vessel-mounted ADCP measurements were conducted to describe the transverse structure of flow between the two headland tips in Khuran Channel, south of Iran (26° 45′ N), where the highest tidal velocities in spring tides were ~?1.8 m/s. Current profiles were obtained using a 614.4 kHz TRDI WorkHorse Broadband ADCP over nine repetitions of three cross-channel transects during one semidiurnal tidal cycle. The 2.2-km-long transects ran north/south across the channel. A least-square fit to semidiurnal, quarter-diurnal, and sixth diurnal harmonics was used to separate the tidal signals from the observed flow. Spatial gradients showed that the greatest lateral shears and convergences were found over the northern channel and near the northern headland tip due to very sharp bathymetric changes in this area. Contrary to the historical assumption, the across-channel momentum balance in the Khuran Channel was ageostrophic. The current study represents one of the few examples reported where the lateral friction influences the across-channel momentum balance.     

Spatial and Temporal Distribution of Dust‐Bound Trace Metal Elements around Kuhdasht Watershed Area in Iran

Dust, as a source of trace metal elements, affects the health of society. The spatial and temporal concentrations of dust‐bound trace metals (Cd, Pb, Ni, Zn, Cu, and Mn) in Kuhdasht watershed (456 km²), Lorestan Province, Iran, is investigated. Dust is collected using glass traps placed in ten research stations in the region. The spatial and temporal distribution of dust trace metals are plotted using ARC‐GIS. The highest and the lowest concentrations of Zn (9751150 mg kg^?1), Pb (46.352.9 mg kg^?1), and Cd (2.443.30 mg kg^?1) are obtained in winter, of Ni (98110 mg kg^?1) and Cu in autumn (16.053.5 mg kg^?1), and of Mn in summer (385505 mg kg^?1). The spatial concentrations of dust‐bound trace metals indicate all, except Cu, show a decreasing trend from the mountains toward the plains, similar to that of soil and of dust, except for Zn, which shows higher concentrations in dust than in soil. The potential sources of dust‐bound trace metals and their rate of contamination are also investigated using the enrichment and contamination factors. The major sources of Cd and Zn in the dust of watershed are due to anthropogenic activities or from activities outside the borders.     

Spatially-Weighted Factor Analysis for Extraction of Source-Oriented Mineralization Feature in 3D Coordinates of Surface Geochemical Signal

Natural Resources Research - This contribution proposes a spatially weighted factor analysis (SWFA) to recognize effectively the underlying mineralization-related feature(s) in geochemical signals....     

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.     

Impact of hydrogeomorphic processes on ecological functions of brown trout habits

In recent decades, due to river regulations and their impact on river morphology, brown trout populations have been declining along Lar River downstream of Lar Dam located near Tehran, Iran. Considering the recent water scarcity in the country, development of river habitat assessment models seems necessary. Therefore, in this research, an analytically applied approach is adopted to evaluate brown trout habitat by creating a relation among the hydrologic, hydraulic, geomorphic and ecologic processes. After field survey, dimensionless shear stress of the stream flow thresholds including environmental flow, bankfull flow, surface and subsurface sediment flow thresholds was calculated for Lar, Dalichay and Sefidab Rivers using Shields formula. Then, by considering the dimensionless shear stress ranges of the stream flow thresholds, functional flows ranges and duration were calculated together with ecological efficiency of the cross sections. In addition, effects of annual water yield and entrenchment ratio of the cross sections on habitat functionality were also worked out as a result of which an exponential interaction was developed between the dimensionless shear stress and discharge. Results show that an increase in functional flows ranges and duration, together with rising of ecological efficiency, is directly proportional to an increase in median bed sediment size, entrenchment ratio and annual water yield. Therefore, flow regime, cross-sectional geometry, water-surface slope and bed sediment size could be effective on the ecological functions of the brown trout’s life cycle and functionality of river flow.     

Support vector machines and feed-forward neural networks for spatial modeling of groundwater qualitative parameters

The present study attempts to model the spatial variability of three groundwater qualitative parameters in Guilan Province, northern Iran, using artificial neural networks (ANNs) and support vector machines (SVMs). Data collected from 140 observation wells for the years 2002–2014 were used. Five variables, X and Y coordinates of the observation well, distance of the observation well from the shoreline, areal average 6-month rainfall depth, and groundwater level at the day of water quality sampling, were considered as primary input variables. In addition, nine qualitative variables were also considered as auxiliary input variables. Electrical conductivity (EC), sodium concentration (Na⁺), and sulfate concentration (SO₄ ^2?) of the groundwater in the region were estimated using ANNs and SVMs with different input combinations. The results showed that both ANNs and SVMs work well when the only primary input variable is the well location. The ANN yielded an RMSE of 1.03 mEq/l for SO₄ ^2?, 1.05 mEq/l for Na⁺, and 203.17 μS/cm for EC, using the X and Y coordinates of the observation wells in the study area. In the case of SVM, these values were, respectively, 0.87, 0.87, and 176.68. Considering the auxiliary input variables (pH, EC, and the concentrations of Na⁺, K⁺, Ca²⁺, Mg²⁺, Cl^?, SO₄ ^2?, and HCO₃ ^?) resulted in a significant decrease in the RMSE of both ANNs (0.22, 0.30, and 33.04) and SVMs (0.26, 0.34, and 36.23). Comparing these RMSE values with those of cokriging interpolation technique (0.59, 0.98, and 177.59) indicated that ANNs and SVMs produced more accurate estimates of the three qualitative parameters. The relative importance of auxiliary input variables was also determined using Gamma test. The output uncertainty of ANNs and SVMs were determined using p-factor and d-factor. The results showed that SVMs have less uncertainty than ANNs.     

Denoising and improving the quality of seismic data using combination of DBM filter and FX deconvolution

Seismic data denoising, random noise attenuation (RNA) and spike-like noise suppression, is a main consideration for improving the quality of records. RNA could increase signal to noise ratio (S/N) to avoid misinterpretation of seismic data. In this research, a novel method is created by using the combination of frequency-offset deconvolution (FXD) and decision-based median (DBM) filter for RNA from seismic data. The method is applied in two main phases; FXD is focused to remove the Gaussian noise and DBM filter is focused to attenuate the impulsive noise and spikes. To implement and verify the method, three types of data are used: two synthetic models (a model with linear events and a model with hyperbolic events) and an observed seismic section. The ability of the proposed method (FXD-DBM) in comparison of applying each in seismic RNA application is proven. The noise level is reduced obviously, and hence, the S/N of all examined seismic records is increased considerably after denoising by the combination of FX deconvolution and DBM filter. About the real seismic section, suppressing random noise and spikes show up improving the seismic reflector continuity and hence enhancing the interpretability of data. Moreover, some masked events by random noise are clarified in different parts of data after denoising using the planned method.     

Implementation of online model updating in hybrid simulation

Hybrid simulation combines numerical and experimental methods for cost‐effective, large‐scale testing of structures under simulated earthquake loading. Structural system level response can be obtained by expressing the equation of motion for the combined experimental and numerical substructures, and solved using time‐stepping integration similar to pure numerical simulations. It is often assumed that a reliable model exists for the numerical substructures while the experimental substructures correspond to parts of the structure that are difficult to model. A wealth of data becomes available during the simulation from the measured experiment response that can be used to improve upon the numerical models, particularly if a component with similar structural configuration and material properties is being tested and subjected to a comparable load pattern. To take advantage of experimental measurements, a new hybrid test framework is proposed with an updating scheme to update the initial modeling parameters of the numerical model based on the instantaneously‐measured response of the experimental substructures as the test progresses. Numerical simulations are first conducted to evaluate key algorithms for the selection and calibration of modeling parameters that can be updated. The framework is then expanded to conduct actual hybrid simulations of a structural frame model including a physical substructure in the laboratory and a numerical substructure that is updated during the tests. The effectiveness of the proposed framework is demonstrated for a simple frame structure but is extendable to more complex structural behavior and models. Copyright © 2013 John Wiley & Sons, Ltd.     

Innovative substructuring technique for hybrid simulation of multistory buildings through collapse

Hybrid simulation combines numerical and experimental methods for cost‐effective, large‐scale testing of structures under simulated dynamic earthquake loads. Particularly for experimental seismic collapse simulation of structures, hybrid testing can be an attractive alternative to earthquake simulators due to the limited capacity of most facilities and the difficulties and risks associated with a collapsing structure on a shaking table. The benefits of hybrid simulation through collapse can be further enhanced through accurate and practical substructuring techniques that do not require testing the entire structure. An innovative substructuring technique for hybrid simulation of structures subjected to large deformations is proposed to simplify the boundary conditions by overlapping the domains between the numerical and experimental subassemblies. The advantages of this substructuring technique are the following: it requires only critical components of the structure to be tested experimentally; it reduces the number of actuators at the interface of the experimental subassemblies; and it can be implemented using typically available equipment in laboratories. Compared with previous overlapping methods that have been applied in hybrid simulation, this approach requires additional sensing in the hybrid simulation feedback loop to obtain internal member forces, but provides significantly better accuracy in the highly nonlinear range. The proposed substructuring technique is verified numerically and validated experimentally, using the response of a four‐story moment‐resisting frame that was previously tested to collapse on an earthquake simulator. Copyright © 2014 John Wiley & Sons, Ltd.