Using LM‐OSL of quartz to distinguish sediments derived from surface‐soil and channel erosion

This study describes the use of linearly modulated optically stimulated luminescence (LM‐OSL) to distinguish surface‐soil derived sediments from those derived from channel bank erosion. LM‐OSL signals from quartz extracted from 15 surface‐soil and five channel bank samples were analysed and compared to signals from samples collected from two downstream river sites. Discriminant analysis showed that the detrapping probabilities of fast, first slow and second slow components of the LM‐OSL signal can be used to differentiate between the samples collected from the channel bank and surface‐soil sources. We show that for each of these source end members these components are all normally distributed. These distributions are then used to estimate the relative contribution of surface‐soil derived and channel bank derived sediment to the river bed sediments. The results indicate that channel bank derived sediments dominate the sediment sources at both sites, with 90.1 ± 3% and 91.9 ± 1.9% contributions. These results are in agreement with a previous study which used measurements of ¹³⁷Cs and ²¹⁰Pb_ex fallout radionuclides to estimate the relative contribution from these two sources. This result shows that LM‐OSL may be a useful method, at least in the studied catchment, to estimate the relative contribution of surface soil and channel erosion to river sediments. However, further research in different settings is required to test the difference of OSL signals in distinguishing these sediment sources. And if generally acceptable, this technique may provide an alternative to the use of fallout radionuclides for source tracing. Copyright © 2015 John Wiley & Sons, Ltd.     

Parametric uncertainty assessment of hydrological models: coupling UNEEC-P and a fuzzy general regression neural network

Due to the complicated nature of environmental processes, consideration of uncertainty is an important part of environmental modelling. In this paper, a new variant of the machine learning-based method for residual estimation and parametric model uncertainty is presented. This method is based on the UNEEC-P (UNcertainty Estimation based on local Errors and Clustering – Parameter) method, but instead of multilayer perceptron uses a “fuzzified” version of the general regression neural network (GRNN). Two hydrological models are chosen and the proposed method is used to evaluate their parametric uncertainty. The approach can be classified as a hybrid uncertainty estimation method, and is compared to the group method of data handling (GMDH) and ordinary kriging with linear external drift (OKLED) methods. It is shown that, in terms of inherent complexity, measured by Akaike information criterion (AIC), the proposed fuzzy GRNN method has advantages over other techniques, while its accuracy is comparable. Statistical metrics on verification datasets demonstrate the capability and appropriate efficiency of the proposed method to estimate the uncertainty of environmental models.     

Fully coupled elastoplastic hydro-mechanical analysis of unsaturated porous media using a meshfree method

This paper presents the first application of an advanced meshfree method, ie, the edge-based smoothed point interpolation method (ESPIM), in simulation of the coupled hydro-mechanical behaviour of unsaturated porous media. In the proposed technique, the problem domain is spatially discretised using a triangular background mesh, and the polynomial point interpolation method combined with a simple node selection scheme is adopted for creating nodal shape functions. Smoothing domains are formed on top of the background mesh, and a constant smoothed strain, created by applying the smoothing operation over the smoothing domains, is assigned to each smoothing domain. The deformation and flow models are developed based on the equilibrium equation of the mixture, and linear momentum and mass balance equations of the fluid phases, respectively. The effective stress approach is followed to account for the coupling between the flow and deformation models. Further coupling among the phases is captured through a hysteretic soil water retention model that evolves with changes in void ratio. An advanced elastoplastic constitutive model within the context of the bounding surface plasticity theory is employed for predicting the nonlinear behaviour of soil skeleton. Time discretisation is performed by adopting a three-point discretisation method with growing time steps to avoid temporal instabilities. A modified Newton-Raphson framework is designed for dealing with nonlinearities of the discretised system of equations. The performance of the numerical model is examined through a number of numerical examples. The state-of-the-art computational scheme developed is useful for simulation of geotechnical engineering problems involving unsaturated soils.     

Estimation of Pore Volume Compressibility in Carbonate Reservoir Rocks Based on a Classification

Geotechnical and Geological Engineering - This study examined the petrographically classification, petrological and petrophysical characteristics by taking a vast range of carbonate reservoir rock...     

Middle Jurassic palynomorphs of the Dalichai Formation, central Alborz Ranges, northeastern Iran: Paleoecological inferences

Palynological data are used to draw paleoecological inferences for the Dalichai Formation,northeast of Semnan,northeastern Iran.All samples examined yield well-preserved,diverse palynofloras consisting predominantly of miospores;dinoflagellate cysts,foraminiferal test linings,and fungal spores occur as minor constituents.Fifty-four species of spores(37 genera),18species of pollen(9 genera),and 16 species of dinoflagellate cysts(13 genera)are recognized.Co-occurrence of such miospore species with known vertical ranges as Klukisporites variegatus,Sellaspora asperata,Murospora florida,and Concavissimisporites verrucosus suggests a Middle Jurassic(Bajocian-Callovian)age for the host strata,thus corroborating the available paleozoological evidence.Such spore species as Klukisporites,Cyathidites,and Dictyophyllidites known to have been produced by Pterophyta dominate the palynofloras.Thus the contemporaneous coastal vegetation was characterized by predominance of Pterophyta whereas representatives of Ginkgophyta,Pteridospermophyta,Lycophyta,Coniferophyta,and Bryophyta were rarely represented.This reconstruction implies that a moist,warm climate prevailed in northeastern Iran during the Middle Jurassic(Bajocian-Callovian).This is confirmed by occurrence of fungal spores accompanied by such warm water dinoflagellate cysts as Mendicodinium groenlandicum,Pareodinia ceratophora,and Gonyaulacysta jurassica.Abundance of Amorphous Organic Matter(AOM)signifies a shallow,low-energy,dysoxic-anoxic depositional site for the host strata.Furthermore,the ratio of AOM to marine palynomorphs as well as abundance of blade-shaped to eqiudimensional opaque palynomacerals could indicate low sedimentation rate in a shallow,low-oxygenated marine environment.Additionally,occurrence of chorate dinoflagellate cysts(e.g.,Adnatosphaeridium caulleryi)and acritarchs bearing relatively long processes(e.g.,Micrhystridium)possibly suggests deepening upward in the study section.     

Artificial recharge efficiency assessment by soil water balance and modelling approaches in a multi-layered vadose zone in a dry region

To assess recharge through floodwater spreading, three wells, approx. 30 m deep, were dug in a 35-year-old basin in southern Iran. Hydraulic parameters of the layers were measured. One well was equipped with pre-calibrated time domain reflectometry (TDR) sensors. The soil moisture was measured continuously before and after events. Rainfall, ponding depth and the duration of the flooding events were also measured. Recharge was assessed by the soil water balance method, and by calibrated (inverse solution) HYDRUS-1D. The results show that the 15 wetting front was interrupted at a layer with fine soil accumulation over a coarse layer at the depth of approx. 4 m. This seemed to occur due to fingering flow. Estimation of recharge by the soil water balance and modelling approaches showed a downward water flux of 55 and 57% of impounded floodwater, respectively.     

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.     

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.