ODM: an analytical solution-based tool for reacting oxygen diffusion modelling in mine spoils

A simple one-dimensional analytical solution is presented to model oxygen diffusion through the pore space of mine spoils containing pyrite. The model incorporates volumetric oxygen consumption terms due to pyrite oxidation, oxidation of Fe ²⁺ to Fe ³⁺ and bacterial activity. Based on this analytical solution, a graphical user interface (GUI) tool is programmed and designed in MATLAB software. This tool can be used to model transport of oxygen through the mine spoils either with or without a cap. Results of several simulation scenarios of sensitivity analysis showed a significant change in oxygen concentration with varying effective diffusion coefficient of oxygen transport model and simulation time. Efficiency and flexibility of the tool developed here is verified by modelling oxygen transport through the pore space of a coal waste pile (case A) and a copper mine tailings (case B). Maximum depth of oxygen diffusion is obtained approximately equal to 2 and 1.5 m through the cases A and B, respectively.     

Compressibility and collapse characteristics of arid saline sabkha soils

Arid saline soils are well-distributed over the globe, with a variety of nomenclature. Along the seaboard of the Arabian Gulf, these soils exist widely and are known as “sabkhas”. Despite the cemented and saline characteristics of the sabkha matrix, a recent investigation indicated that flooding the saline sabkha with distilled water in the conventional oedometer apparatus was incapable of producing a sudden reduction in volume and/or a significant collapse. This study proposes a modification to the conventional oedometer on undisturbed sabkha specimens to consolidating specimens under a constant head. Tests were, therefore, conducted on undisturbed sabkha specimens to assess their compressibility and collapse potential whereby percolation of water was commenced under two pressures to evaluate the role of sustained pressure on the collapse mechanisms.

Despite the low compressibility of sabkhas, results of these tests indicated that these arid, saline soils possess a high collapse potential attributable primarily to dissolution of sodium chlorides, leaching of calcium ions and soil grain adjustment. The collapse potential increases with an increase in the acting pressure at which percolation of water takes place. In contrast to other typical soils, the collapse of arid, saline soils is not instantaneous but requires sufficient volume of water to percolate in order to enhance the dissolution of the cementing agents.     

Yield Forecasting of Spring Maize Using Remote Sensing and Crop Modeling in Faisalabad-Punjab Pakistan

Real time, accurate and reliable estimation of maize yield is valuable to policy makers in decision making. The current study was planned for yield estimation of spring maize using remote sensing and crop modeling. In crop modeling, the CERES-Maize model was calibrated and evaluated with the field experiment data and after calibration and evaluation, this model was used to forecast maize yield. A Field survey of 64 farm was also conducted in Faisalabad to collect data on initial field conditions and crop management data. These data were used to forecast maize yield using crop model at farmers’ field. While in remote sensing, peak season Landsat 8 images were classified for landcover classification using machine learning algorithm. After classification, time series normalized difference vegetation index (NDVI) and land surface temperature (LST) of the surveyed 64 farms were calculated. Principle component analysis were run to correlate the indicators with maize yield. The selected LSTs and NDVIs were used to develop yield forecasting equations using least absolute shrinkage and selection operator (LASSO) regression. Calibrated and evaluated results of CERES-Maize showed the mean absolute % error (MAPE) of 0.35–6.71% for all recorded variables. In remote sensing all machine learning algorithms showed the accuracy greater the 90%, however support vector machine (SVM-radial basis) showed the higher accuracy of 97%, that was used for classification of maize area. The accuracy of area estimated through SVM-radial basis was 91%, when validated with crop reporting service. Yield forecasting results of crop model were precise with RMSE of 255 kg ha^?1, while remote sensing showed the RMSE of 397 kg ha^?1. Overall strength of relationship between estimated and actual grain yields were good with R² of 0.94 in both techniques. For regional yield forecasting remote sensing could be used due greater advantages of less input dataset and if focus is to assess specific stress, and interaction of plant genetics to soil and environmental conditions than crop model is very useful tool.     

Statistical landslide susceptibility assessment of the Mansehra and Torghar districts,Khyber Pakhtunkhwa Province,Pakistan

This paper presents laboratory experiments and numerical simulations of effects of submerged obstacles on tsunami-like solitary wave and its run-up. This study was carried out for the breaking and non-breaking solitary waves on 1:19.85 uniform slope which contains a submerged obstacle. New laboratory experiments are performed to describe the mitigation of tsunami amplitude and run-up under the effect of submerged obstacles. We are based on experimental results obtained to validate the numerical model. The numerical modeling using COULWAVE aims essentially to show the effect of the obstacle on the shape of solitary wave and the limit of this effect. Using a multiple nonlinear regression, we have determined a model to estimate height of run-up according to the amplitude of the wave and the obstacle peak depth.     

A new class of bulk viscous universe with time dependent deceleration parameter and Λ-term

A new class of exact solutions of Einstein’s field equations with a bulk viscous fluid for an LRS Bianchi type-Ia obtained by using a time dependent deceleration parameter and cosmological term Λ. The coefficient of bulk viscosity is assumed to be a power function of mass density (ξ=ξ ₀ ρ ⁿ ). We have obtained a general solution of the field equations from which six models of the universe are derived: exponential, polynomial and sinusoidal form respectively. The behaviour of these models of the universe are also discussed in the frame of reference of recent supernovae Ia observations.      

Sorption of lead by chemically modified rice bran

In this work, the effectiveness of native and chemically modified rice bran to remove heavy metal Pb(II) ions from aqueous solution was examined. Chemical modifications with some simple and low-cost chemicals resulted in enhancement of the adsorption capacities and had faster kinetics than native rice bran. Experiments were conducted in shake flasks to monitor the upshot of parameters over a range of pH, initial Pb(II) concentrations and contact times using a batch model study. The sorption capacities q (mg g^?1) increased in the following order: NaOH (147.78), Ca(OH)₂ (139.08), Al(OH)₃ (127.24), esterification (124.28), NaHCO₃ (118.08), methylation (118.88), Na₂CO₃ (117.12) and native (80.24). The utmost uptake capacity q (mg g^?1) was shown by NaOH-pretreated rice bran. The results showed that, using NaOH-modified rice bran, the chief removal of Pb(II) was 74.54 % at pH 5, primary Pb(II) concentration 100 mg L^?1 and contact time 240 min. Equilibrium isotherms for the Pb(II) adsorption were analyzed by Langmuir and Freundlich isotherm models. The Langmuir isotherm model, showing Pb(II) sorption as accessible through the high value of the correlation coefficient (R ² = 0.993), showed a q _max value of 416.61 mg g^?1. The kinetic model illustrated adsorption rates well, depicted by a second order, which gives an indication concerning the rate-limiting step. Thermodynamic evaluation of the metal ion ?G ^o was carried out and led to the observation that the adsorption reaction is spontaneous and endothermic in nature. NaOH chemically modified rice bran was a superb biosorbent for exclusion of Pb(II) and proved to be excellent for industrial applications.     

Application of different clustering approaches to hydroclimatological catchment regionalization in mountainous regions,a case study in Utah State

With respect to the different hydrological responses of catchments, even the adjacent ones, in mountainous regions, there are a great number of motivations for classifying them into homogeneous clusters. These motivations include prediction in ungauged basins (PUB), model parameterization, understanding the potential impact of environmental changes, transferring information from gauged catchments to the ungauged ones. The present study investigated the similarity of catchments through the hydro-climatological pure time-series of a 14-year period from 2001 to 2015. Data sets encompass more than 13,000 month-station streamflow, rainfall, and temperature data obtained from 27 catchments in Utah State as one of the eight mountainous states of the USA. The identification, analysis, and interpretation of homogeneous catchments were investigated by applying the four approaches of clustering, K-means, Ward, and SOM (Self-Organized Map) and a newly proposed Wavelet-Entropy-based (WE-SOM) clustering method. By using two clustering evaluation criteria, 3, 5, and 6 clusters were determined as the best numbers of clusters, depending on the method employed, where each cluster represents different hydro-climatological behaviors. Despite the absence of geographic characteristics in input data matrix, the results indicated a regionalization in agreement with topographic characteristics. Considering the dependency of the hydrological behavior of catchments on the physiographic field aspects and characteristics, WE-SOM method demonstrated a more acceptable performance, compared to the other three conventional clustering methods, by providing more clusters. WE-SOM appears to be a promising approach in catchment clustering. It preserves the topological structure of data which can, as a result, be proofed in a greater number of clusters by dividing data into higher numbers of distinct clusters with similar altitudes of catchments in each cluster. The results showed the aptitude of wavelets to quantify the time-based variability of temperature, rainfall and streamflow, in the way contributing to the regionalization of diverse catchments.     

Behaviour of rainbow trout (Oncorhynchus mykiss) under defensible and indefensible patterns of food delivery

The goal of this study was to investigate the behaviour of rainbow trout (n=30), Oncorhynchus mykiss, in small raceways when either self-feeders (T2) or hand-feeding (t2) were used. The method of food delivery in T2 was defensible while that of t2 was indefensible. Fish in both raceways were subjected to restricted feeding (RF) for 25 days. Food was available in the morning (09:00–10:00) in the downstream area and in the afternoon (16:00–17:00) in the upstream area of the raceways. The results showed that the behaviour of rainbow trout was significantly different under interference competition (T2) for food compared with that under scramble competition (t2). RF in T2 fish limited food availability to meal times when feeding rewards were available while t2 fish only responded to the location of food delivery. The aggressive fish in T2 were dominant, and t2 fish at high densities showed intense social interactions under the indefensible pattern of food distribution; these interactions did not dampen to a minimum level to suppress the development of dominance hierarchies. Further, the stocking density did not break down the dominance hierarchies between the T2 fish. This suggests that decreased efficiency in the search for food or inefficient foraging, induced by interference competition at high densities, affected the behaviour of rainbow trout.