Axially Symmetric Bianchi Type-I Bulk-Viscous Cosmological Models with Time-Dependent Λ and q

The present study deals with spatially homogeneous and anisotropic axially symmetric Bianchi type-I cosmological model with time variable cosmological term Λ in the presence of bulk viscous fluid. The Einstein’s field equations are solved explicitly by time varying deceleration parameter q. Consequences of the four cases of phenomenological decay of Λ have been discussed which are consistent with observations. Physical and kinematical parameters of the models are discussed.     

EPC: Matlab software to estimate Euler pole parameters

The estimation of Euler pole parameters has always been an important issue in global tectonics and geodynamics studies. In addition, the increasing number of permanent GPS stations and the ease of access to their data, along with advances in computers, promise new methods and tools for the estimation and the quantitative analysis of Euler pole parameters. Therefore, we developed the Euler pole calculator software using a set of mathematical algorithms based on the model of tectonic plate motion on a spherical surface. The software is able to calculate the expected velocities for any points located on the earth’s surface given the relevant Euler pole parameters and to estimate the Euler pole parameters given the observed velocities of a set of sites located on the same tectonic plate. Mathematical algorithms and functions of the software are explained in detail.     

On lattice reduction algorithms for solving weighted integer least squares problems: comparative study

Decorrelation or reduction theory deals with identifying appropriate lattice bases that aid in accelerating integer search to find the optimal integer solution of the weighted integer least squares problem. Orthogonality defect has been widely used to measure the degree of orthogonality of the reduced lattice bases for many years. This contribution presents an upper bound for the number of integer candidates in the integer search process. This upper bound is shown to be a product of three factors: (1) the orthogonality defect, (2) the absolute value of the determinant of the inverse of the generator matrix of the lattice, and (3) the radius of the search space raised to the power of the dimension of the integer ambiguity vector. Four well-known decorrelation algorithms, namely LLL, LAMBDA, MLAMBDA, and Seysen, are compared. Many simulated data with varying condition numbers and dimensions as well as real GPS data show that the Seysen reduction algorithm reduces the condition number much better than the other algorithms. Also, the number of integer candidates, before and after the reduction process, is counted for all algorithms. Comparing the number of integer candidates, condition numbers, and orthogonality defect reveals that reducing the condition number and the orthogonality defect may not necessarily result in decreasing the number of integer candidates in the search process. Therefore, contrary to the common belief, reducing the orthogonality defect and condition number do not always result in faster integer least squares estimation. The results indicate that LAMBDA and MLAMBDA perform much better in reducing the number of integer candidates than the other two algorithms, despite having a larger orthogonality defect and condition number in some cases. Therefore, these two algorithms can speed up the integer least squares estimation problem in general and the integer ambiguity resolution problem in particular.     

A Morphological Approach to Predicting Urban Expansion

Many methods for modeling urban expansion are available. Most of these computational models demand a variety of large‐scale environmental and socio‐economic data to investigate the relationship between urban expansion and its driving forces. These requirements are not always fulfilled, particularly in developing countries due to a lack of data availability. This necessitates methods not suffering from data limitations to ease their application. Consequently, this research presents a morphological approach for predicting urban expansion on the basis of spatiotemporal dynamics of urban margins by investigating the interior metropolitan area of Tehran, Iran as a case study. To assess the model's performance, urban expansion is monitored from 1976 to 2012. The proposed model is evaluated to ensure that the prediction performance for the year 2012 is acceptable. For the year 2024, the model predicts Tehran's urban expansion at an overall R² of 88%. Accordingly, it is concluded that: (1) although this approach only inputs urban margins, it represents a suitable and easy‐to‐use urban expansion model; and (2) urban planners are faced with continuing urban expansion.     

On weighted total least-squares with linear and quadratic constraints

A weighted total least-squares (WTLS) approach with linear and quadratic constraints is developed. This method is according to the traditional Lagrange approach to optimize the target function of this problem. The WTLS and constrained total least-squares (CTLS) approach had been distinctively investigated, however, these two problems have not been simultaneously considered yet; furthermore, among the contributions on the CTLS problem, only Schaffrin and Felus considered linear and quadratic constraints together; nevertheless, in many practical examples, some elements of the design/coefficient matrix are fixed and should not be modified and this approach cannot deal with these cases. The main necessity of this research appears after the desirable property of the WTLS approach in preserving the structure of the design matrix was proven by Mahboub. In other words, currently, the WTLS approach is one of the most efficient methods for solving the so-called errors-in-variables model and an attempt for equipping it with constraints seems necessary. Also it is demonstrated that the additional constraints have a ’regularization role’ for ill-conditioned problems and the unconstrained solution suffers from ill-conditioning effects which give it an added advantage over the unconstrained WTLS algorithm. Four geodetic applications indicate the significant of this problem in the presence of colored and white noise in the data.     

Matching authority and VGI road networks using an extended node-based matching algorithm

The amount of volunteered geographic information (VGI) has increased over the past decade, and several studies have been conducted to evaluate the quality of VGI data. In this study, we evaluate the completeness of the road network in the VGI data set OpenStreetMap (OSM). The evaluation is based on an accurate and efficient network-matching algorithm. The study begins with a comparison of the two main strategies for network matching: segment-based and node-based matching. The comparison shows that the result quality is comparable for the two strategies, but the node-based result is considerably more computationally efficient. Therefore, we improve the accuracy of node-based algorithm by handling topological relationships and detecting patterns of complicated network components. Finally, we conduct a case study on the extended node-based algorithm in which we match OSM to the Swedish National Road Database (NVDB) in Scania, Sweden. The case study reveals that OSM has a completeness of 87% in the urban areas and 69% in the rural areas of Scania. The accuracy of the matching process is approximately 95%. The conclusion is that the extended node-based algorithm is sufficiently accurate and efficient for conducting surveys of the quality of OSM and other VGI road data sets in large geographic regions.     

Multivariate approach to estimate colour producing agents in Case 2 waters using first-derivative spectrophotometer data

The complex composition and distribution of colour producing agents (CPAs) in turbid aquatic environments such as the Western Basin of Lake Erie (WBLE) presents a challenge to the application of remote sensing data for differentiating among in-water constituents and estimating their concentrations independently. In this study, multivariate procedures are applied to lab-based spectrophotometer data to estimate the concentration of chlorophyll-a and suspended matters in the WBLE. Principal Component Analysis of first-derivative transformed hyper-spectral data from the spectrophotometer extracted three significant spectral components for each cruise, explaining up to 88% of the spectral variability. Spectral matching using reference spectra indicated that two of the extracted patterns represent signatures of in-water constituents that govern the optical properties of the WBLE, namely, cyanobacteria and diatoms associated with green algae. The spectrophotometer data clearly revealed known spectral features associated with phytoplankton, such as the absorption minima near 550 and 700 nm, which can be attributed to the minimum of absorption and fluorescence of chlorophyll-a, respectively. The method also extracted the absorption peaks due to chlorophyll-a, near 670 nm, and due to phycocyanin, near 620 nm. Principal component regression of chlorophyll-a on the PC scores indicated that 63.4% of variation of chlorophyll-a in the WBLE can be explained by two components. Factors 2 and 3 explain 60% of the joint spatiotemporal variability of suspended matters in the WBLE. The results illustrate the potential of multivariate technique applied to remote sensing data in isolating the patterns that represent constituents in turbid Case 2 waters.     

Carbamazepine Removal from Groundwater: Effectiveness of the TiO2/UV,Nanoparticulate Zero‐Valent Iron,and Fenton (NZVI/H2O2) Processes

Pharmaceutical compounds, widely produced and used all around the world, are partly responsible for the widespread water pollution in the environment. Carbamazepine (CBZ) is an antiepileptic drug that persists in the environment for many years. In the present study, we used the TiO₂/UV, nanoparticulate zero‐valent iron (NZVI), and NZVI/H₂O₂ treatment processes to compare efficiency of CBZ removal from water. Influence of NZVI loading, H₂O₂ concentration, TiO₂ loading, UV lamp power, and the matrix (distilled water and groundwater) on CBZ removal efficiency was evaluated using full factorial design. Results indicated that the NZVI/H₂O₂ process oxidized CBZ within 5 min. On the other hand, the NZVI process alone did not reduce CBZ concentration after 120 min of process time. The NZVI/H₂O₂ process was equally effective in CBZ removal from both distilled water and groundwater whereas the TiO₂/UV process was less effective due to the presence of ions in groundwater. CBZ removal efficiency of the TiO₂/UV process declined 30% when the matrix was changed from distilled water to groundwater. Negative divalent ions, i.e., and , were the main cause of reduction of CBZ removal efficiency from groundwater. It is likely that these two ions adsorb onto, and consequently prevent the superoxide anion and hydroxyl radical OH^? from being generated on, the surface of the TiO₂.     

Pesticide Health Risk Mapping and Sensitivity Analysis of Parameters in Groundwater Vulnerability Assessment

The extensive use of pesticides for increasing the agricultural production is affecting the quality of groundwater. The objectives of this article are to (i) develop pesticide relative leaching ranks for well sites, (ii) develop maps for human health risks due to pesticide applications, and (iii) identify the most significant parameters in pesticide simulations for groundwater vulnerability assessment. The methods include (i) development of acifluorfen relative leaching ranks for 25 well sites using ArcPRZM‐3, (ii) development of health risk maps using model simulated maximum dissolved bentazon concentrations on the basis of USA drinking water quality guidelines, (iii) sensitivity analysis for 14 ArcPRZM‐3 input parameters using the Plackett–Burman method. ArcPRZM‐3 is a user‐friendly system for spatial modeling of pesticide leaching from surface to groundwater. Thirteen acifluorfen relative leaching potential ranks were developed in which the pesticide leaching decrease from 1 to 13. The model predicted ranks for well 34 and well 9 were 2nd and 3rd, respectively, and acifluorfen was detected in both wells during the physical monitoring. The percentages of high health risks in the agricultural areas were 48.38 and 72.72% for Randolph and Independence Counties, respectively. The most significant parameters were thickness of horizon compartment, runoff curve number of antecedent moisture condition II for cropping, soil bulk density, and total application of pesticide. The irrigation, soil permeability, and numerical dispersion could impact the pesticide leaching in soils toward groundwater. The ArcPRZM‐3 system could be efficiently applied for spatial modeling and mapping of pesticide concentrations for groundwater vulnerability assessment on a large scale.     

Seasonal variations in the isotopic composition of leaf and stem water from an arid region of Southeast Asia

Abstract

Stable isotopes are powerful research tools in environmental sciences and their use in ecosystem research is increasing. Stable isotope measurements allow the study of evapotranspiration fluxes, soil evaporation and leaf transpiration phenomena. Soil water and leaf water are the sources of the evapotranspiration that transfers large quantities of water from land to the atmosphere; as a result the isotopic composition of water left in the leaves is modified towards enrichment. Evaporation also changes the isotopic composition of water bodies creating a natural isotopic signal. The isotopic identity of soil water affects the oxygen isotopic signature of leaf and stem water. In this paper we present the isotopic data of bulk leaf water, showing the enrichment in isotopic value of oxygen due to evapotranspiration from leaves in conjunction with the isotopic signal of rainwater and other environmental factors such as humidity and temperature. Results suggest that the variation in the values of δ¹⁸O of Eucalyptus citriodora, Dalbergia sissoo, Melia azedarach and Pinus roxburghii is due to the seasonal changes in the δ¹⁸O of the source water for plants, i. e. rain. It is further observed that leaf water δ¹⁸O values are depleted during the months of July, August and September. This occurs due to the following reasons: (a) the sampling areas receive about 50% of the average annual rain during these months, and (b) rainfalls during these months are isotopically depleted compared with winter rains.

Citation Butt, S., Ali, M., Fazil, M. & Latif, Z. (2010) Seasonal variations in the isotopic composition of leaf and stem water from an arid region of Southeast Asia. Hydrol. Sci. J. 55(5), 844–848.