Analyzing the occurrence of floods and droughts in connection with climate change in Punjab province,Pakistan

Natural Hazards - Frequency and intensity of extreme weather events are immensely changing throughout the world. This study aims to give insight into the changing climatic patterns leading to...     

A GIS-based earthquake damage assessment and settlement methodology

Earthquakes have a greater effect on society than most people think. These effects range from structural damages to economic impacts and fatalities. An earthquake only lasts for a few seconds and the aftershocks may continue for days, but the damage does continue for years. Residential site safety and earthquake damage assessment studies play a crucial role in developing reliable rehabilitation and development programs, improving preparedness and mitigating losses in urbanized areas. The extremely densely populated metropolis of Tehran, which totals of 7,768,561 for 22 districts (according to the 2006 population census), coupled with the fragility of houses and infrastructure, highlight the necessity of a reliable earthquake damage assessment based on essential datasets, such as building resistance attributes, building population, soil structures, streets network and hazardous facilities. This paper presents a GIS-based model for earthquake loss estimation for a district in Tehran, Iran. Damages to buildings were calculated only for the ground shaking effect of one of the region's most active faults, the Mosha Fault in a likely earthquake scenario. Earthquake intensity for each building location was estimated based on attenuation relation and the ratio of damage was obtained from customized fragility curves. Human casualties and street blockages caused by collapsed buildings were taken into account in this study, as well. Finally, accessibility verification found locations without clear passages for temporary settlements by buildings via open streets. The model was validated using the 2003 Bam earthquake damages. The proposed model enables the decision-makers to make more reliable decisions based on various spatial datasets before and after an earthquake occurs. The results of the earthquake application showed total losses as follows: structural damages reaching 64% of the building stock, a death rate of 33% of all the residents, a severe injury rate reaching 27% of the population and street closures upwards of 22% due to building collapse.     

Wavelet-Hilbert transform-based simulation of pulse-like ground motion

In nonlinear dynamic structural analysis, a suite of pulse-like ground motions is required for the performance-based design of structures near active faults. The dissimilarity in the amplitude and frequency content of the earthquake time series referred to nonstationary properties in temporal and spectral, respectively. An approach is proposed based on the nonstationary properties of the far-field records and the seismological information in an event for simulating pulse-like records. The pulse-like earthquake time history is estimated via the superposition of the residual part of the earthquake with the estimated pulse. The wavelet-based Hilbert transform is utilized to characterize the nonstationary properties, the instantaneous amplitude, and frequencies of far-field records to model residual part. The effects of near-fault and pulse are estimated based on the seismological properties of the region. The validation of the procedure is indicated by comparing simulated time-series, response spectra, and Arias intensity with recorded pulse-like records in two different earthquakes in California; the M_w 6.7 1994 Northridge and the M_w 6.5 1979 Imperial valley.

     

Removal of zinc(II) from aqueous solutions using modified agricultural wastes: kinetics and equilibrium studies

In recent years, the need for safe and economical methods to eliminate heavy metals from contaminated waters has necessitated research on the production of low-cost alternatives to commercially available activated carbon. In the present work, in order to enhance the removal of heavy metals from contaminated water, Zizyphus vulgaris wastes were modified chemically to produce an adsorbent rich in carboxylic groups to enhance the removal of heavy metals from contaminated water. Adsorption of Zn(II) ions on the produced adsorbent was then optimized. The optimal ratio for esterification involved the treatment of Z. vulgaris wastes (1 g) with 0.0037 mmol malic acid in the presence of a very small amount of water for 2 h at 140 °C. The maximum values for adsorption capacity, q _max, were 28.7 and 164.6 mg/g on native and modified Z. vulgaris wastes, respectively, at pH 5 and 30 °C with a contact time 2 h and an initial metal ion concentration of 400 mg/L. The equilibrium data were well fitted by the Langmuir and Freundlich adsorption models and demonstrated the significant capacity for Z. vulgaris wastes in the removal of Zn(II) ions from aqueous solutions.     

An improved classification of mineralized zones using particle swarm optimization: A case study from Dagh-Dali ZnPb (±Au) prospect,Northwest Iran

Classification of mineralized areas into different geochemical classes in terms of prospectivity is crucial in the optimal management of exploration risk and costs. Machine learning (ML) algorithms can be served as appropriate alternatives for separating ore-related anomalies due to avoiding the assumptions of statistical distribution and compatibility with the multivariate nature of geochemical features. By hybridizing the ML with a metaheuristic algorithm called particle swarm optimization (PSO), this contribution aims to provide an innovative approach to optimize the classification of geochemical anomalies within the study area. The algorithm, PSO, is inspired by simulating the social behavior of flocks of birds in search of food. The Dagh-Dali ZnPb (±Au) mineral prospect in northwest Iran was subjected as a case study to examine the integrity of the proposed method. Mineralization-related features were extracted by applying principal component analysis (PCA) on metallogenic elements analyzed in soil samples as PC1 and PC2 with elemental assemblages of AgAuPbZn and PbZn, respectively. The silhouette index was employed to estimate the number of underlying geochemical clusters within the adopted feature space. To constitute a comparative analysis, two k-means clustering and PSO-based learning (PSO-L) algorithms were implemented to classify the gridded data of PC1 and PC2 within the study area. The results indicated that the use of PSO has improved the cost function of the clustering problem (up to 4%). Adapting the mineralization classes with the metallogenic evidence demonstrated by boreholes drilled in the study area indicated that PSO-L was superior to the traditional k-means method, improving the accurate estimation of subsurface mineralization classes by 7%. By overcoming the drawbacks of conventional methods for trapping at the local optima, PSO-based learning possesses the potential to highlight weak mineralization signals that are numerically located in boundary conditions. The results show that the proposed approach can serve as an effective medium for optimal modeling of geochemical classes and management of detailed exploration operations.     

Geochemistry and petrology of garnet‐bearing S‐type Shir‐Kuh Granite,southwest Yazd,Central Iran

The Jurassic Shir‐Kuh granitoid batholith in Central Iran intrudes Lower Jurassic sandstones and shales. The batholith consists of three main facies: (i) a granodioritic facies to the north; (ii) a monzogranitic facies spread throughout the batholith; and (iii) a leucogranitic facies along the northwestern margin. The granodiorites are composed mainly of plagioclase, quartz, K‐feldspar, biotite, and some muscovite, garnet, cordierite, ilmenite, zircon, apatite, and monazite. This facies contains variable amounts of restite minerals which are mainly defined by calcic plagioclase cores and small aggregates of biotite. The monzogranites, with mineral assemblages similar to those in the granodiorites, range from relatively mafic (cordierite‐bearing) to felsic (muscovite‐rich) rocks. The leucogranites, exposed as small stock and dykes, consist mainly of quartz, K‐feldspar, and sodic plagioclase. The batholith is peraluminous, calc‐alkaline, and typical of S‐type, as indicated by Na₂O content (2.74%), molecular Al₂O₃/(CaO + Na₂O + K₂O) (A/CNK) ratio (1.17), K₂O/Na₂O ratio (1.39), and isotopic data ([⁸⁷Sr/⁸⁶Sr]_i = 0.715). The rocks are characterized by enrichment in large ion lithophile elements such as Rb, Th and K and depletion in high field strength elements such as Nb and Ti. Chondrite‐normalized rare earth element (REE) patterns are characterized by light rare earth element (LREE) enrichment, with values of (La/Yb)_N between 4.5 and 19.53, unfractionated heavy rare earth element (HREE) with values of (Gd/Yb)_N between 0.98 and 2.88, and a distinct negative Eu. The parental magma of the Shir‐Kuh Granite was derived from a plagioclase‐rich metasedimentary source (local anatexis of metagreywacke) in the crust, with heat input from mantle melt components. The separation of restite crystals from the primary melt followed by the fractional crystallization appears to have been an effective differentiation process in the batholith.     

Comparison of wave equation migration in logpolar and elliptic coordinates

We extend Riemannian wavefield extrapolation to pre- and post-stack migration using 2D logpolar coordinate system in order to enhance imaging of subsurface structures with imaging of dipping reflectors and turning waves. The logpolar coordinate is a coordinate system adequate for propagating both the source and receiver wavefields. The logpolar extrapolation wavenumber introduces an isotropic slowness model stretch to the single square root operator that enables the use of Cartesian finite-difference extrapolators for propagating wavefields in logpolar meshes. Wavefield extrapolation in this coordinate does not require any ray tracing at all and it can be readily extended to high-order finite-difference schemes since it is an analytic extrapolation operator. Two migration examples illustrate the advantages of the logpolar coordinate for imaging complex geological structures. We compared results of post- and pre-stack depth migration in logpolar and elliptic coordinate systems and we found that steeply dipping events can be better imaged in logpolar coordinate than in elliptic coordinate.     

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.