Comparison of univariate and multivariate geographically weighted regression for estimating air temperature over Iran

Station recording air temperature (T_a) has limited spatial coverage, especially in unpopulated areas. Since temperature can change greatly both spatially and temporally, stations data are often inadequate for meteorology and subsequently climatology studies. Time series of moderate-resolution imaging spectroradiometer (MODIS) land surface temperature (T_s) and normalized difference vegetation index (NDVI) products, combined with digital elevation model (DEM), albedo from Era-Interim and meteorological data from 2006 to 2015, were used to estimate daily mean air temperature over Iran. Geographically weighted regression was applied to compare univariate and multivariate model accuracy. In the first model, which only interfered with land surface temperature (LST), the results indicate a weak performance with coefficient of determination up to 91% and RMSE of 1.08 to 2.9 °C. The mean accuracy of a four-variable model (which used LST, elevation, slope, NDVI) slightly increased (6.6% of the univariate model accuracy) when compared to univariate model. RMSE dropped by 19% of the first model. By addition albedo in the third model, the coefficient of determination increased significantly. This increase was 32% of the univariate model and 23.75% of the 4-variable model accuracy. The statistical comparison between the three models revealed that there is significant improvement in air estimation by applying the geographically weighted regression (GWR) method with interfering LST, NDVI, elevation, slope, and albedo with mean absolute RMSE of 0.62 °C and mean absolute R² of 0.99. In order to better illustrate the third model, t values were spatially mapped at 0.05 level.     

Determination of sand dune characteristics through geomorphometry and wind data analysis in central Iran (Kashan Erg)

The combination of wind measurements and remotely sensed geomorphometry indices provides a valuable resource in the study of desert landforms, because arduous desert environments are difficult to access. In this research, we couple wind data and geomorphometry to separate and classify different sand dunes in Kashan Erg in central Iran. Additionally, the effect of sand-fixing projects on sand dune morphology was assessed using geomorphometry indices (roughness, curvature, surface area, dune spacing and dune height). Results showed that a Digital Elevation Model of the National Cartographic Center of Iran (NCC DEM) with 10-m resolution and accuracy of 54% could discriminate geomorphometry parameters better than the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data with 30-m resolution and Shuttle Radar Topography Mission (SRTM) data with 90-m resolution and 45.2 and 1.6% accuracy, respectively. Low classification of SRTM DEM was associated with too many non-value points found in the DEM. Accuracy assessment of comparison ground control points revealed that ASTER DEM (RMSE = 4.25) has higher accuracy than SRTM and NCC DEMs in this region. Study of curvature showed that transverse and linear sand dunes were formed in concave topography rather than convex. Reduced slopes in fixed sand dunes were established due to wind erosion control projects. Measurements of dune height and spacing show that there is significant correlation in compound dunes (R ² = 0.546), linear dunes (R ² = 0.228) and fixed dunes (R ² = 0.129). In general, the height of dunes in Kashan Erg increases from the margin of the field to the center of the field with a maximum height of 120 m in star dunes. Analysis of wind data showed that sand drift potential is in low-medium class in Kashan Erg. Linear sand dunes in Kashan Erg show that they are following a global trend in forming of these. Finally, established of geomorphometry method in dune classification will help researchers to identify priority of land management and performance assessment of sand dunes fixing projects in arid arduous environment.     

The crystalline complexes of Hamadan (Sanandaj–Sirjan zone, western Iran): metasedimentary Mesozoic sequences affected by Late Cretaceous tectono-metamorphic and plutonic events

The Hamadan area is characterised by various metamorphic rocks where the slates yielded Jurassic fossils. The entire column, representing the Mesozoic from at least the Jurassic to the Mid-Cretaceous, has been affected by tectono-metamorphic events and the emplacement of Late Cretaceous granitic rocks. A timing of these events is based on the ⁴⁰K–⁴⁰Ar ages carried mainly on separated amphiboles, biotites and muscovites, and interpreted as the ages of their isotopic closure. Results are ranging between 91 and 70 Ma. To cite this article: A. Baharifar et al., C. R. Geoscience 336 (2004).

Résumé

La région de Hamadan expose des roches métamorphiques dont les termes les moins transformés contiennent des fossiles jurassiques. Au cours du Crétacé supérieur, elle a été affectée par un événement tectono-métamorphique régional et elle a été le siège d'une activité plutonique. Les résultats des datations ⁴⁰K–⁴⁰Ar des amphiboles et des micas séparés des roches métamorphiques et plutoniques qui s'étagent entre 91 et 70 Ma montrent l'importance de ces événements et leur étalement au cours du Crétacé supérieur. Pour citer cet article : A. Baharifar et al., C. R. Geoscience 336 (2004).     

Lithological facies identification in Iranian largest gas field: A comparative study of neural network methods

Determination of different facies in an underground reservoir with the aid of various applicable neural network methods can improve the reservoir modeling. Accordingly facies identification from well logs and cores data information is considered as the most prominent recent tasks of geological engineering. The aim of this study is to analyze and compare the five artificial neural networks (ANN) approaches with identification of various structures in a rock facies and evaluate their capability in contrast to the labor intensive conventional method. The selected networks considered are Backpropagation Neural Networks (BPNN), Radial Basis Function (RBF), Probabilistic Neural Networks (PNN), Competitive Learning (CL) and Learning Vector Quantizer (LVQ). All these methods have been applied in four wells of South Pars field, Iran. Data of three wells were employed for the networks training purpose and the fourth one was used to test and verify the trained network predictions. The results have demonstrated that all approaches have the ability of facies modeling with more than 65% of precision. According to the performed analysis, RBF, CL and LVQ methods could model the facies with the accuracy between 66 and 68 percent while PNN and BPNN techniques are capable of making predictions with more than 72% and 88.5% of precision, respectively. It can be concluded that the BPNN can generate most accurate results in comparison to the other type of networks but it is important to note that the other factors such as consuming the amount of time taken, simplicity and the less adjusted parameters as well as the acquired precisions should be considered. As a result, the model evaluation analysis used in this study can be useful for prospective surveys and cost benefit facies identification.     

A Hybrid Particle Swarm Optimization and Genetic Algorithm for Model Updating of A Pier-Type Structure Using Experimental Modal Analysis

China Ocean Engineering - Conventional design of pier structures is based on the assumption of fully rigid joints. In practice, the real connections are semi-rigid that cause changes in dynamic...     

Seismic piezocone interpretation for shear wave velocity (<Emphasis Type="Italic">V</Emphasis><Subscript>S</Subscript>) determination in the Persian Gulf

Shear wave velocity is one of the important factors representing the dynamic characteristics of soil layers. Hence, many researchers have focused their studies on determining shear wave velocity by direct field measurements or expressions developed by other soil parameters. The shear module and damping ratio of the soil layers also play a similar role in the majority of dynamic soil response analyses. Nevertheless, since they have to be measured in the laboratory by resonant column or cyclic triaxial tests on undisturbed samples, the possibility of preparing such samples and the reliability of the obtained results are of great concerns. In the present study, great effort has been made to determine the above dynamic factors by means of field data obtained from a versatile instrument, namely the seismic piezocone (SPCT_U), and to derive expressions correlating them with some parameters obtainable by much simpler instruments. The reliability of laboratory measurements on undisturbed samples is also evaluated. The seismic piezocone test apparatus has been employed to evaluate the soil properties at 1-m depth intervals by means of measuring tip resistance, sleeve resistance, pore pressure and shear wave velocity. The shear module and the damping ratio are calculated using field data. Meanwhile, in order to assess the laboratory measurements of these parameters, some resonant column tests and cyclic triaxial tests on undisturbed samples of the same soil layers have been carried out. In order to compare the field results of shear modulus and damping ratios with those obtained from laboratory tests, the influences of the soil nature and sample disturbance on the conventional laboratory methods are evaluated and discussed. The shear wave velocity is correlated to overburden pressure and the corrected tip resistance for two groups of fine soils, namely silty clays and carbonate clayey silts, which mainly cover the areas under study in this project, are located in southern parts of Iran near the Persian Gulf. According to the results of the present study, there are narrow limits of shear modulus regarding soils for which the laboratory tests and the field measurements yield approximately the same shear modulus. This limit of shear modulus is about 30–50(MPa) for clay deposits and 70–100 (MPa) for sandy deposits. Also the shear wave velocity can be calculated by a simple expression from total overburden pressure and the tip resistance of simple cone penetration test results conventionally available in many soil explorations prior to engineering practices. However, if the pore pressure inside the saturated soil deposits can be measured by a piezocone apparatus, the shear wave velocity may be calculated using another suggested equation in terms of effective overburden pressure in the present study. Regarding the shear module and the damping ratio, due to the disturbances of the stiff deposits in the sampling process and great deviations of laboratory results from field results, the laboratory measurements of these parameters out of the above limits are not recommended.     

Unsupported advance length in tunnels constructed using New Austrian Tunnelling Method and ground surface settlement

Tunnels constructed using New Austrian Tunnelling Method (NATM) are always based on certain round (unsupported) advance lengths, after which, the temporary lining is placed. The settlement of the ground surface resulting from such construction is of high significance in design and practice. The existing data in this respect, however, is scarce. It is the aim of this paper to propose a semi‐analytical procedure based on three‐dimensional finite element analyses to predict the maximum surface settlement of the ground in NATM tunnels under different combinations of tunnel diameter, overburden depth, round length and soil and lining properties. The comparison of the results with three case histories of real tunnels reveals reasonable accuracy of the present solution. Copyright © 2012 John Wiley & Sons, Ltd.     

Hybrid stochastic finite fault modeling of 2003, M6.5, Bam earthquake (Iran)

Accelerographic time series of the M ^∗6.5 Bam (Iran) earthquake of December 26, 2003, are used to calibrate the source and propagation path characteristics based on a hybrid stochastic approach, which includes stochastic finite fault and analytical modeling. Estimation of source characteristics is based on the calibration of finite-fault modeling to near-source observed time series, while propagation characteristics are estimated using far-field recorded ones. The distance-dependent Kappa factor is obtained from the slope of smoothed amplitude of acceleration Fourier spectrum at higher frequencies. The estimated zero-distance Kappa value is 0.06. Calibration based on near-source time series indicates a stress drop of 130 bars for the Bam earthquake. The strong impulsive long-period motion, recorded at the only near-source station, is modeled using analytical modeling of Mavroeidis and Papageorgiou (2003).     

Vibration screening by trench barriers,a review

This paper provides a review of various investigations concerned with vibration isolation using trench barriers and factors affecting their performance, also extracts design recommendations, because there is no exact conclusion of researches in this field. Vibrations induced by different sources can be seriously harmful to structures and occupants. Geometrical parameters, soil characteristics, and filling material properties can affect a barrier’s performance. Investigators have applied analytical approach, finite element, boundary element, experimental, and field studies to identify relevant factors. Various geometrical parameters affecting trench’s isolation level were examined, among which depth of trench was found to be the most important, but in most cases, the width of the trench and source-barrier distance have a low effect. Shear-wave velocity ratio of filling material and surrounding soil has the most significant role of all material properties. Using high-energy-absorbing materials can lead to better isolation. The majority of studies consider soil and filling material’s behavior to be elastic, so changes in loading amplitude have no effect on vibration reduction. Finally, among special cases in vibration isolation by trenches, non-rectangular and multiple ones found to be economically satisfying and well-isolating barriers.