Delineation of groundwater potential zones using remote sensing,GIS, and AHP technique in Tehran–Karaj plain,Iran

Evaluation of groundwater resources in dry areas without enough data is a challenging task in many parts of the world, including Tehran–Karaj plain in Iran, which includes Tehran, the capital city of Iran and Karaj, one of Iran’s biggest cities. Water demand due to increasing agricultural and industrial activities caused many problems in the field of water resources management. In this study, the potential of groundwater resources was evaluated using remote sensing, geographic information system (GIS), and analytic hierarchy process (AHP) for the first time. Digital Elevation Model from Shuttle Radar Topography Mission was used to generate a slope map and drainage density map. Three Landsat-8 satellite images were utilized to provide lineament density and land cover/land use maps. Geological and soil type maps were provided from the Geological Survey and Mineral Explorations of Iran (GSI). Tropical Rainfall Measuring Mission data were used to prepare average annual precipitation map. Discharge values from 102 pumping wells in the time period of 2002–2014 were used to evaluate the results. Seven data layers were prepared, and the geodatabase was made in GIS. The layers and their classes were assigned weights using AHP method. Finally, the layers were overlaid based on their weights, and the potential map of groundwater resources was generated. The area was classified into five zones with very high, high, moderate, low, and very low potentials. The zones covered 5.95, 32.90, 22.70, 10.20, and 28.25% of the study area, respectively. The results showed good agreement with the field data obtained from discharge wells.     

Estimation of inelastic displacement ratio for base‐isolated structures

This study develops a straightforward approximate method to estimate inelastic displacement ratio, C₁ for base‐isolated structures subjected to near‐fault and far‐fault ground motions. Taking into account the inelastic behavior of isolator and superstructure, a 2 degrees of freedom model is employed. A total of 90 earthquake ground motions are selected and classified into different clusters according to the frequency content features of records represented by the peak ground acceleration to peak ground velocity ratio, A_p/V_p. A parametric study is conducted, and effective factors in C₁ (i.e., fundamental vibration period of the superstructure, T_s; postyield stiffness ratio of the superstructure, α_s; strength reduction ratio, R; vibration period of the isolator, T_b; strength of the isolator, Q; ratio of superstructure mass to total mass of the system, γ_m) are recognized. The results indicate that the practical range of C₁ values could be expected for base‐isolated structures. Subsequently, effective parameters are included in simple predictive equations. Finally, the accuracy of the proposed approximate equations is evaluated and verified through error measurement, and comparisons are made in the analyses.     

Risk assessment of extreme air pollution based on partial duration series: IDF approach

The occurrences of extreme pollution events have serious effects on human health, environmental ecosystems, and the national economy. To gain a better understanding of this issue, risk assessments on the behavior of these events must be effectively designed to anticipate the likelihood of their occurrence. In this study, we propose using the intensity–duration–frequency (IDF) technique to describe the relationship of pollution intensity (i) to its duration (d) and return period (T). As a case study, we used data from the city of Klang, Malaysia. The construction of IDF curves involves a process of determining a partial duration series of an extreme pollution event. Based on PDS data, a generalized Pareto distribution (GPD) is used to represent its probabilistic behaviors. The estimated return period and IDF curves for pollution intensities corresponding to various return periods are determined based on the fitted GPD model. The results reveal that pollution intensities in Klang tend to increase with increases in the length of time between return periods. Although the IDF curves show different magnitudes for different return periods, all the curves show similar increasing trends. In fact, longer return periods are associated with higher estimates of pollution intensity. Based on the study results, we can conclude that the IDF approach provides a good basis for decision-makers to evaluate the expected risk of future extreme pollution events.     

IRG2018: A regional geoid model in Iran using Least Squares Collocation

Studia Geophysica et Geodaetica - The aim of this study is to determine an accurate geoid model for Iran based on the Least Squares Collocation method in the framework of the Remove — Compute...     

The application of GPR and ERI in combination with exposure logging and retrodeformation analysis to characterize sinkholes and reconstruct their impact on fluvial sedimentation

This work illustrates the practicality of investigating sinkholes integrating data gathered by ground penetrating radar (GPR), electrical resistivity imaging (ERI) and trenching or direct logging of the subsidence‐affected sediments in combination with retrodeformation analysis. This mutidisciplinary approach has been tested in a large paleosinkhole developed during the deposition of a Quaternary terrace on salt‐bearing evaporites. The subsidence structure, exposed in an artificial excavation, is located next to Puilatos, a village that was abandoned in the 1970s due to severe subsidence damage. Detailed logging of the exposure revealed that the subsidence structure corresponds to an asymmetric sagging and collapse paleosinkhole with no clear evidence of recent activity. The sedimentological and structural relationships together with the retrodeformation analysis indicate that synsedimentary subsidence controlled channel location, the development of a palustrine environment and local changes in the channel pattern. GPR profiles were acquired using an array of systems with different antenna frequencies, including some recently developed shielded antennas with improved vertical resolution and penetration depth. Although radargrams imaged the faulted sagging structure and provided valuable data on fault throw, they did not satisfactorily image the complex architecture of the fluvial deposit. ERI showed lower resolution but higher penetration depth when compared to GPR, roughly capturing the subsidence structure and yielding information on the thickness of the high‐resistivity alluvium and the nature of the underlying low‐resistivity karstic residue developed on top of the halite‐bearing evaporitic bedrock. Data comparison allows the assessment of the advantages and limitations of these complementary techniques, highly useful for site‐specific sinkhole risk management. Copyright © 2016 John Wiley & Sons, Ltd.     

Meteorites from the Lut Desert (Iran)

We present for the first time a detailed report on the discovery of a new meteorite collection region in the Lut Desert, eastern–southeastern Iran, describing its geological, morphological, and climatic setting. Our search campaigns, alongside with the activity of meteorite hunters, yielded >200 meteorite finds. Here, we report on their classification, spatial distribution, and terrestrial weathering. All the collected meteorites are ordinary chondrites (OCs). The most abundant by far are the highly weathered paired H5 distributed in the northwest of Kalut area (central Lut, Kerman dense collection area). The second are well‐preserved paired L5 also found in Kalut region. A detailed study of the geochemistry and mineralogy of selected meteorites reveals significant effects of terrestrial weathering. Fe,Ni metal (hereafter simply metal) and troilite are transformed into Fe oxyhydroxides. A rather unusual type of troilite weathering to pyrite/marcasite is observed in most of the Lut Desert meteorites. Magnetic measurements and X‐ray diffractometry confirm the occurrence of terrestrial weathering products, with the dominance of maghemite, goethite, and hematite. Mobile elements, such as Li, Sr, Mo, Ba, Tl, Th, and U, are enriched with respect to fresh falls. Meanwhile, a decrease in the V, Cr, Co, Rb (and possibly Fe) due to terrestrial weathering is detectable. The total carbon and CaCO₃ is higher than in samples from other hot deserts. The weathering effects observed in the Lut Desert OCs can be used as distinctive indicators to distinguish them from meteorites from other regions of the Earth. Measurements of terrestrial age (¹⁴C) show a range of 10–30 ka, which is in the range of ages reported for meteorites from other hot deserts except the Atacama Desert (Chile). Considering the high potential of the Lut Desert in meteorite preservation, systematic works should lead to the discovery of more samples giving access to interesting material for future studies.     

Comparison of different gravity field implied density models of the topography

Density within the Earth crust varies between 1.0 and 3.0 g/cm³. The Bouguer gravity field measured in south Iran is analyzed using four different regional-residual separation techniques to obtain a residual map of the gravity field suitable for density modeling of topography. A density model of topography with radial and lateral distribution of density is required for an accurate determination of the geoid, e.g., in the Stokes-Helmert approach. The apparent density mapping technique is used to convert the four residual Bouguer anomaly fields into the corresponding four gravity im-plied subsurface density (GRADEN) models. Although all four density models showed good correlation with the geological density (GEODEN) model of the region, the GRADEN models obtained by high-pass filter-ing and GGM high-pass filtering show better numerical correlation with GEODEN model than the other models.     

Large-scale seismic isolation through regulated liquefaction: a feasibility study

Using controlled liquefaction, a seismic isolation technique is introduced by which a large area with dozens of structures can be seismically isolated. The proposed Large Scale Seismic Isolation (LSSI) is in many ways similar to conventional base isolations. The required bearing is provided by a fully undrained pre-saturated liquefiable layer which has substantial vertical stiffness/capacity and minimal lateral stiffness. Moreover, required energy dissipation would be provided through material damping and Biot flow-induced damping within the liquefied layer. LSSI consists of a thick nonliquefiable crust layer and an underlying engineered pre-saturated liquefiable layer bounded by two impermeable thin clay layers. The liquefiable layer should be designed to trigger liquefaction as soon as possible within the early seconds of a design level seismic event. Adopting the energy-based GMP liquefaction theory, optimum gradation of the liquefiable layer is also investigated. It turned out that LSSI would effectively reduce acceleration response spectrum within short to medium periods. Contribution of the proposed LSSI is more pronounced in the case of stronger ground motions such as near field events as well as ground motions with longer return periods.     

Comparison of spatial interpolation methods for gridded bias removal in surface temperature forecasts

All numerical weather prediction (NWP) models inherently have substantial biases, especially in the forecast of near-surface weather variables. Statistical methods can be used to remove the systematic error based on historical bias data at observation stations. However, many end users of weather forecasts need bias corrected forecasts at locations that scarcely have any historical bias data. To circumvent this limitation, the bias of surface temperature forecasts on a regular grid covering Iran is removed, by using the information available at observation stations in the vicinity of any given grid point. To this end, the running mean error method is first used to correct the forecasts at observation stations, then four interpolation methods including inverse distance squared weighting with constant lapse rate (IDSW-CLR), Kriging with constant lapse rate (Kriging-CLR), gradient inverse distance squared with linear lapse rate (GIDS-LR), and gradient inverse distance squared with lapse rate determined by classification and regression tree (GIDS-CART), are employed to interpolate the bias corrected forecasts at neighboring observation stations to any given location. The results show that all four interpolation methods used do reduce the model error significantly, but Kriging-CLR has better performance than the other methods. For Kriging-CLR, root mean square error (RMSE) and mean absolute error (MAE) were decreased by 26% and 29%, respectively, as compared to the raw forecasts. It is found also, that after applying any of the proposed methods, unlike the raw forecasts, the bias corrected forecasts do not show spatial or temporal dependency.