Effects of Microparameters on Macroparameters of Flat-Jointed Bonded-Particle Materials and Suggestions on Trial-and-Error Method

The aims of this paper are to analyze the effects of microparameters on macroparameters of flat-jointed bonded-particle materials of particle flow code in two dimensions (PFC2D) and improve the efficiency of trial-and-error method in calibration of microparameters. The trial-and-error method is always used to calibrate the microparameters for a PFC2D model, but it is time-consuming and empirical. To improve the efficiency of the trial-and-error method, the effects of microparameters on macroparameters need to be analyzed. By using the trial-and-error method, a desirable set of microparameters for a uniaxial compression PFC2D model (with a flat-joint contact model as the contact model) of limestone were calibrated to match the macroscopic properties obtained from laboratory tests. Based on the calibration set of microparameters, effects of microparameters on macroparameters of the PFC2D model were studied by the orthogonal design method. On this basis, a flowchart of calibrating microparameters via trial-and-error method was proposed. This flowchart was used to calibrate the microparameters of granite. The macroparameters and failure characteristics determined from numerical simulation were very similar to those of laboratory tests, confirming the effectiveness of the proposed flowchart.     

Landslide susceptibility mapping of the Sera River Basin using logistic regression model

Of the natural hazards in Turkey, landslides are the second most devastating in terms of socio-economic losses, with the majority of landslides occurring in the Eastern Black Sea Region. The aim of this study is to use a statistical approach to carry out a landslide susceptibility assessment in one area at great risk from landslides: the Sera River Basin located in the Eastern Black Sea Region. This paper applies a multivariate statistical approach in the form of a logistics regression model to explore the probability distribution of future landslides in the region. The model attempts to find the best fitting function to describe the relationship between the dependent variable, here the presence or absence of landslides in a region and a set of independent parameters contributing to the occurrence of landslides. The dependent variable (0 for the absence of landslides and 1 for the presence of landslides) was generated using landslide data retrieved from an existing database and expert opinion. The database has information on a few landslides in the region, but is not extensive or complete, and thus unlike those normally used for research. Slope, angle, relief, the natural drainage network (including distance to rivers and the watershed index) and lithology were used as independent parameters in this study. The effect of each parameter was assessed using the corresponding coefficient in the logistic regression function. The results showed that the natural drainage network plays a significant role in determining landslide occurrence and distribution. Landslide susceptibility was evaluated using a predicted map of probability. Zones with high and medium susceptibility to landslides make up 38.8 % of the study area and are located mostly south of the Sera River Basin and along streams.     

Flash flood vulnerability assessment for small catchments with a material flow approach

Destructions resulted from natural hazards like earthquake, landslide, or flood in the urban roads and lifelines introduce their negative effects including the psychological damage to citizens as well as decreased urban functions that usually last for a long time. Thus, a quick and efficient recovery of infrastructures, lifelines, and service-providing facilities along with reducing reconstruction costs and time are essential. This paper proposed an approach that consists of four models for forming an algorithm in order to quantitating and integrating of the criteria that have decisive influence in the recovery of urban roadways after a natural disaster. Meanwhile, to aggregate and conclude the data that are collected by means of presented functions and formulations, we applied fuzzy VIKOR technique as a compromise ranking method. The model outputs a priority list showing the revival of which urban paths stands in higher priority for recovery operation after a natural disaster. Results show that not only the model is able to precisely quantize the selected criteria and provide an action plan for post-event recovery prioritization, but also it offers an appropriate order of transportation roads priority for recovery operations. Finally, the results from the recovery model application to a roadway system in Tehran area are provided.     

An approach for estimating the largest probable tsunami from far-field subduction zone earthquakes

Following the recent unexpected earthquake events of 2004 and 2011, it can be cautiously extrapolated that all major subduction zones bearing the capacity to produce mega-earthquake events will eventually do so given enough time, irrespective of the lack of such in the relatively short historical record. This notion has led to an effort of assigning maximum earthquake magnitudes to all major subduction zones, either based on geological constraints or based on size–frequency relations, or a combination of both. In this study, we utilize the proposed maximum magnitudes to assess tsunami hazard in Central California in the very long return periods. We also assessed tsunami hazard following an alternative methodology to calculate maximum magnitudes, which uses scaling relations for subduction zone earthquakes and maximum fault rupture scenarios found in literature. A sensitivity analysis is performed for Central California that is applicable to any coastal site in the Pacific Rim and can readily provide a strong indication for which subduction zones beam the most energy toward a study area. The maximum earthquake scenarios are then narrowed down to a few candidates, for which the initial conditions are examined in more detail. The chosen worst-case scenarios for Central California stem from the Alaska–Aleutian subduction zone that beams more energy and generates the biggest amplitude waves toward the study area. The largest tsunami scenario produces maximum free surface elevations of 15 m and run-up heights greater than 20 m.     

Relationships between typhoons,climate and crime rates in Taiwan

The literature indicates climate change is likely to cause more frequent and intense extreme weather events along with higher temperatures and altered precipitation. Taiwan frequently suffers from extremes in the form of typhoons, and their effects threaten both social stability and public security. Temperature effects through climate change are also expected to alter crime rates. We examine the immediate and longer-run impacts of typhoons and other climate variables on crime rates in Taiwan. The immediate results suggest that typhoon intensity has a significantly negative influence on rates of crime, including all violent crimes and automobile thefts. They also show that warmer temperatures have a strong positive effect on all violent crimes and all the subtypes of violent crimes. In addition, longer duration typhoons increase the immediate rates of all violent crimes, automobile thefts and muggings while decreasing the rate of burglaries. In the long run, we find that typhoon intensity, duration and landfall have persistent, lagged effects on crime that vary from negative to positive. For example, strong-intensity typhoons have significantly negative lagged effects on crimes 3–5 months in the future but positive lagged effects on crimes in future months 6–9. Finally, projections under the IPCC climate change scenarios show all violent crimes will increase.     

Forecasting flood-prone areas using Shannon’s entropy model

With regard to the lack of quality information and data in watersheds, it is of high importance to present a new method for evaluating flood potential. Shannon’s entropy model is a new model in evaluating dangers and it has not yet been used to evaluate flood potential. Therefore, being a new model in determining flood potential, it requires evaluation and investigation in different regions and this study is going to deal with this issue. For to this purpose, 70 flooding areas were recognized and their distribution map was provided by ArcGIS10.2 software in the study area. Information layers of altitude, slope angle, slope aspect, plan curvature, drainage density, distance from the river, topographic wetness index (TWI), lithology, soil type, and land use were recognized as factors affecting flooding and the mentioned maps were provided and digitized by GIS environment. Then, flood susceptibility forecasting map was provided and model accuracy evaluation was conducted using ROC curve and 30% flooding areas express good precision of the model (73.5%) for the study area.     

Reconstruction of specific mass balance for glaciers in Western Himalaya using seasonal sensitivity characteristic(s)

Seasonal sensitivity characteristics (SSCs) were developed for Naradu, Shaune Garang, Gor Garang and Gara glaciers, Western Himalaya to quantify the changes in mean specific mass balance using monthly temperature and precipitation perturbations. The temperature sensitivities were observed high during summer (April–October) and precipitation sensitivities during winter months (November–March), respectively. The reconstructed mass balance correlates well with the field and remote sensing measurements, available between 1980 and 2014. Further, SSCs were used with the monthly mean temperatures and precipitation estimates of ERA 20CM ensemble climate reanalysis datasets to reconstruct the specific mass balance for a period of 110 years, between 1900 and 2010. Mass balance estimates suggest that the Shaune Garang, Gor-Garang and Gara glaciers have experienced both positive and negative mass balance, whereas the Naradu glacier has experienced only negative mass balance since 1900 AD. Further, a cumulative loss of \(-133 \pm 21.5\) m.w.e was estimated for four glaciers during the observation period. This study is the first record from Indian Himalaya in evaluating the mass balance characteristics over a century scale.     

First discovery of fossil winged seeds of <Emphasis Type="BoldItalic">Pinus</Emphasis> L. (family Pinaceae) from the Indian Cenozoic and its palaeobiogeographic significance

The occurrences of Pinus L. (family Pinaceae) megafossils (cones and leaf remains) have been abundantly documented from the Cenozoic sediments of eastern Asia (Japan and China), but none has been confirmed from the Indian Cenozoic till date. Here, we describe Pinus arunachalensis Khan and Bera, sp. nov. on the basis of seed remains from the middle to late Miocene Siwalik sediments of the Dafla Formation exposed around West Kameng district in Arunachal Pradesh, eastern Himalaya. Seeds are winged, broadly oblong to oval in outline, 1.3–1.5 cm long and 0.4–0.6 cm broad (in the middle part), located basipetally and symmetrically to wing, cellular pattern of wing is seemingly undulatory and parallel with the long axis of the wing. So far, this report provides the first ever fossil record of Pinus winged seeds from India. This record suggests that Pinus was an important component of tropical-subtropical evergreen forest in the area during the Miocene and this group subsequently declined from the local vegetation probably because of the gradual intensification of MSI (monsoon index) from the Miocene to the present. We also review the historical phytogeography and highlight the phytogeographic implication of this genus.     

Evaluation of four supervised learning methods for groundwater spring potential mapping in Khalkhal region (Iran) using GIS-based features

One important tool for water resources management in arid and semi-arid areas is groundwater potential mapping. In this study, four data-mining models including K-nearest neighbor (KNN), linear discriminant analysis (LDA), multivariate adaptive regression splines (MARS), and quadric discriminant analysis (QDA) were used for groundwater potential mapping to get better and more accurate groundwater potential maps (GPMs). For this purpose, 14 groundwater influence factors were considered, such as altitude, slope angle, slope aspect, plan curvature, profile curvature, slope length, topographic wetness index (TWI), stream power index, distance from rivers, river density, distance from faults, fault density, land use, and lithology. From 842 springs in the study area, in the Khalkhal region of Iran, 70 % (589 springs) were considered for training and 30 % (253 springs) were used as a validation dataset. Then, KNN, LDA, MARS, and QDA models were applied in the R statistical software and the results were mapped as GPMs. Finally, the receiver operating characteristics (ROC) curve was implemented to evaluate the performance of the models. According to the results, the area under the curve of ROCs were calculated as 81.4, 80.5, 79.6, and 79.2 % for MARS, QDA, KNN, and LDA, respectively. So, it can be concluded that the performances of KNN and LDA were acceptable and the performances of MARS and QDA were excellent. Also, the results depicted high contribution of altitude, TWI, slope angle, and fault density, while plan curvature and land use were seen to be the least important factors.     

Statistical analysis and source rock of the Minim-Martap plateau bauxite,Cameroon

The Minim-Martap plateau bauxite deposit, located between the Minim and the Martap villages, is one of the 11 plateaus within the Minim-Martap bauxite region. The plateau has an elevation of 1294 m above sea level, with three to more 30 m thickness of bauxite horizon. These plateaus were formed as result of supergene weathering of volcanic rocks occurring as dissected flow basalt landscapes that form relatively flat plateau rising steeply from the surrounding granites. The bauxite deposit of the plateau is lateritic, with the surface of the plateau been completely covered by indurated caps. Seventeen bauxite samples were collected from the plateau and prepared for geochemical analysis. Whole rock analysis was carried out using the X-ray Fluorescence technique and ICP-MS was used for trace elements investigation. Statistical analysis reveals that average values of Al₂O₃ (54.87%), Fe₂O₃ (7.17%), SiO₂ (2.44%), and TiO₂ (4.54%) indicate the plateau bauxite deposit is an of a world class standard with very little impurities compared to the standard major element contents of bauxite (>?40% A1₂O₃, less than <?20% Fe₂O₃, and less than <?8% combined SiO₂). Abundant trace elements include Zr, Ce, Sr, V, Ba, La, Nd, Ga, and Nb. Weathering due to chemical alteration indices using the Ruxton ratio and CIA approaches revealed the plateau have undergone intense weathering process that formed the bauxite deposit. Three different classification systems indicate it as a low iron-rich bauxite deposit. Precursor rock investigation indicates the origin of the bauxite is mafic, basaltic andesite igneous rocks with intermediate pH (basic–acidic characteristic).