New insights into the occurrence of the catastrophic Zhaiban slope debris flow that occurred in a dry valley in the Hengduan Mountains in southwest China

Landslides - In 2019, the catastrophic Zhaiban slope debris flow (ZSDF) crushed an open road tunnel in Ganluo County, Sichuan Province, China, causing seven deaths and interrupting traffic flow for...     

Mineralogy and petrography of C asteroid regolith: The Sutter's Mill CM meteorite

Based upon our characterization of three separate stones by electron and X‐ray beam analyses, computed X‐ray microtomography, Raman microspectrometry, and visible‐IR spectrometry, Sutter's Mill is a unique regolith breccia consisting mainly of various CM lithologies. Most samples resemble existing available CM2 chondrites, consisting of chondrules and calcium‐aluminum‐rich inclusion (CAI) set within phyllosilicate‐dominated matrix (mainly serpentine), pyrrhotite, pentlandite, tochilinite, and variable amounts of Ca‐Mg‐Fe carbonates. Some lithologies have witnessed sufficient thermal metamorphism to transform phyllosilicates into fine‐grained olivine, tochilinite into troilite, and destroy carbonates. One finely comminuted lithology contains xenolithic materials (enstatite, Fe‐Cr phosphides) suggesting impact of a reduced asteroid (E or M class) onto the main Sutter's Mill parent asteroid, which was probably a C class asteroid. One can use Sutter's Mill to help predict what will be found on the surfaces of C class asteroids such as Ceres and the target asteroids of the OSIRIS‐REx and Hayabusa 2 sample return missions (which will visit predominantly primitive asteroids). C class asteroid regolith may well contain a mixture of hydrated and thermally dehydrated indigenous materials as well as a significant admixture of exogenous material would be essential to the successful interpretation of mineralogical and bulk compositional data.     

Solitary and rogue waves in Fermi-Dirac plasmas: relativistic degeneracy effects

Ion acoustic (IA) solitary and rogue waves are studied in an unmagnetized plasma consisting of non-degenerate warm ions, relativistically degenerate electrons and positrons. By using the reductive perturbation technique, the evolution of IA solitary waves is described by the Korteweg-de Vries (KdV) equation. However, when the frequency of the carrier wave is much smaller than the ion plasma frequency then the KdV equation is also used to study the nonlinear evolution of modulationally unstable modified IA wavepackets through the derivation of nonlinear Schrödinger equation. It is found that the characteristics of the IA solitary and rogue waves are substantially influenced by the intrinsic plasma parameters. The relevance of the present investigation involving IA solitary and rogue waves in astrophysical plasma environments is also highlighted.     

Spatial variability of soil erodibility and its correlation with soil properties in semi-arid mountainous watershed,Saudi Arabia

Soil erodibility values are best estimated from long-term direct measurements on runoff-plots; however, in lack of field tests, these values can be estimated using relationships based on physico-chemical soil properties. The study objective was to assess the erodibility and its correlation with soil properties. The average erodibility value was estimated 0.043 t ha h ha^?1 MJ^?1 mm^?1. The areas with heavy textured soil and low organic matter content had the lowest values of erodibility. The erodibility decreases as the sand content increases, whereas silt showed a positive correlation. The erodibility factors and its relation to soil properties were evaluated using multiple regression analysis. Results revealed that sand and organic matter content of soil combinedly explained 78% of variation. Altitudinal increases also seem to affect the soil texture. This study has demonstrated that soil properties and erodibility values can be used as assistance for soil conservation practices and modelling of landscape processes.     

Retrieval of tropical forest biomass information from ALOS PALSAR data

Advanced Land Observing Satellite Phased Array L-band Synthetic Aperture Radar (ALOS PALSAR) data from different observation modes were analysed to determine (1) which observation mode most accurately retrieves tropical forest biomass information and (2) whether different modes, when considered together, yield improved results in comparison to identical data-sets analysed independently. We performed regression analysis to estimate above-ground forest biomass using PALSAR backscatter data for natural and planted forests in south-eastern Bangladesh. The coefficient of determination (r ²) was lower or equal to 0.499 (n = 70) when PALSAR data from different observation modes were separately considered, but increased sharply when one class (rubber) is dropped and average backscatter of fine beam single (FBS) and polrimetric (PLR) modes are used in the analysis. The results presented in this article are useful for both regional and global forest biomass inventories and fixing acquisition modes for planned L-band SAR missions.     

Assessment of Land use/land cover Change in the North-West District of Delhi Using Remote Sensing and GIS Techniques

Land is one of the prime natural resources. A city grows not only by population but also by changes in spatial dimensions. Urban population growth and urban sprawl induced land use changes and land transformation. The land transformation is a natural process and cannot be stopped but it can be regulated. Many geographical changes at the urban periphery are associated with the transfer of land from rural to urban purpose. There is an urgent need for fast growing areas like Delhi, which can be easily done by high-resolution remote sensing data. Land use/land cover of North West of Delhi has been analyzed for the time period of 1972?C2003. The remote sensing data used in study is Aster image of 2003 with a spatial resolution of 15?m and other data of 1972 Survey of India (SOI) toposheet at the scale of 1:50,000. Supervised digital classification using maximum likelihood classifier was applied for preparing land use/land cover. A change detection model was applied in ERDAS Imagine to find out the land use/land cover during 1972 to 2003. Eight land use classes was identified but main dominated classes were built up and agricultural land. A drastic change has been recorded during 30 years of time i. e. (1972-2003). In 1972, 92.06% of the land was under agricultural practice, which reduced to 64.71% in 2003. This shows 27.35% decrease in agricultural land in three decades. On the other hand built up area was 6.31% in 1972, which increased to 34% in 2003. One of the main cause of this land use change is the population growth due to the migration in the district from small cities and rural areas of Delhi.     

Mapping of Soil Micronutrients in Kashmir Agricultural Landscape Using Ordinary Kriging and Indicator Approach

Soil nutrient maps based on intensive soil sampling are useful to adopt site-specific management practices. Geostatistical methods have been widely used to determine the spatial correlation and the range of spatial dependence at different sampling scales. If spatial dependence is detected, the modeled semivariograms can then be used to map the interested variable by kriging, an interpolation method that produces unbiased estimates with minimal estimation variance. The objectives of this paper were to examine and map the spatial distribution of the soil micronutrients Cu, Zn, Fe and Mn on an agricultural area in Kupwara, J&K, under temperate climatic conditions. The ordinary kriging was first used to determine the values for the non-sampled locations, and then the indicator approach was used to transform the micronutrient content values into binary values having the mean values of each nutrient as the threshold content. All four elements analyzed showed spatial dependence using the indicator semivariograms. The strength of spatial dependence was assessed using the values of nugget effect and range from the semivariogram, the fitted range values decreased in the order Zn > Cu > Mn > Fe. The spatial dependence of the combination of two or more of the studied micronutrients was also examined using indicator semivariograms. In opposition to spatial analysis of individual microelements, indicator semivariograms obtained for the binary coding of the variables showed a great nugget effect value or a low proportion of sill. The maps for each nutrient obtained using indicator kriging showed some similarity in the spatial distribution, suggesting the delimitation of uniform management areas.     

Calibration of local magnitude scale for Hindukush continental subduction zone

Hindukush is an active subduction zone where at least one earthquake occurs on daily basis. For seismic hazard studies, it is important to develop a local magnitude scale using the data of local seismic network. We have computed local magnitude scale for Hindukush earthquakes using data from local network belonging to Center for Earthquake Studies (CES) for a period of three years, i.e. 2015–2017. A total of 26,365 seismic records pertaining to 2,683 earthquakes with magnitude 2.0 and greater, was used with hypocentral distance less than 600 km. Magnitude scale developed by using this data comes to be M_L = logA + 0.929logr + 0.00298r – 1.84. The magnitude determined through formulated relation was compared with that of standard relation for Southern California and relation developed by the same authors for local network for Northern Punjab. It was observed that Hindukush region has high attenuation as compared to that of Southern California and Northern Punjab which implies that Hindukush is tectonically more disturbed as compared to the said regions, hence, seismically more active as well. We have calculated station correction factors for our network. Station correction factors do not show any pattern which probably owes to the geological and tectonic complexity of this structure. Standard deviation and variance of magnitude residuals for CES network determined using Hutton and Boore scale and scale developed in this study were compared, it showed that a variance reduction of 44.1% was achieved. Average of magnitude residuals for different distance ranges was almost zero which showed that our magnitude scale was stable for all distances up to 600 km. Newly developed magnitude scale will help in homogenization of earthquake catalog. It has been observed that b-value of CES catalog decreases when magnitude is calculated by using newly developed magnitude scale.     

On the possible origin of X-rays in long laboratory sparks

In this paper, based on theoretical estimation of the achievable electric fields during the physical development process of a long spark under different conditions, we show that the encounter of negative and positive streamer fronts just before the final breakdown is one scenario, under which the observed X-ray bursts in long sparks is highly possible. Our calculations show that for example in an 80 cm long rod–sphere air gap at atmospheric pressure with negative lightning impulse breakdown voltage of about 925 kV, electrons are accelerated to values in the range of 100–300 keV during the encounter. Subsequently, these electrons gain more energy moving through the potential gradient of the positive streamer region. The total gain of energy by electrons may reach 300–500 keV. The results also show that negative discharges can produce more energetic electrons than positive. If the suggested mechanism of X-ray production in long sparks is correct, then the X-ray burst may consist of several pulses closely spaced in time. Time resolved photography in simultaneous measurement of X-rays would be able to confirm this prediction.     

A neural network model for liquefaction-induced horizontal ground displacement

The horizontal ground displacement generated by seismically induced liquefaction is known to produce significant damage to engineered structures. A backpropagation neural network model is developed to predict the horizontal ground displacements. A large database containing the case histories of lateral spreads observed in eight major earthquakes is used. The results of this study indicate that the neural network model serves as a reliable and simple predictive tool for the amount of horizontal ground displacement. As more data become available, the model itself can be improved to make more accurate displacement prediction for a wider range of earthquake and site conditions.