Analyzing and modeling of a large river basin dynamics applying integrated cellular automata and Markov model

Historical and exact information about the land use/land cover change is very important for regional sustainable development. The aim of this paper is to determine the rapid changes in land use/land cover (LULC) pattern due to agriculture expansion, environmental calamities such as flood and government policies over Upper Narmada basin, India. Multi-temporal Landsat satellite images for years 1990, 2000, 2010 and 2015 were used to analyze and monitor the changes in LULC with an overall accuracy of more than 85%. Results revealed a potential decrease in natural vegetation (? 9.52%) due to the expansion of settlement (+ 0.52%) and cropland (+ 9.43%) from 1990 to 2015. In the present study, Cellular Automata and Markov (CA–Markov), an integrated tool was used to project the short-term LULC map of year 2030. The projected LULC (2030) indicated the expansion of built-up area along with the cropland and degradation in the vegetation area. The outcomes from the study can help as a guiding tool for protection of natural vegetation and the management of the built-up area. Additionally, it will help in devising the strategies to utilize every bit of land in the study area for decision makers.     

Magnetostatic models filled with dust and disordered radiation

Magnetostatic models filled with dust and disordered radiation in which the distribution is that of perfect fluid, are obtained. Some physical and geometrical aspects of the models are investigated. In the last section of the paper, the Newtonian analogues of forces are also obtained.     

GIS application to determine the effect of topography on landuse in Ashwani Khad watershed

The landuse status of Ashwani Khad watershed has been obtained using 1RS-ID satellite data for 1999 and further topographic analysis has been carried out using GIS software-ARC/ INFO and ARCVIEW. It has been found that of the total geographical area (85.30 sq. km) of the Ashwani Khad watershed which lies between 30°50′ to 31°N latitude and 77°05′ to 77° 15′E longitude in Himachal Pradesh, 54.53 % constituted wasteland, 33.55% agriculture and least 11.92 % forest. The altitude, aspect and slope have exhibited marked effect on land utilization. Agriculture and wasteland have been found maximum in mid altitude (1300-1500 m) and moderate slopes (13.2-26.4 degree), whereas, agriculture and forest have been maximum in flat and north aspect.     

A comprehensive and quantitative assessment of Raunthi Gad flash flood,Rishi Ganga catchment,central Himalaya,Uttarakhand, India

Natural Hazards - Drought severity is increasing in Southern Africa which is affecting rain-fed agriculture, the main source of livelihood in most countries in this region. The study assessed the...     

Effect of grain packing tightness on strain estimation from the Fry method

How tightly should a sample be packed for strain estimation by the Fry method? We address this issue using synthetic simulations of 900 images such that each image contains 200 randomly distributed grains, but differs from other images with respect to the packing tightness and the degree of sorting. Each image is coaxially distorted by various known strain ratios and the strain estimates from distorted images are obtained by the Fry method. The statistical errors in the strain estimates are found to grow larger with the decrease in the packing tightness irrespective of the level of distortion. We demonstrate that a progressive decrease in the packing tightness results in an increasingly clustered nature of grain center distribution and hence the larger errors. These results, obtained from the synthetic images, are corroborated by two natural examples of sandstone, one loosely packed and the other tightly packed. Based on the results of tests on synthetic and natural examples, we recommend that the Fry method should be used only on those samples that have \({>}30\%\) packing density.     

Chronology of Late Pleistocene environmental changes in the lower Mahi basin,western India

Sediments exposed in the lower Mahi basin at the southern fringe of the Thar Desert, Rajasthan, India, provide evidence of three distinct depositional environments, namely marine, aeolian and fluvial. These have been used to reconstruct Late Pleistocene environmental and tectonic history of the region. Infrared stimulated luminescence (IRSL) chronology of the fluvial and aeolian litho‐units provides evidence of two major fluvial aggradation phases in the region corresponding to Oxygen Isotopic Stages 5 and 3. The basal marine clay is inferred to represent the last interglacial stage and its present elevation at +20 m a.s.l. is attributed to post‐depositional tectonism. Comparison of fluvial records from other regions indicates interhemispherically documented wetter phases during Oxygen Isotope Stages 5 and 3. Copyright © 2000 John Wiley & Sons, Ltd.     

Eroding islands of Gulf of Mannar,Southeast India: a consequence of long-term impact of coral mining and climate change

Natural Hazards - Lightning is one of the most widespread and deadly hazards in Bangladesh. Bangladesh has among the highest death rates of any country. The main objective of this study is to...     

Influence of secondary compression on undrained strength of soft kaolinites

Soft kaolinite deposits of marine origin are encountered as foundation soils in many parts of the world. The well-developed flocculated structure of kaolinite-bearing marine deposits is amenable to alterations from leaching of pore solution salts, loss of overburden, and secondary compression. Secondary compression causes densification of microstructure that may impact the viscous resistance, soil stiffness, and undrained shear strength of kaolinite-bearing marine deposits. This study examines the influence of secondary compression on viscous resistance and constrained stress–strain modulus of soft kaolinites prepared in synthetic seawater and sodium chloride solutions. The impact of secondary compression on undrained shear strength is interpreted from changes in microstructure, percent monovalent cation concentration, viscous resistance, and constrained stress–strain modulus. Kaolinite specimens experience reduction in void space during secondary compression. Breakdown of edge–face (E–F) and edge–edge (E–E) contacts of kaolinite particles during secondary compression and creation of interlocking zones is observed from scanning electron micrograph studies. Breakdown of E–F and E–E contacts is considered responsible for reduction in constrained stress–strain modulus during secondary compression. Concomitant, creation of interlocking zones at particle contacts increases the viscous resistance of microstructure that enhances the undrained shear strength of soft kaolinites.     

A Novel Methodology to Classify Soil Liquefaction Using Deep Learning

In this research, deep learning (DL) model is proposed to classify the soil reliability for liquefaction. The applicability of the DL model is tested in comparison with emotional backpropagation neural network (EmBP). The database encompassing cone penetration test of Chi–Chi earthquake. This study uses cone resistance (q_c) and peck ground acceleration as inputs for prediction of liquefaction susceptibility of soil. The performance of developed models has been assessed by using various parameters (receiver operating characteristic, sensitivity, specificity, Phi correlation coefficient, Precision–Recall F measure). The performance of DL is excellent. Consistent results obtained from the proposed deep learning model, compared to the EmBP, indicate the robustness of the methodology used in this study. In addition, both the developed model was also tested on global earthquake data. During validation on global data, both the models shows good results based on fitness parameters. The developed classification models a simple, but also efficient decision-making tool in engineering design to quantitatively assess the liquefaction potential. The finding of this paper can be further used to capture the relationship between soil and earthquake parameters.