Causes of large-scale landslides in the Lesser Himalaya of central Nepal

Geologically and tectonically active Himalayan Range is characterized by highly elevated mountains and deep river valleys. Because of steep mountain slopes, and dynamic geological conditions, large-scale landslides are very common in Lesser and Higher Himalayan zones of Nepal Himalaya. Slopes along the major highways of central Nepal namely Prithvi Highway, Narayangadh-Mugling Road and Tribhuvan Highway are considered in this study of large-scale landslides. Geologically, the highways in consideration pass through crushed and jointed Kathmandu Nappe affected by numerous faults and folds. The relict large-scale landslides have been contributing to debris flows and slides along the highways. Most of the slope failures are mainly bechanced in geological formations consisting phyllite, schist and gneiss. Laboratory test on the soil samples collected from the failure zones and field investigation suggested significant hydrothermal alteration in the area. The substantial hydrothermal alteration in the Lesser Himalaya during advancement of the Main Central Thrust (MCT) and thereby clay mineralization in sliding zones of large-scale landslide are the main causes of large-scale landslides in the highways of central Nepal. This research also suggests that large-scale landslides are the major cause of slope failure during monsoon in the Lesser Himalaya of Nepal. Similarly, hydrothermal alteration is also significant in failure zone of the large-scale landslides. For the sustainable road maintenance in Nepal, it is of utmost importance to study the nature of sliding zones of large-scale landslides along the highways and their role to cause debris flows and slides during monsoon period.     

Biodiversity Information System for North East India

Abstract

Biodiversity is the variety and variability of flora and fauna in an ecosystem. Articulated into genes, species, and ecosystem, it provides the biological plasticity needed by life on the earth to adapt changes. As we approach towards the forthcoming century, the earth's diversity of life is increasingly at risk through a combination of mostly human induced factors leading to erosion of genetic resources, extinction of species and collapse of ecological systems. Insitu conservation, biotechnology tools for conservation and prospecting, species habitat relationship and following evolutionary process of speciation are some of the challenges. India being one of the mega biodiversity centers of the world is also known for its traditional knowledge of conservation. The varied regions of the country, with unique floristic and faunal richness, their vastness, endemism, heterogeneity and also inaccessibility of large areas have necessitated creation of authentic baseline database on biodiversity. With the advent of Internet based Geographic Information System technology an effort is being made to harness the power of these technologies to facilitate biodiversity conservation.

The information system organizes the data base generated under the project on “Biodiversity Characterization at landscape level using remote sensing and Geographic Information System in North East India” of the Department of Biotechnology and Department of Space, Government of India. The entire database is organized in object oriented relational database using Oracle as Backend and Visual Basic, ASP as front end. The web enabling part comes through uploading the entire spatial and non‐spatial data at a common platform using ArcSDE and ArcIMS The spatial characterization of landscape structures and its linkages with attribute information on the floristic composition, economic valuation, endemism are presented in Biodiversity Information System on a sharable environment. It is a step to evolve with new a mechanism to conserve biological diversity at local, regional and national level.     

Automated classification of sloan digital sky survey (SDSS) stellar spectra using artificial neural networks

Automated techniques have been developed to automate the process of classification of objects or their analysis. The large datasets provided by upcoming spectroscopic surveys with dedicated telescopes urges scientists to use these automated techniques for analysis of such large datasets which are now available to the community. Sloan Digital Sky Survey (SDSS) is one of such surveys releasing massive datasets. We use Probabilistic Neural Network (PNN) for automatic classification of about 5000 SDSS spectra into 158 spectral type of a reference library ranging from O type to M type stars.     

Phosphorus fractionation in sediments of the Pichavaram mangrove ecosystem,south-eastern coast of India

Present study examined phosphorus dynamics through delineation of source as well as availability of phosphorus and its fractionation within the intertidal sediments of Pichavaram mangrove ecosystem. Twelve sediment samples and two cores were collected from the mangrove forest along with estuarine area (Vellar-Coleroon) during January 2005. Sediments were analyzed for total phosphorus and its fractionation using operationally defined chemical sequential extraction scheme (SEDEX). Dissolved phosphorus (in water) and total phosphorus (in sediments) concentrations were high in the Vellar region of Pichavaram mangrove area due to pollution load from nearby villages and agricultural fields. However, the spatial variation in dissolved phosphorus were insignificant (at significance level = 0.05). The results for the phosphorus fractionation (post-tsunami) were compared with earlier studies (pre-tsunami). It was observed that all phosphorus fractions (except adsorbed-phosphorus) showed a highly significant (at significance level = 0.05) increase in concentration after the tsunami event. There was significant decrease in the adsorbed phosphorus concentration as a result of tsunami. The changes were more pronounced for organic phosphorus which increased by almost twofold following the event. These variations were attributed to change in salinity, increase in dissolved oxygen as well as the retreat of tsunami water carrying the waste load. The vertical distribution of phosphorus through core sediments showed that mixing after tsunami had altered the different phosphorus fraction and its availability. Overall, the study indicated that the fluvial weathering along with litter degradation and anthropogenic sources controlled the biogeochemistry of phosphorus in this mangrove ecosystem. Observed changes in the concentrations are a result of altered physico-chemical characteristics caused by tsunami.     

Regional-scale landslide activity and landslide susceptibility zonation in the Nepal Himalaya

Landslide susceptibility zonation mapping is a fundamental procedure for geo-disaster management in tropical and sub-tropical regions. Recently, various landslide susceptibility zonation models have been introduced in Nepal with diverse approaches of assessment. However, validation is still a problem. Additionally, the role of various predisposing causative parameters for landslide activity is still not well understood in the Nepal Himalaya. To address these issues of susceptibility zonation and landslide activity, about 4,000 km² area of central Nepal was selected for regional-scale assessment of landslide activity and susceptibility zonation mapping. In total, 655 new landslides and 9,229 old landslides were identified with the study area with the help of satellite images, aerial photographs, field data and available reports. The old landslide inventory was “blind landslide database” and could not explain the particular rainfall event responsible for the particular landslide. But considering size of the landslide, blind landslide inventory was reclassified into two databases: short-duration high-intensity rainfall-induced landslide inventory and long-duration low-intensity rainfall-induced landslide inventory. These landslide inventory maps were considered as proxy maps of multiple rainfall event-based landslide inventories. Similarly, all 9,884 landslides were considered for the activity assessment of predisposing causative parameters. For the Nepal Himalaya, slope, slope aspect, geology and road construction activity (anthropogenic cause) were identified as most affective predisposing causative parameters for landslide activity. For susceptibility zonation, multivariate approach was considered and two proxy rainfall event-based landslide databases were used for the logistic regression modelling, while a relatively recent landslide database was used in validation. Two event-based susceptibility zonation maps were merged and rectified to prepare the final susceptibility zonation map and its prediction rate was found to be more than 82 %. From this work, it is concluded that rectification of susceptibility zonation map is very appropriate and reliable. The results of this research contribute to a significant improvement in landslide inventory preparation procedure, susceptibility zonation mapping approaches as well as role of various predisposing causative parameters for the landslide activity.     

Utilities of Virtual 3D City Models Based on CityGML: Various Use Cases

Virtual 3D city models are increasingly being used to model the realms of the real world for utilization in a number of applications related to environmental simulations including, urban planning, mapping the energy characteristics of buildings, noise mapping, flood modelling, etc. Apart from geometric and appearance/textural information, these applications have a requirement for complex urban semantics. Currently, a number of 3D standards are available in CAD, BIM and GIS related domains for the storage, visualization and transfer of 3D geospatial datasets. Initially, the 3D data models (such as COLLADA, VRML, X3D, etc.) were purely graphical/geometrical in nature and mainly used for visualization purposes. With the inclusion of thematic modules in OGC CityGML, the integration of geometry and semantics in a single data model paved the way for better sharing of virtual 3D city models. In spite of the availability of a wide range of 3D data standards, there are certain differences with respect to geometry, topology, semantics, LODs, etc., which complicates the integration of 3D geodata from heterogeneous sources. This paper serves to highlights the need for the innovative solutions with respect to the urban environmental related simulations primarily based on the use of virtual 3D city models. Four use cases are studied in this context namely, (1) urban solar potential estimation using CityGML models, (2) simulation of traffic noise level mapped on building walls from the urban road segments, (3) CityGML based 3D data models interoperability, and (4) 3D indoor logistics and subsurface utilities. However, for modelling majority of use cases, CityGML does not provide explicit thematic representations but provides support for extending the CityGML schema using Application Domain Extensions. In a nutshell, the study explores the semantic modelling capabilities of the CityGML for the transformation of native 3D virtual city models to one satisfying capabilities like semantic information and support towards interoperability.     

Influence of physicochemical parameters on surface water quality: a case study of the Brahmani River,India

This investigation is intended to evaluate the surface water quality of Brahmani River in order to determine its uses for different purposes. The water samples were collected from the strategic locations of the river from February 2014 to July 2015 and analyzed for physicochemical parameters such as water temperature; pH; electrical conductivity (EC); dissolved oxygen (DO); total dissolved solids (TDS); major cations, e.g., Na⁺, K⁺, Mg²⁺, Ca²⁺; and major anions, e.g., F^?, Cl^?, \( {\mathrm{SO}}_4^{2-} \), \( {\mathrm{NO}}_3^{-} \), \( {\mathrm{PO}}_4^{2-} \), and alkalinity. The water quality index (WQI) being a valuable and unique rating scale to depict the overall water quality status in a single term has been employed to determine the feasibility of using the river water as a source for various activities. The parameters with higher impact on water quality were selected to derive WQI of each selected sampling station. Results showed significant deterioration in quality of water at some of the sampling stations. WQI of Brahmani River ranged from 37.87 to 62.36 which falls in the range of good to poor quality of water. Pearson’s correlation matrix was derived to find possible interrelations among water quality parameters.     

Scattering Properties and Composition of Cometary Dust

Composition of the Comet dust obtained by the dust impact analyzer on the Halley probes indicated that the comet dust is a mixture of silicate and carbonaceous material. The collected interplanetary dust particles (IDP's) are fluffy and composite, having grains of several different types stuck together. Using discrete dipole approximation (DDA) we study the scattering properties of composite grains. In particular, we study the angular distribution of the scattered intensity and linear polarization of composite grains. We assume that the composite grains are made up of a host silicate sphere/spheroid with the inclusions of graphite. Results of our calculations on the composite grains show that the angle of maximum polarization shifts, and the degree of polarization varies with the volume fraction of the inclusions. We use these results on the composite grains to interpret the observed scattering in cometary dust.