Length-weight relationship of sucker head, Garra Gotyla Gotyla (Gray, 1830) in different rivers of Nepal and the influence of monsoon

Size structure data particularly that of length and weight is very important fisheries management tool, which is also applied to assess the health, habitat and integrity of the rivers. Nepal is tremendously rich in both fisheries and water resource and thus, this analysis is very important. However, this kind of analysis is not common in fisheries studies and hence the size structure information of all the fish in Nepal is wanting. This study simply tries to open the door for such studies with the study of the sucker head Garra gotyla gotyla, a very common fish in Nepal. The field observation was done in nine rivers of the country in all the seasons of the 2003 by using electrofishing gear. The length-weight relationship was found to vary both spatially and temporally among rivers and seasons respectively indicating different conditions in different rivers. The length weight relationship also showed some interesting facts about the seasonal cycle of the species indicating the period of growth and stress in different rivers. The monsoon event was found to be highly influential in this relationship.     

Refinement of predictive reaeration equations for a typical Indian river

Dissolved oxygen mass balance has been computed for different reaches of River Kali in western Uttar Pradesh (India) to obtain the reaeration coefficient (K₂). A total of 270 field data sets have been collected during the period from March 1999 to February 2000. Eleven most popular predictive equations, used for reaeration prediction and utilizing mean stream velocity, bed slope, flow depth, friction velocity and Froude number, have been tested for their applicability in the River Kali using data generated during field survey. The K₂ values computed from these predictive equations have been compared with the K₂ values observed from dissolved oxygen balance measurements in the field. The performance of predictive equations have been evaluated using error estimation, namely standard error (SE), normal mean error (NME), mean multiplicative error (MME) and correlation statistics. The equations developed by Smoot and by Cadwallader and McDonnell showed comparatively better results. Moreover, a refined predictive equation has been developed using a least‐squares algorithm for the River Kali that minimizes error estimates and improves correlation between observed and computed reaeration coefficients. Copyright © 2001 John Wiley & Sons, Ltd.     

Strong ground motion parameters of the 18 September 2011 Sikkim Earthquake Mw = 6.9 and its analysis: a recent seismic hazard scenario

Natural Hazards - The 18 September 2011 earthquake in Sikkim was one the most devastating earthquake in Sikkim Himalaya in India–Asia collision boundary. The source characteristic of this...     

Seismic vulnerability assessment of earthquake-prone mega-city Shillong,India using geophysical mapping and remote sensing

ABSTRACT

The concept of seismic vulnerability is a yard-stick of damage estimation from a probable earthquake considering physical cum social dimension and enables a basis for decision-makers to develop preparedness and mitigation strategies. We aim at vulnerability assessment of the typical urban system of capital city Shillong situated on hilly terrain. High-resolution satellite imagery of Shillong facilitates analysis of building footprints, communication network, and open ground. Different building typologies are identified taking into account the building’s structural configuration assessed through a rapid visual survey of more than 15% of total residential households. Slope map demarcates the landslide-prone area through discrete elevation modelling. A methodology incorporating several parameters e.g. building typology, slope angle, shear wave velocity characteristics, geomorphology, and the number of occupants in correlation with a physical measurement of vulnerability is presented and is applied to estimate the dimension of vulnerability. Additionally, MASW survey indicates lithology up to 30?m deep along with the existence of stiff soil and rocks at different depths whereas resonant frequency is identified to be in the range of 6–8?Hz through H/V ratio. Integrating all, it is observed that more than 60% of Shillong city falls under moderate to higher vulnerability and the rest is less vulnerable.     

Biological neutralization of chlor-alkali industry wastewater

The present work reports biological neutralization of chlor-alkali industrial effluent by an alkaliphilic bacterium, isolated from the Gujarat coast, which was identified as Enterococcus faecium strain R-5 on the basis of morphological, biochemical and partial 16S rRNA gene sequencing. The isolate was capable of bringing down the pH of waste water from 12.0 to 7.0 within 3 h in the presence of carbon and nitrogen sources, with simultaneous reduction in total dissolved solutes (TDS) up to 19-22%. This bacterium produced carboxylic acid, as revealed by FT-IR analysis, which facilitated neutralization of alkaline effluent. The presence of unconventional raw materials viz. Madhuca indica flowers or sugar cane bagasse as carbon and nitrogen sources could effectively neutralize alkaline effluent and thus making the bioremediation process economically viable. The time required for neutralization varied with size of inoculum. To the best of our knowledge, this is the first report on biological neutralization of a chlor-alkali industrial effluent.     

Some studies in the resistivity of Indian sandstones

Summary In this paper some measurements of the resistivity of Talchir and Barakar sandstones of the Jharia Coal field under dry and saturated conditions have been made and the results are discussed in the light of known theories. Techniques of measurement have been briefly described.     

A supplementary approach for estimating reaeration rate coefficients

Different commonly used predictive equations for the reaeration rate coefficient (K₂) have been evaluated using 231 data sets obtained from the literature and 576 data sets measured at different reaches of the River Kali in western Uttar Pradesh, India. The data sets include stream/channel velocity, bed slope, flow depth, cross‐sectional area and reaeration rate coefficient (K₂), obtained from the literature and generated during the field survey of River Kali, and were used to test the applicability of the predictive equations. The K₂ values computed from the predictive equations have been compared with the corresponding K₂ values measured in streams/channels. The performance of the predictive equations has been evaluated using different error estimation, namely standard error (SE), normal mean error (NME), mean multiplicative error (MME) and coefficient of determination (r²). The results show that the reaeration rate equation developed by Parkhurst and Pomeroy yielded the best agreement, with the values of SE, NME, MME and r² as 33·387, 4·62, 3·58 and 0·95, respectively, for literature data sets (case 1) and 37·567, 3·57, 2·6 and 0·95, respectively, for all the data sets (literature data sets and River Kali data sets) (case 2). Further, to minimize error estimates and improve correlation between measured and computed reaeration rate coefficients, supplementary predictive equations have been developed based on Froude number criteria and a least‐squares algorithm. The supplementary predictive equations have been verified using different error estimates and by comparing measured and computed reaeration rate coefficients for data sets not used in the development of the equations. Copyright © 2003 John Wiley & Sons, Ltd.     

Estimation of Above Ground Biomass Using Texture Metrics Derived from IRS Cartosat-1 Panchromatic Data in Evergreen Forests of Western Ghats,India

Assessment of above ground forest biomass (AGB) is essential in carbon modelling studies to provide mitigation strategies as demonstrated by reducing emissions from deforestation and forest degradation. Several researchers have demonstrated the use of remote sensing data in spatial AGB estimation, in terms of spectral and radar backscatter based approaches at a landscape scale with several known limitations. However, these methods lacked the predictive ability at high biomass ranges due to saturation. The current study addresses the problem of saturation at high biomass ranges using canopy textural metric from high resolution optical data. Fourier transform based textural ordination (FOTO) technique, which involves deriving radial spectrum information via 2D fast Fourier transform and ordination through principal component analysis was used for characterizing the textural properties of forest canopies. In the current study, plot level estimated AGB from 15 (1 ha) plots was used to relate with texture derived information from very high resolution datasets (viz., IKONOS and Cartosat-1). In addition to the estimation of high biomass ranges, one of the prime objective of the current study is to understand the effects of spatial resolution on deriving textural-AGB relationship from 2.5 m IRS Cartosat data (Cartosat-A, viewing angle = ?5°) to that of IKONOS imagery with near nadir view. Further, since texture is impacted by several illumination geometry issues, the effect of viewing geometry on the relationship was evaluated using Cartosat-F (Viewing angle = 26°) imagery. The results show that the FOTO method using stereo Cartosat (A and F) images at 2.5 m resolution are able to perform well in characterizing high AGB values since the texture-biomass relationship is only subjected to 18 % relative error to that of 15 % in case of IKONOS and could aid in reduction of uncertainty in AGB estimation at a large landscape levels.     

A global,high-resolution (30-m) inland water body dataset for 2000: first results of a topographic–spectral classification algorithm

The science and management of terrestrial ecosystems require accurate, high-resolution mapping of surface water. We produced a global, 30-m-resolution inland surface water dataset with an automated algorithm using Landsat-based surface reflectance estimates, multispectral water and vegetation indices, terrain metrics, and prior coarse-resolution water masks. The dataset identified 3,650,723 km² of inland water globally – nearly three quarters of which was located in North America (40.65%) and Asia (32.77%), followed by Europe (9.64%), Africa (8.47%), South America (6.91%), and Oceania (1.57%). Boreal forests contained the largest portion of terrestrial surface water (25.03% of the global total), followed by the nominal ‘inland water’ biome (16.36%), tundra (15.67%), and temperate broadleaf and mixed forests (13.91%). Agreement with respect to the Moderate-resolution Imaging Spectroradiometer water mask and Landsat-based national land-cover datasets was very high, with commission errors <4% and omission errors <14% relative to each. Most of these were accounted for in the seasonality of water cover, snow and ice, and clouds – effects which were compounded by differences in image acquisition date relative to reference datasets. The Global Land Cover Facility (GLCF) inland surface water dataset is available for open access at the GLCF website (http://www.landcover.org).