16 resultados para Vulnerability assessment

em Indian Institute of Science - Bangalore - Índia


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Forest-management goals in the context of climate change are to reduce the adverse impact of climate change on biodiversity, ecosystem services and carbon stocks. For developing an effective adaptation strategy, knowledge on nature and sources of vulnerability of forests is necessary to conserve or enhance carbon sinks. However, assessing the vulnerability of forest ecosystems is a challenging task, as the mechanisms that determine vulnerability cannot be observed directly. In this article, we list the challenges in forest vulnerability assessments and propose an assessment of inherent vulnerability by using process-based indicators under the current climate. We also suggest periodic assessment of vulnerability, which is necessary to review adaptation strategies for the management of forests and forest carbon stocks.

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Vulnerability of communities and natural ecosystems, to potential impacts of climate change in developing countries like India, and the need for adaptation are rapidly emerging as central issues in the debate around policy responses to climate change. The present study presents an approach to identify and prioritize the most vulnerable districts, villages and households in Karnataka State, through a multi-scale assessment of inherent vulnerability to current climate variability. It also identifies the drivers of inherent vulnerability, thereby providing a tool for developing and mainstreaming adaptation strategies, in ongoing developmental or dedicated adaptation programmes. The multi-scale assessment was made for all 30 districts at the state level in Karnataka, about 1220 villages in Chikballapur district, and at the household level for two villages - Gundlapalli and Saddapalli - in Bagepalli taluk of Chikballapur district. At the district, village and household levels, low levels of education and skills are the dominant factors contributing to vulnerability. At the village and household level, the lack of income diversification and livelihood support institutions are key drivers of vulnerability. The approach of multi-scale vulnerability assessment facilitates identification and prioritization of the drivers of vulnerability at different scales, to focus adaptation interventions to address these drivers.

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An assessment of the impact of projected climate change on forest ecosystems in India based on climate projections of the Regional Climate Model of the Hadley Centre (HadRM3) and the global dynamic vegetation model IBIS for A1B scenario is conducted for short-term (2021-2050) and long-term (2071-2100) periods. Based on the dynamic global vegetation modelling, vulnerable forested regions of India have been identified to assist in planning adaptation interventions. The assessment of climate impacts showed that at the national level, about 45% of the forested grids is projected to undergo change. Vulnerability assessment showed that such vulnerable forested grids are spread across India. However, their concentration is higher in the upper Himalayan stretches, parts of Central India, northern Western Ghats and the Eastern Ghats. In contrast, the northeastern forests, southern Western Ghats and the forested regions of eastern India are estimated to be the least vulnerable. Low tree density, low biodiversity status as well as higher levels of fragmentation, in addition to climate change, contribute to the vulnerability of these forests. The mountainous forests (sub-alpine and alpine forest, the Himalayan dry temperate forest and the Himalayan moist temperate forest) are susceptible to the adverse effects of climate change. This is because climate change is predicted to be larger for regions that have greater elevations.

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Climate change vulnerability profiles are developed at the district level for agriculture, water and forest sectors for the North East region of India for the current and projected future climates. An index-based approach was used where a set of indicators that represent key sectors of vulnerability (agriculture, forest, water) is selected using the statistical technique principal component analysis. The impacts of climate change on key sectors as represented by the changes in the indicators were derived from impact assessment models. These impacted indicators were utilized for the calculation of the future vulnerability to climate change. Results indicate that majority of the districts in North East India are subject to climate induced vulnerability currently and in the near future. This is a first of its kind study that exhibits ranking of districts of North East India on the basis of the vulnerability index values. The objective of such ranking is to assist in: (i) identifying and prioritizing the most vulnerable sectors and districts; (ii) identifying adaptation interventions, and (iii) mainstreaming adaptation in development programmes.

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Climate change impact on a groundwater-dependent small urban town has been investigated in the semiarid hard rock aquifer in southern India. A distributed groundwater model was used to simulate the groundwater levels in the study region for the projected future rainfall (2012-32) obtained from a general circulation model (GCM) to estimate the impacts of climate change and management practices on groundwater system. Management practices were based on the human-induced changes on the urban infrastructure such as reduced recharge from the lakes, reduced recharge from water and wastewater utility due to an operational and functioning underground drainage system, and additional water extracted by the water utility for domestic purposes. An assessment of impacts on the groundwater levels was carried out by calibrating a groundwater model using comprehensive data gathered during the period 2008-11 and then simulating the future groundwater level changes using rainfall from six GCMs Institute of Numerical Mathematics Coupled Model, version 3.0 (INM-CM. 3.0); L'Institut Pierre-Simon Laplace Coupled Model, version 4 (IPSL-CM4); Model for Interdisciplinary Research on Climate, version 3.2 (MIROC3.2); ECHAM and the global Hamburg Ocean Primitive Equation (ECHO-G); Hadley Centre Coupled Model, version 3 (HadCM3); and Hadley Centre Global Environment Model, version 1 (HadGEM1)] that were found to show good correlation to the historical rainfall in the study area. The model results for the present condition indicate that the annual average discharge (sum of pumping and natural groundwater outflow) was marginally or moderately higher at various locations than the recharge and further the recharge is aided from the recharge from the lakes. Model simulations showed that groundwater levels were vulnerable to the GCM rainfall and a scenario of moderate reduction in recharge from lakes. Hence, it is important to sustain the induced recharge from lakes by ensuring that sufficient runoff water flows to these lakes.

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This study borrows the measures developed for the operation of water resources systems as a means of characterizing droughts in a given region. It is argued that the common approach of assessing drought using a univariate measure (severity or reliability) is inadequate as decision makers need assessment of the other facets considered here. It is proposed that the joint distribution of reliability, resilience, and vulnerability (referred to as RRV in a reservoir operation context), assessed using soil moisture data over the study region, be used to characterize droughts. Use is made of copulas to quantify the joint distribution between these variables. As reliability and resilience vary in a nonlinear but almost deterministic way, the joint probability distribution of only resilience and vulnerability is modeled. Recognizing the negative association between the two variables, a Plackett copula is used to formulate the joint distribution. The developed drought index, referred to as the drought management index (DMI), is able to differentiate the drought proneness of a given area when compared to other areas. An assessment of the sensitivity of the DMI to the length of the data segments used in evaluation indicates relative stability is achieved if the data segments are 5years or longer. The proposed approach is illustrated with reference to the Malaprabha River basin in India, using four adjoining Climate Prediction Center grid cells of soil moisture data that cover an area of approximately 12,000 km(2). (C) 2013 American Society of Civil Engineers.

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In this paper, we present a machine learning approach to measure the visual quality of JPEG-coded images. The features for predicting the perceived image quality are extracted by considering key human visual sensitivity (HVS) factors such as edge amplitude, edge length, background activity and background luminance. Image quality assessment involves estimating the functional relationship between HVS features and subjective test scores. The quality of the compressed images are obtained without referring to their original images ('No Reference' metric). Here, the problem of quality estimation is transformed to a classification problem and solved using extreme learning machine (ELM) algorithm. In ELM, the input weights and the bias values are randomly chosen and the output weights are analytically calculated. The generalization performance of the ELM algorithm for classification problems with imbalance in the number of samples per quality class depends critically on the input weights and the bias values. Hence, we propose two schemes, namely the k-fold selection scheme (KS-ELM) and the real-coded genetic algorithm (RCGA-ELM) to select the input weights and the bias values such that the generalization performance of the classifier is a maximum. Results indicate that the proposed schemes significantly improve the performance of ELM classifier under imbalance condition for image quality assessment. The experimental results prove that the estimated visual quality of the proposed RCGA-ELM emulates the mean opinion score very well. The experimental results are compared with the existing JPEG no-reference image quality metric and full-reference structural similarity image quality metric.

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The demand for tunnelling and underground space creation is rapidly growing due to the requirement of civil infrastructure projects and urbanisation. Blasting remains the most inexpensive method of underground excavations in hard rock. Unfortunately, there are no specific safety guidelines available for the blasted tunnels with regards to the threshold limits of vibrations caused by repeated blasting activity in the close proximity. This paper presents the results of a comprehensive study conducted to find out the effect of repeated blast loading on the damage experienced by jointed basaltic rock mass during tunnelling works. Conducting of multiple rounds of blasts for various civil excavations in a railway tunnel imparted repeated loading on rock mass of sidewall and roof of the tunnel. The blast induced damage was assessed by using vibration attenuation equations of charge weight scaling law and measured by borehole extensometers and borehole camera. Ground vibrations of each blasting round were also monitored by triaxial geophones installed near the borehole extensometers. The peak particle velocity (V-max) observations and plastic deformations from borehole extensometers were used to develop a site specific damage model. The study reveals that repeated dynamic loading imparted on the exposed tunnel from subsequent blasts, in the vicinity, resulted in rock mass damage at lesser vibration levels than the critical peak particle velocity (V-cr). It was found that, the repeated blast loading resulted in the near-field damage due to high frequency waves and far-field damage due to low frequency waves. The far field damage, after 45-50 occurrences of blast loading, was up to 55% of the near-field damage in basaltic rock mass. The findings of the study clearly indicate that the phenomena of repeated blasting with respect to number of cycles of loading should be taken into consideration for proper assessment of blast induced damage in underground excavations.

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Improving access to safe drinking water can result in multi-dimensional impacts on people's livelihood. This has been aptly reflected in the Millennium Development Goals (MDG) as one of the major objectives. Despite the availability of diverse and complex set of technologies for water purification, pragmatic and cost-effective use of the same is impeding the use of available sources of water. Hence, in country like India simple low-energy technologies such as solar still are likely to succeed. Solar stills would suffice the basic minimum drinking water requirements of man. Solar stills use sunlight, to kill or inactivate many, if not all, of the pathogens found in water. This paper provides an integrated assessment of the suitability of domestic solar still as a viable safe water technology for India. Also an attempt has been made to critically assess the operational feasibility and costs incurred for using this technology in rural India.

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The Ozone Monitoring Instrument (OMI) aboard EOS-Aura and the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard EOS-Aqua fly in formation as part of the A-train. Though OMI retrieves aerosol optical depth (AOD) and aerosol absorption, it must assume aerosol layer height. The MODIS cannot retrieve aerosol absorption, but MODIS aerosol retrieval is not sensitive to aerosol layer height and with its smaller pixel size is less affected by subpixel clouds. Here we demonstrate an approach that uses MODIS-retrieved AOD to constrain the OMI retrieval, freeing OMI from making an a priori estimate of aerosol height and allowing a more direct retrieval of aerosol absorption. To predict near-UV optical depths using MODIS data we rely on the spectral curvature of the MODIS-retrieved visible and near-IR spectral AODs. Application of an OMI-MODIS joint retrieval over the north tropical Atlantic shows good agreement between OMI and MODIS-predicted AODs in the UV, which implies that the aerosol height assumed in the OMI-standard algorithm is probably correct. In contrast, over the Arabian Sea, MODIS-predicted AOD deviated from the OMI-standard retrieval, but combined OMI-MODIS retrievals substantially improved information on aerosol layer height (on the basis of validation against airborne lidar measurements). This implies an improvement in the aerosol absorption retrieval, but lack of UV absorption measurements prevents a true validation. Our study demonstrates the potential of multisatellite analysis of A-train data to improve the accuracy of retrieved aerosol products and suggests that a combined OMI-MODIS-CALIPSO retrieval has large potential to further improve assessments of aerosol absorption.

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This paper presents a new approach for assessing power system voltage stability based on artificial feed forward neural network (FFNN). The approach uses real and reactive power, as well as voltage vectors for generators and load buses to train the neural net (NN). The input properties of the NN are generated from offline training data with various simulated loading conditions using a conventional voltage stability algorithm based on the L-index. The performance of the trained NN is investigated on two systems under various voltage stability assessment conditions. Main advantage is that the proposed approach is fast, robust, accurate and can be used online for predicting the L-indices of all the power system buses simultaneously. The method can also be effectively used to determining local and global stability margin for further improvement measures.

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The objective of the current study was to investigate the mechanism by which the corpus luteum (CL) of the monkey undergoes desensitization to luteinizing hormone following exposure to increasing concentration of human chorionic gonadotrophin (hCG) as it occurs in pregnancy. Female bonnet monkeys were injected (im) increasing doses of hCG or dghCG beginning from day 6 or 12 of the luteal phase for either 10 or 4 or 2 days. The day of oestrogen surge was considered as day '0' of luteal phase. Luteal cells obtained from CL of these animals were incubated with hCG (2 and 200 pg/ml) or dbcAMP (2.5, 25 and 100 mu M) for 3 h at 37 degrees C and progesterone secreted was estimated. Corpora lutea of normal cycling monkeys on day 10/16/22 of the luteal phase were used as controls, In addition the in vivo response to CG and deglycosylated hCG (dghCG) was assessed by determining serum steroid profiles following their administration. hCG (from 15-90 IU) but not dghCG (15-90 IU) treatment in vivo significantly (P < 0.05) elevated serum progesterone and oestradiol levels. Serum progesterone, however, could not be maintained at a elevated level by continuous treatment with hCG (from day 6-15), the progesterone level declining beyond day 13 of luteal phase. Administering low doses of hCG (15-90 IU/day) from day 6-9 or high doses (600 IU/day) on days 8 and 9 of the luteal phase resulted in significant increase (about 10-fold over corresponding control P < 0.005) in the ability of luteal cells to synthesize progesterone (incubated controls) in vitro. The luteal cells of the treated animals responded to dbcAMP (P < 0.05) but not to hCG added in vitro, The in vitro response of luteal cells to added hCG was inhibited by 0, 50 and 100% if the animals were injected with low (15-90 IU) or medium (100 IU) between day 6-9 of luteal phase and high (600 IU on day 8 and 9 of luteal phase) doses of dghCG respectively; such treatment had no effect on responsivity of the cells to dbcAMP, The luteal cell responsiveness to dbcAMP in vitro was also blocked if hCG was administered for 10 days beginning day 6 of the luteal phase. Though short term hCG treatment during late luteal phase (from days 12-15) had no effect on luteal function, 10 day treatment beginning day 12 of luteal phase resulted in regain of in vitro responsiveness to both hCG (P < 0.05) and dbcAMP (P < 0.05) suggesting that luteal rescue can occur even at this late stage. In conclusion, desensitization of the CL to hCG appears to be governed by the dose/period for which it is exposed to hCG/dghCG. That desensitization is due to receptor occupancy is brought out by the fact that (i) this can be achieved by giving a larger dose of hCG over a 2 day period instead of a lower dose of the hormone for a longer (4 to 10 days) period and (ii) the effect can largely be reproduced by using dghCG instead of hCG to block the receptor sites. It appears that to achieve desensitization to dbcAMP also it is necessary to expose the luteal cell to relatively high dose of hCG for more than 4 days.

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Crystals growing from solution, the vapour phase and from supercooled melt exhibit, as a rule, planar faces. The geometry and distribution of dislocations present within the crystals thus grown are strongly related to the growth on planar faces and to the different growth sectors rather than the physical properties of the crystals and the growth methods employed. As a result, many features of generation and geometrical arrangement of defects are common to extremely different crystal species. In this paper these commoner aspects of dislocation generation and configuration which permits one to predict their nature and distribution are discussed. For the purpose of imaging the defects a very versatile and widely applicable technique viz. x-ray diffraction topography is used. Growth dislocations in solution grown crystals follow straight path with strongly defined directions. These preferred directions which in most cases lie within an angle of ±15° to the growth normal depend on the growth direction and on the Burger's vector involved. The potential configuration of dislocations in the growing crystals can be evaluated using the theory developed by Klapper which is based on linear anisotropic elastic theory. The preferred line direction of a particular dislocation corresponds to that in which the dislocation energy per unit growth length is a minimum. The line direction analysis based on this theory enables one to characterise dislocations propagating in a growing crystal. A combined theoretical analysis and experimental investigation based on the above theory is presented.

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Several N,N -dipyridyl- and N-phenyl-N -pyridyl-thioureas were examined in different solvents at various temperatures by 1H NMR in order to study their conformational properties. The influence of concentration and the methyl substituent in the pyridine ring on the chemical shifts of the NH and pyridine groups was investigated. The observed chemical shifts are analysed in terms of the conformational properties of the molecules. Free energy barriers to the internal rotation about the C N bonds have been determined. Infrared spectra have been measured to supplement the NMR studies. Intramolecular hydrogen bonding played a major role in the preferred conformation of pyridylthioureas. The data further revealed an interesting dynamic exchange phenomenon occurring in symmetric N,N -dipyridylthioureas between two intramolecularly hydrogen bonded conformers.

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Calciothermic reduction of TiO2 provides a potentially low-cost route to titanium production. Presented in this article is a suitably designed diagram, useful for assessing the degree of reduction of TiO2 and residual oxygen contamination in metal as a function of reduction temperature and other process parameters. The oxygen chemical potential diagram à la Ellingham-Richardson-Jeffes is useful for visualization of the thermodynamics of reduction reactions at high temperatures. Although traditionally the diagram depicts oxygen potentials corresponding to the oxidation of different metals to their corresponding oxides or of lower oxides to higher oxides, oxygen potentials associated with solution phases at constant composition can be readily superimposed. The usefulness of the diagram for an insightful analysis of calciothermic reduction, either direct or through an electrochemical process, is discussed. Identified are possible process variations, modeling and optimization strategies.