96 resultados para River Forest


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The INFORMATION SYSTEM with user friendly GUI’s (Graphical user Interface) is developed to maintain the flora data and generate reports for Sharavathi River Basin. The database consists of the information related to trees, herbs, shrubs and climbers. The data is based on the primary field survey and the information available in flora of Shimoga, Karnataka and Hassan flora. User friendly query options based on dichotomous keys are provided to help user to retrieve the data while data entry options aid in updating and editing the database at family, genus and species levels.

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Analysis of climate change impacts on streamflow by perturbing the climate inputs has been a concern for many authors in the past few years, but there are few analyses for the impacts on water quality. To examine the impact of change in climate variables on the water quality parameters, the water quality input variables have to be perturbed. The primary input variables that can be considered for such an analysis are streamflow and water temperature, which are affected by changes in precipitation and air temperature, respectively. Using hypothetical scenarios to represent both greenhouse warming and streamflow changes, the sensitivity of the water quality parameters has been evaluated under conditions of altered river flow and river temperature in this article. Historical data analysis of hydroclimatic variables is carried out, which includes flow duration exceedance percentage (e.g. Q90), single low- flow indices (e.g. 7Q10, 30Q10) and relationships between climatic variables and surface variables. For the study region of Tunga-Bhadra river in India, low flows are found to be decreasing and water temperatures are found to be increasing. As a result, there is a reduction in dissolved oxygen (DO) levels found in recent years. Water quality responses of six hypothetical climate change scenarios were simulated by the water quality model, QUAL2K. A simple linear regression relation between air and water temperature is used to generate the scenarios for river water temperature. The results suggest that all the hypothetical climate change scenarios would cause impairment in water quality. It was found that there is a significant decrease in DO levels due to the impact of climate change on temperature and flows, even when the discharges were at safe permissible levels set by pollution control agencies (PCAs). The necessity to improve the standards of PCA and develop adaptation policies for the dischargers to account for climate change is examined through a fuzzy waste load allocation model developed earlier. Copyright (C) 2011 John Wiley & Sons, Ltd.

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Land cover (LC) and land use (LU) dynamics induced by human and natural processes play a major role in global as well as regional patterns of landscapes influencing biodiversity, hydrology, ecology and climate. Changes in LC features resulting in forest fragmentations have posed direct threats to biodiversity, endangering the sustainability of ecological goods and services. Habitat fragmentation is of added concern as the residual spatial patterns mitigate or exacerbate edge effects. LU dynamics are obtained by classifying temporal remotely sensed satellite imagery of different spatial and spectral resolutions. This paper reviews five different image classification algorithms using spatio-temporal data of a temperate watershed in Himachal Pradesh, India. Gaussian Maximum Likelihood classifier was found to be apt for analysing spatial pattern at regional scale based on accuracy assessment through error matrix and ROC (receiver operating characteristic) curves. The LU information thus derived was then used to assess spatial changes from temporal data using principal component analysis and correspondence analysis based image differencing. The forest area dynamics was further studied by analysing the different types of fragmentation through forest fragmentation models. The computed forest fragmentation and landscape metrics show a decline of interior intact forests with a substantial increase in patch forest during 1972-2007.

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Saplings of forty nine species of trees from Western Ghats forests were planted on a 1.5 hectare tract of Deccan plateau (in the campus of Indian Institute of Science, Bangalore) and their performance monitored for 23 years. The objective was to evaluate their adaptability to a habitat and conditions apparently alien to these species. The study was also meant to understand the linkages of these trees with the surrounding environment. Contrary to the belief that tree species are very sensitive to change of location and conditions, the introduced trees have grown as good as they would do in their native habitat and maintained their phenology. Further, they have grown in perfect harmony with trees native to the location. The results show that the introduced species are opportunistic and readily acclimatized and grew well overcoming the need for the edaphic and other factors that are believed to be responsible for their endemicity. Besides ex situ conservation, the creation of miniforest has other accrued ecosystem benefits. For instance, the ground water level has risen and the ambient temperature has come down by two degrees.

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A two-stage methodology is developed to obtain future projections of daily relative humidity in a river basin for climate change scenarios. In the first stage, Support Vector Machine (SVM) models are developed to downscale nine sets of predictor variables (large-scale atmospheric variables) for Intergovernmental Panel on Climate Change Special Report on Emissions Scenarios (SRES) (A1B, A2, B1, and COMMIT) to R (H) in a river basin at monthly scale. Uncertainty in the future projections of R (H) is studied for combinations of SRES scenarios, and predictors selected. Subsequently, in the second stage, the monthly sequences of R (H) are disaggregated to daily scale using k-nearest neighbor method. The effectiveness of the developed methodology is demonstrated through application to the catchment of Malaprabha reservoir in India. For downscaling, the probable predictor variables are extracted from the (1) National Centers for Environmental Prediction reanalysis data set for the period 1978-2000 and (2) simulations of the third-generation Canadian Coupled Global Climate Model for the period 1978-2100. The performance of the downscaling and disaggregation models is evaluated by split sample validation. Results show that among the SVM models, the model developed using predictors pertaining to only land location performed better. The R (H) is projected to increase in the future for A1B and A2 scenarios, while no trend is discerned for B1 and COMMIT.

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The Silicate Weathering Rate (SWR) and associated Carbon dioxide Consumption Rate (CCR) in tropical silicate terrain is assessed through a study of the major ion chemistry in a small west flowing river of Peninsular India, the Nethravati River. The specific features of the river basin are high mean annual rainfall and temperature, high runoff and a Precambrian basement composed of granitic-gneiss, charnockite and minor metasediments. The water samples (n = 56) were collected from three locations along the Nethravati River and from two of its tributaries over a period of twelve months. Chemical Weathering Rate (CWR) for the entire watershed is calculated by applying rainwater correction using river chloride as a tracer. Chemical Weathering Rate in the Nethravati watershed is estimated to 44 t.km(-2).y(-1) encompassing a SWR of 42 t.km(-2).y(-1) and a maximum carbonate contribution of 2 t.km(-2).y(-1). This SWR is among the highest reported for granito-gneissic terrains. The assessed CCR is 2.9 . 10(5) mol.km(-2).y(-1). The weathering index (Re). calculated from molecular ratios of dissolved cations and silica in the river, suggests an intense silicate weathering leading to kaolinite-gibbsite precipitation in the weathering covers. The intense SWR and CCR could be due to the combination of high runoff and temperature along with the thickness and nature of the weathering cover. The comparison of silicate weathering fluxes with other watersheds reveals that under similar morpho-climatic settings basalt weathering would be 2.5 times higher than the granite-gneissic rocks. (C) 2012 Elsevier B.V. All rights reserved.

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Reducing emissions from deforestation and forest degradation (REDD+) is considered as an important mechanism under the UNFCCC aimed at mitigating climate change. The Cancun Agreement on REDD mechanism has paved the way for designing and implementation of REDD+ activities, to assist countries experiencing large-scale deforestation and forest degradation. Contrary to the general perception, the present analysis shows that India is currently experiencing deforestation and forest degradation. According to the latest assessment of the Forest Survey of India, the net annual loss of forests is estimated to be 99,850 ha during the period 2007-2009, even though the total area under forests has increased. The REDD+ mechanism aims to provide financial incentives for reducing deforestation and forest degradation. India, despite having robust legislations, policies and remote sensing capabilities, is not ready to benefit from the emerging REDD+ mechanism, with potential flow of large financial benefits to rural and forest-dependent communities from international financial sources.

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A hydrological modelling framework was assembled to simulate the daily discharge of the Mandovi River on the Indian west coast. Approximately 90% of the west-coast rainfall, and therefore discharge, occurs during the summer monsoon (June-September), with a peak during July-August. The modelling framework consisted of a digital elevation model (DEM) called GLOBE, a hydrological routing algorithm, the Terrestrial Hydrological Model with Biogeochemistry (THMB), an algorithm to map the rainfall recorded by sparse rain-gauges to the model grid, and a modified Soil Conservation Service Curve Number (SCS-CN) method. A series of discharge simulations (with and without the SCS method) was carried out. The best simulation was obtained after incorporating spatio-temporal variability in the SCS parameters, which was achieved by an objective division of the season into five regimes: the lean season, monsoon onset, peak monsoon, end-monsoon, and post-monsoon. A novel attempt was made to incorporate objectively the different regimes encountered before, during and after the Indian monsoon, into a hydrological modelling framework. The strength of our method lies in the low demand it makes on hydrological data. Apart from information on the average soil type in a region, the entire parameterization is built on the basis of the rainfall that is used to force the model. That the model does not need to be calibrated separately for each river is important, because most of the Indian west-coast basins are ungauged. Hence, even though the model has been validated only for the Mandovi basin, its potential region of application is considerable. In the context of the Prediction in Ungauged Basins (PUB) framework, the potential of the proposed approach is significant, because the discharge of these (ungauged) rivers into the eastern Arabian Sea is not small, making them an important element of the local climate system.