878 resultados para Catchment
Resumo:
Drastic groundwater resource depletion due to excessive extraction for irrigation is a major concern in many parts of India. In this study, an attempt was made to simulate the groundwater scenario of the catchment using ArcSWAT. Due to the restriction on the maximum initial storage, the deep aquifer component in ArcSWAT was found to be insufficient to represent the excessive groundwater depletion scenario. Hence, a separate water balance model was used for simulating the deep aquifer water table. This approach is demonstrated through a case study for the Malaprabha catchment in India. Multi-site rainfall data was used to represent the spatial variation in the catchment climatology. Model parameters were calibrated using observed monthly stream flow data. Groundwater table simulation was validated using the qualitative information available from the field. The stream flow was found to be well simulated in the model. The simulated groundwater table fluctuation is also matching reasonably well with the field observations. From the model simulations, deep aquifer water table fluctuation was found very severe in the semi-arid lower parts of the catchment, with some areas showing around 60m depletion over a period of eight years. Copyright (c) 2012 John Wiley & Sons, Ltd.
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A variety of methods are available to estimate future solar radiation (SR) scenarios at spatial scales that are appropriate for local climate change impact assessment. However, there are no clear guidelines available in the literature to decide which methodologies are most suitable for different applications. Three methodologies to guide the estimation of SR are discussed in this study, namely: Case 1: SR is measured, Case 2: SR is measured but sparse and Case 3: SR is not measured. In Case 1, future SR scenarios are derived using several downscaling methodologies that transfer the simulated large-scale information of global climate models to a local scale ( measurements). In Case 2, the SR was first estimated at the local scale for a longer time period using sparse measured records, and then future scenarios were derived using several downscaling methodologies. In Case 3: the SR was first estimated at a regional scale for a longer time period using complete or sparse measured records of SR from which SR at the local scale was estimated. Finally, the future scenarios were derived using several downscaling methodologies. The lack of observed SR data, especially in developing countries, has hindered various climate change impact studies. Hence, this was further elaborated by applying the Case 3 methodology to a semi-arid Malaprabha reservoir catchment in southern India. A support vector machine was used in downscaling SR. Future monthly scenarios of SR were estimated from simulations of third-generation Canadian General Circulation Model (CGCM3) for various SRES emission scenarios (A1B, A2, B1, and COMMIT). Results indicated a projected decrease of 0.4 to 12.2 W m(-2) yr(-1) in SR during the period 2001-2100 across the 4 scenarios. SR was calculated using the modified Hargreaves method. The decreasing trends for the future were in agreement with the simulations of SR from the CGCM3 model directly obtained for the 4 scenarios.
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Climate change impact assessment studies involve downscaling large-scale atmospheric predictor variables (LSAPVs) simulated by general circulation models (GCMs) to site-scale meteorological variables. This article presents a least-square support vector machine (LS-SVM)-based methodology for multi-site downscaling of maximum and minimum daily temperature series. The methodology involves (1) delineation of sites in the study area into clusters based on correlation structure of predictands, (2) downscaling LSAPVs to monthly time series of predictands at a representative site identified in each of the clusters, (3) translation of the downscaled information in each cluster from the representative site to that at other sites using LS-SVM inter-site regression relationships, and (4) disaggregation of the information at each site from monthly to daily time scale using k-nearest neighbour disaggregation methodology. Effectiveness of the methodology is demonstrated by application to data pertaining to four sites in the catchment of Beas river basin, India. Simulations of Canadian coupled global climate model (CGCM3.1/T63) for four IPCC SRES scenarios namely A1B, A2, B1 and COMMIT were downscaled to future projections of the predictands in the study area. Comparison of results with those based on recently proposed multivariate multiple linear regression (MMLR) based downscaling method and multi-site multivariate statistical downscaling (MMSD) method indicate that the proposed method is promising and it can be considered as a feasible choice in statistical downscaling studies. The performance of the method in downscaling daily minimum temperature was found to be better when compared with that in downscaling daily maximum temperature. Results indicate an increase in annual average maximum and minimum temperatures at all the sites for A1B, A2 and B1 scenarios. The projected increment is high for A2 scenario, and it is followed by that for A1B, B1 and COMMIT scenarios. Projections, in general, indicated an increase in mean monthly maximum and minimum temperatures during January to February and October to December.
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Eleven GCMs (BCCR-BCCM2.0, INGV-ECHAM4, GFDL2.0, GFDL2.1, GISS, IPSL-CM4, MIROC3, MRI-CGCM2, NCAR-PCMI, UKMO-HADCM3 and UKMO-HADGEM1) were evaluated for India (covering 73 grid points of 2.5 degrees x 2.5 degrees) for the climate variable `precipitation rate' using 5 performance indicators. Performance indicators used were the correlation coefficient, normalised root mean square error, absolute normalised mean bias error, average absolute relative error and skill score. We used a nested bias correction methodology to remove the systematic biases in GCM simulations. The Entropy method was employed to obtain weights of these 5 indicators. Ranks of the 11 GCMs were obtained through a multicriterion decision-making outranking method, PROMETHEE-2 (Preference Ranking Organisation Method of Enrichment Evaluation). An equal weight scenario (assigning 0.2 weight for each indicator) was also used to rank the GCMs. An effort was also made to rank GCMs for 4 river basins (Godavari, Krishna, Mahanadi and Cauvery) in peninsular India. The upper Malaprabha catchment in Karnataka, India, was chosen to demonstrate the Entropy and PROMETHEE-2 methods. The Spearman rank correlation coefficient was employed to assess the association between the ranking patterns. Our results suggest that the ensemble of GFDL2.0, MIROC3, BCCR-BCCM2.0, UKMO-HADCM3, MPIECHAM4 and UKMO-HADGEM1 is suitable for India. The methodology proposed can be extended to rank GCMs for any selected region.
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Eleven general circulation models/global climate models (GCMs) - BCCR-BCCM2.0, INGV-ECHAM4, GFDL2.0, GFDL2.1, GISS, IPSL-CM4, MIROC3, MRI-CGCM2, NCAR-PCMI, UKMO-HADCM3 and UKMO-HADGEM1 - are evaluated for Indian climate conditions using the performance indicator, skill score (SS). Two climate variables, temperature T (at three levels, i.e. 500, 700, 850 mb) and precipitation rate (Pr) are considered resulting in four SS-based evaluation criteria (T500, T700, T850, Pr). The multicriterion decision-making method, technique for order preference by similarity to an ideal solution, is applied to rank 11 GCMs. Efforts are made to rank GCMs for the Upper Malaprabha catchment and two river basins, namely, Krishna and Mahanadi (covered by 17 and 15 grids of size 2.5 degrees x 2.5 degrees, respectively). Similar efforts are also made for India (covered by 73 grid points of size 2.5 degrees x 2.5 degrees) for which an ensemble of GFDL2.0, INGV-ECHAM4, UKMO-HADCM3, MIROC3, BCCR-BCCM2.0 and GFDL2.1 is found to be suitable. It is concluded that the proposed methodology can be applied to similar situations with ease.
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Eleven coupled model intercomparison project 3 based global climate models are evaluated for the case study of Upper Malaprabha catchment, India for precipitation rate. Correlation coefficient, normalised root mean square deviation, and skill score are considered as performance indicators for evaluation in fuzzy environment and assumed to have equal impact on the global climate models. Fuzzy technique for order preference by similarity to an ideal solution is used to rank global climate models. Top three positions are occupied by MIROC3, GFDL2.1 and GISS with relative closeness of 0.7867, 0.7070, and 0.7068. IPSL-CM4, NCAR-PCMI occupied the tenth and eleventh positions with relative closeness of 0.4959 and 0.4562.
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The Hawkesbury-Nepean River in New South Wales (NSW), Australia, is the largest river system in the Sydney metropolitan area, and it drains most of the developing areas to the west. This catchment is under increasing pressure from urban expansion and the river frequently experiences extended periods of low flows due to a combination of extensive river regulation and the Australian temperate climate. Added to this, the river and several of its tributaries receive treated sewage and stormwater from various sources. Habitats and biota within the Hawkesbury-Nepean River catchment have been altered since European settlement and many introduced species have spread throughout the terrestrial and aquatic environment (Recher et al. 1993). Submersed macrophyte assemblages within the river have undergone significant changes in their distribution and abundance due to eutrophication, habitat alteration and changes to river flows (Recher et al 1993). Anecdotal evidence and some early unpublished studies suggest that egeria (Egeria densa Planchon), introduced from South America as an aquarium plant, was present in the Hawkesbury-Nepean River prior to 1980. Sainty (1973) reported a persistent and troublesome infestation over a number of years at Wallacia in the upper Nepean River. Here, as part of a larger study on the ecology of macrophyte and invertebrate assemblages associated with anthropogenic disturbance in the Hawkesbury-Nepean River, we document the rapid spread of egeria since 1994. Significant increases in egeria biomass were also found, and we present preliminary evidence which suggest that the native ribbonweed, vallisneria (Vallisneria americana Michx.) is being displaced.
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The prediction and estimate of water and soil loss is fundamental important for understanding the effect of the spatial heterogeneity of underlying surfaces and preventing ecological environment deterioration. In this paper, a dynamic model of runoff and sediment yield in small watersheds is established. The proposed model includes three components: runoff generation caused by rainfall, soil erosion on hillslopes by overland flow, and runoff concentration and sediment transport on watersheds. Applying the proposed model, the runoff and sediment yield processes in a typical catchment on the loess plateau was estimated, which exhibited a good agreement between predicted results and observation.
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Abstract The rapid growth of both formal and informal high density urban settlements around major water resources has led to increased pollution of streams, rivers, lakes and estuaries, due to contaminated runoff from these developments. The paper identified major contaminants to be : organic waste (sewage), industrial effluent, pesticides and litter. Pollutant loads vary depending on the hydrology of the urban area, local topography and soil conditions. In some instances, severe pollution of neighbouring and downstream water courses has been observed. The management of catchment land uses, riparian zones, in stream habitat, as well as in stream water flow patterns and quality are necessary in order to sustain the integrity and "health" of water resources, for fisheries and other developments. As such, attempts to ensure a certain level of water quality without attention to other aspects will not automatically ensure a "healthy" ecosystem even as fish habitat. Proper management leads to better water quality and conducive environment for increased fish production
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In 1990, "BICER" or the Baikal International Centre for Ecological Research was created to foster collaborative research on Lake Baikal. The British effort in BICER was initiated and is administered by the Royal Society, London. Much of the on-going research effort is now focussed on environmental change, as there is increasing concern about recent changes in the lake's unique ecosystem that could be linked with the effects of water pollution from catchment effluents. Monitoring studies of the phytoplankton in Lake Baikal's southern basin indicate that several species have increased in abundance since the mid-70's. Diatoms in Lake Baikal sediments are also being studied.
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In 1937 the Development Commission provided an annual grant to the Freshwater Biological Association to pay for a director and secretary. The author moved to the Lake District in the same year, and at that time T.T. Macan was working on invertebrates; K.R. Allen on fish; C.H. Mortimer on chemistry and physics of the aquatic environment, and Marie Rosenberg on phytoplankton. They were backed by George Thompson as laboratory assistant and Rosa Bullen as secretary. The work of the Association continued and expanded throughout the Second World War with some far-reached discoveries made. For example, the recovery of lake sediment cores and the examination of diatom remains, so starting the discipline of archaeo-limnology. Also, a hydrological survey of the Windermere catchment area found significant traces of sulphuric acid in rain gauges. This was more than 30 years before "acid rain" became fashionable.
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This report summarises the annual rainfall of the River Derwent catchment area and examines the floods of 1931 and 1932. The author uses data from the Meteorological Office to examine if the floods were extraordinary and takes into account local lakes in reducing the magnitude of the flood. Areas that are presented in more detail are Bassenthwaite Lake, Thirlmere, Cockermouth, Keswick, Newlands and Coledale Beck. (PDF contains 38 pages)
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This short paper records some measurements made on the Little Sea, a shallow, coastal, acidic lake on Studland Heath, Dorset. The lake, formed about 100 years ago by dunes cutting off a sea inlet, has not received any input of agricultural fertilizers or other waste products for at least the last 30 years. It is a Site of Special Scientific Interest (SSSI). Samples of surface water were taken from the northern and southern ends of the lake at 3-monthly intervals, from July 1995 to April 1996. The first samples in July 1995 were taken during a period of drought; rain, sometimes very heavy, came in late September. With the exception of silicate, potassium and phosphate, there were no large changes in plant nutrient concentrations during the year. The concentration of nitrate-nitrogen was very low (close to the limits of analytical detection), but total phosphorus at ca. 30 mu g per litre was similar to concentrations found in some of the Cumbrian eutrophic lakes. The large number of algal species at low cell/colony concentrations suggested that the lake is mesotrophic. Sodium, chloride and magnesium in the lake water were close to the same proportions as those found in sea water. Dry and wet deposition of sea-salts on the lake surface and its catchment area probably is the major source of sodium, magnesium and chloride ions in the lake, and also accounts for about half of the mean potassium and sulphate concentrations.
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This article is based on a survey of tarns conducted mainly in the summers of 1983 to 1985, plus a survey made in the winter of 1985, in which streams were sampled on the wide variety of rock-types occurring on the fringes of the Lake District. Differences in composition of major ions and their concentrations in the surface waters of Cumbria reflect the complex geological structure of the region. At altitudes above 300 m, on Borrowdale Volcanics and Skiddaw Slates, surface waters are derived from atmospheric precipitation, with additional inputs of some ions - especially calcium and bicarbonate - from catchment rocks and soils. In some of the low-lying large lakes on the fringes of the central fells, water composition is also dominated by inputs from upper catchments; examples are Wastwater, Ullswater and Haweswater. However in other lakes there is evidence (Derwentwater and Bassenthwaite Lake) of inputs from saline groundwater.
Resumo:
The economic, environmental and social benefits of more sensitive land use practices that protect or restore the natural functions of river catchments have been widely discussed. Changing land use has implications for a wide range of other biological communities. Some studies have already been undertaken on the benefits of sensitive farming at the catchment scale in England and Wales. However, there is a gap in these studies at the local scale, and particularly for upland farms from which headwaters arise. This article documents a case study relating to a successful partnership in Cumbria, UK, set within the wider context of catchment management. Whilst the case study is not highly detailed, and some costs have been described in outline only to protect confidentiality and commercial sensitivity, it provides some generic lessons and may therefore be useful in informing more sustainable policy-making. High Hullockhowe Farm near Haweswater, which was used a the case study highlighting changes in farm practise, costs and benefits, water resources and biodiversity. The authors relate the case study to wider policy implications.