89 resultados para Management of water

em Indian Institute of Science - Bangalore - Índia


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It is a well-known fact that most of the developing countries have intermittent water supply and the quantity of water supplied from the source is also not distributed equitably among the consumers. Aged pipelines, pump failures, and improper management of water resources are some of the main reasons for it. This study presents the application of a nonlinear control technique to overcome this problem in different zones in the city of Bangalore. The water is pumped to the city from a large distance of approximately 100km over a very high elevation of approximately 400m. The city has large undulating terrain among different zones, which leads to unequal distribution of water. The Bangalore, inflow water-distribution system (WDS) has been modeled. A dynamic inversion (DI) nonlinear controller with proportional integral derivative (PID) features (DI-PID) is used for valve throttling to achieve the target flows to different zones of the city. This novel approach of equitable water distribution using DI-PID controllers that can be used as a decision support system is discussed in this paper.

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A fuzzy waste-load allocation model, FWLAM, is developed for water quality management of a river system using fuzzy multiple-objective optimization. An important feature of this model is its capability to incorporate the aspirations and conflicting objectives of the pollution control agency and dischargers. The vagueness associated with specifying the water quality criteria and fraction removal levels is modeled in a fuzzy framework. The goals related to the pollution control agency and dischargers are expressed as fuzzy sets. The membership functions of these fuzzy sets are considered to represent the variation of satisfaction levels of the pollution control agency and dischargers in attaining their respective goals. Two formulations—namely, the MAX-MIN and MAX-BIAS formulations—are proposed for FWLAM. The MAX-MIN formulation maximizes the minimum satisfaction level in the system. The MAX-BIAS formulation maximizes a bias measure, giving a solution that favors the dischargers. Maximization of the bias measure attempts to keep the satisfaction levels of the dischargers away from the minimum satisfaction level and that of the pollution control agency close to the minimum satisfaction level. Most of the conventional water quality management models use waste treatment cost curves that are uncertain and nonlinear. Unlike such models, FWLAM avoids the use of cost curves. Further, the model provides the flexibility for the pollution control agency and dischargers to specify their aspirations independently.

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Uncertainty plays an important role in water quality management problems. The major sources of uncertainty in a water quality management problem are the random nature of hydrologic variables and imprecision (fuzziness) associated with goals of the dischargers and pollution control agencies (PCA). Many Waste Load Allocation (WLA)problems are solved by considering these two sources of uncertainty. Apart from randomness and fuzziness, missing data in the time series of a hydrologic variable may result in additional uncertainty due to partial ignorance. These uncertainties render the input parameters as imprecise parameters in water quality decision making. In this paper an Imprecise Fuzzy Waste Load Allocation Model (IFWLAM) is developed for water quality management of a river system subject to uncertainty arising from partial ignorance. In a WLA problem, both randomness and imprecision can be addressed simultaneously by fuzzy risk of low water quality. A methodology is developed for the computation of imprecise fuzzy risk of low water quality, when the parameters are characterized by uncertainty due to partial ignorance. A Monte-Carlo simulation is performed to evaluate the imprecise fuzzy risk of low water quality by considering the input variables as imprecise. Fuzzy multiobjective optimization is used to formulate the multiobjective model. The model developed is based on a fuzzy multiobjective optimization problem with max-min as the operator. This usually does not result in a unique solution but gives multiple solutions. Two optimization models are developed to capture all the decision alternatives or multiple solutions. The objective of the two optimization models is to obtain a range of fractional removal levels for the dischargers, such that the resultant fuzzy risk will be within acceptable limits. Specification of a range for fractional removal levels enhances flexibility in decision making. The methodology is demonstrated with a case study of the Tunga-Bhadra river system in India.

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Beavers are often found to be in conflict with human interests by creating nuisances like building dams on flowing water (leading to flooding), blocking irrigation canals, cutting down timbers, etc. At the same time they contribute to raising water tables, increased vegetation, etc. Consequently, maintaining an optimal beaver population is beneficial. Because of their diffusion externality (due to migratory nature), strategies based on lumped parameter models are often ineffective. Using a distributed parameter model for beaver population that accounts for their spatial and temporal behavior, an optimal control (trapping) strategy is presented in this paper that leads to a desired distribution of the animal density in a region in the long run. The optimal control solution presented, imbeds the solution for a large number of initial conditions (i.e., it has a feedback form), which is otherwise nontrivial to obtain. The solution obtained can be used in real-time by a nonexpert in control theory since it involves only using the neural networks trained offline. Proper orthogonal decomposition-based basis function design followed by their use in a Galerkin projection has been incorporated in the solution process as a model reduction technique. Optimal solutions are obtained through a "single network adaptive critic" (SNAC) neural-network architecture.

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Due to increasing trend of intensive rice cultivation in a coastal river basin, crop planning and groundwater management are imperative for the sustainable agriculture. For effective management, two models have been developed viz. groundwater balance model and optimum cropping and groundwater management model to determine optimum cropping pattern and groundwater allocation from private and government tubewells according to different soil types (saline and non-saline), type of agriculture (rainfed and irrigated) and seasons (monsoon and winter). A groundwater balance model has been developed considering mass balance approach. The components of the groundwater balance considered are recharge from rainfall, irrigated rice and non-rice fields, base flow from rivers and seepage flow from surface drains. In the second phase, a linear programming optimization model is developed for optimal cropping and groundwater management for maximizing the economic returns. The models developed were applied to a portion of coastal river basin in Orissa State, India and optimal cropping pattern for various scenarios of river flow and groundwater availability was obtained.

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We conducted surveys of fire and fuels managers at local, regional, and national levels to gain insights into decision processes and information flows in wildfire management. Survey results in the form of fire managers’ decision calendars show how climate information needs vary seasonally, over space, and through the organizational network, and help determine optimal points for introducing climate information and forecasts into decision processes. We identified opportunities to use climate information in fire management, including seasonal to interannual climate forecasts at all organizational levels, to improve the targeting of fuels treatments and prescribed burns, the positioning and movement of initial attack resources, and staffing and budgeting decisions. Longer-term (5–10 years) outlooks also could be useful at the national level in setting budget and research priorities. We discuss these opportunities and examine the kinds of organizational changes that could facilitate effective use of existing climate information and climate forecast capabilities.

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The restoration, conservation and management of water resources require a thorough understanding of what constitutes a healthy ecosystem. Monitoring and assessment provides the basic information on the condition of our waterbodies. The present work details the study carried out at two waterbodies, namely, the Chamarajasagar reservoir and the Madiwala Lake. The waterbodies were selected on the basis of their current use and locations. Chamarajasagar reservoir serves the purpose of supplying drinking water to Bangalore city and is located on the outskirts of the city surrounded by agricultural and forest land. On the other hand, Madiwala lake is situated in the heart of Bangalore city receiving an influx of pollutants from domestic and industrial sewage. Comparative assessment of the surface water quality of both were carried out by instituting the various physico–chemical and biological parameters. The physico-chemical analyses included temperature, transparency, pH, electrical conductivity, dissolved oxygen, alkalinity, total hardness, calcium hardness, magnesium hardness, nitrates, phosphates, sodium, potassium and COD measurements of the given waterbody. The analysis was done based on the standard methods prescribed (or recommended) by (APHA) and NEERI. The biological parameter included phytoplankton analysis. The detailed investigations of the parameters, which are well within the tolerance limits in Chamarajasagar reservoir, indicate that it is fairly unpolluted, except for the pH values, which indicate greater alkalinity. This may be attributed to the natural causes and the agricultural runoff from the catchment. On the contrary, the limnology of Madiwala lake is greatly influenced by the inflow of sewage that contributes significantly to the dissolved solids of the lake water, total hardness, alkalinity and a low DO level. Although, the two study areas differ in age, physiography, chemistry and type of inflows, they still maintain a phytoplankton distribution overwhelmingly dominated by Cyanophyceae members,specifically Microcystis aeruginosa. These blue green algae apparently enter the waterbodies from soil, which are known to harbour a rich diversity of blue green flora with several species common to limnoplankton, a feature reported to be unique to the south Indian lakes.Chamarajasagar water samples revealed five classes of phytoplankton, of which Cyanophyceae (92.15 percent) that dominated other algal forms comprised of one single species of Microcystis aeruginosa. The next major class of algae was Chlorophyceae (3.752 percent) followed by Dinophyceae (3.51 percent), Bacillariophyceae (0.47 percent) and a sparsely available and unidentified class (0.12 percent).Madiwala Lake phytoplankton, in addition to Cyanophyceae (26.20 percent), revealed a high density of Chlorophyceae members (73.44 percent) dominated by Scenedesmus sp.,Pediastrum sp., and Euglena sp.,which are considered to be indicators of organic pollution. The domestic and industrial sewage, which finds its way into the lake, is a factor causing organic pollution. As compared to the other classes, Euglenophyceae and Bacillariophyceae members were the lowest in number. Thus, the analysis of various parameters indicates that Chamarajasagar reservoir is relatively unpolluted except for the high percentage of Microcystis aeruginosa, and a slightly alkaline nature of water. Madiwala lake samples revealed eutrophication and high levels of pollution, which is clarified by the physico–chemical analysis, whose values are way above the tolerance limits. Also, the phytoplankton analysis in Madiwala lake reveals the dominance of Chlorophyceae members, which indicate organic pollution (sewage being the causative factor).

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Ground management problems are typically solved by the simulation-optimization approach where complex numerical models are used to simulate the groundwater flow and/or contamination transport. These numerical models take a lot of time to solve the management problems and hence become computationally expensive. In this study, Artificial Neural Network (ANN) and Particle Swarm Optimization (PSO) models were developed and coupled for the management of groundwater of Dore river basin in France. The Analytic Element Method (AEM) based flow model was developed and used to generate the dataset for the training and testing of the ANN model. This developed ANN-PSO model was applied to minimize the pumping cost of the wells, including cost of the pipe line. The discharge and location of the pumping wells were taken as the decision variable and the ANN-PSO model was applied to find out the optimal location of the wells. The results of the ANN-PSO model are found similar to the results obtained by AEM-PSO model. The results show that the ANN model can reduce the computational burden significantly as it is able to analyze different scenarios, and the ANN-PSO model is capable of identifying the optimal location of wells efficiently.

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At low temperature (below its freezing/melting temperature), liquid water under confinement is known to exhibit anomalous dynamical features. Here we study structure and dynamics of water in the grooves of a long DNA duplex using molecular dynamics simulations with TIP5P potential at low temperature. We find signatures of a dynamical transition in both translational and orientational dynamics of water molecules in both the major and the minor grooves of a DNA duplex. The transition occurs at a slightly higher temperature (TGL ≈ 255 K) than the temperature at which the bulk water is found to undergo a dynamical transition, which for the TIP5P potential is at 247 K. Groove water, however, exhibits markedly different temperature dependence of its properties from the bulk. Entropy calculations reveal that the minor groove water is ordered even at room temperature, and the transition at T ≈ 255 K can be characterized as a strong-to-strong dynamical transition. Confinement of water in the grooves of DNA favors the formation of a low density four-coordinated state (as a consequence of enthalpy−entropy balance) that makes the liquid−liquid transition stronger. The low temperature water is characterized by pronounced tetrahedral order, as manifested in the sharp rise near 109° in the O−O−O angle distribution. We find that the Adams−Gibbs relation between configurational entropy and translational diffusion holds quite well when the two quantities are plotted together in a master plot for different region of aqueous DNA duplex (bulk, major, and minor grooves) at different temperatures. The activation energy for the transfer of water molecules between different regions of DNA is found to be weakly dependent on temperature.

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Water adsorbs molecularly on a clean Zn(0001) surface; on a surface covered with atomic oxygen, however, hydroxyl species is produced due to proton abstraction by the surface oxygen atoms. Methanol, molecularly adsorbed on a clean surface at 80 K, transforms to methoxy species above 110 K. On an atomic oxygen-covered surface, adsorbed methanol gives rise to methoxy species and water, the latter arising from proton abstraction. HCHO adsorbs molecularly at 80 K on both clean as well as oxygen-covered surfaces and polymerizes at higher temperatures. Formic acid does not adsorb on a clean Zn surface, but on an oxygen-covered surface gives rise to formate and hydroxyl species.

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Ultrafine powders of SrTiO3 are prepared at 100–150°C by the hydrothermal method, starting from TiO2·xH2O gel and Sr(OH)2 and H2O-isopropanol mixed solvent as the medium, The X-ray diffractograms of the powder show line broadening. The minimum crystallite size obtained ranges from 5 to 20nm with 20% H2O-80% C3H7OH as the reaction medium, as estimated from X-ray half-peak widths and TEM studies. The electron diffraction results indicate high concentration of lattice defects in these crystallites. The optical spectra of the particle suspensions in water show that the absorption around the band gap is considerably broadened, together with the appearance of maxima in the far ultraviolet. Aqueous suspensions of SrTiO3 powders, as such, do not produce H2 or O2 on UV irradiation. After coating with rhodium, H2 and O2 are evolved on illumination. However, the turn over number of O2 is lower than the stoichiometrically expected values from the corresponding values of H2. No correlation of the photocatalytic activity with surface area is observed. The activity of Rh-SrTiO3 slowly deteriorates with extended period of irradiation.

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The often discussed role of surface hydroxylation of TiO2 particles as an essential characterestics for their photocatalytic activity can be verified by preparing TiO2 powders by hydrothermal method since hydroxylated surface layers will be better retained on these particles formed in superheated water. Thus, fine powders of TiO2 (rutile) with high degree of crystallinity are formed from titanium oxychloride in the mixed solvent of water and 2-propanol at 160–230°C and 20–120 atm. The anatase phase is produced from the same medium when sulfate ion impurity is present, with Image . TiO2 powders are washed free of anions and 2-propanol by ultrafiltration and are Pt mounted by a photochemical method. Aqueous suspensions of both forms of TiO2 neither as such nor after Pt-loading, do not produce H2 on band gap illumination whereas, H2 is generated in presence of hole scavengers such as EDTA, TEOA, sulfite or hypophosphite. The effects of hole scavenger concentration, Pt : TiO2 ratio, particulate suspension density and the nature of hole scavengers on H2 production are presented. Platinised rutile powders are equally active as anatase in sacrificial systems.

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We used molecular dynamics (MD) simulations to study the reorientational dynamics of water molecules confined inside narrow carbon nanotubes immersed in a bath of water. Our simulations show that the confined water molecules exhibit bistability in their reorientational relaxation, which proceeds by angular jumps between the two stable states. The angular jump of a water molecule in the bulk involves the breaking of a hydrogen bond with one of its neighbors and the formation of a hydrogen bond with a different neighbor. In contrast, the angular jump of a confined water molecule corresponds to an interchange of the two hydrogen atoms that can form a hydrogen bond with the same neighbor. The free energy barrier between these two states is a few k(B)T. The analytic solution of a simplified two-state jump model that qualitatively explains the reorientational behavior observed in simulations is also presented.

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In our earlier work ([1]) we proposed WLAN Manager (or WM) a centralised controller for QoS management of infrastructure WLANs based on the IEEE 802.11 DCF standards. The WM approach is based on queueing and scheduling packets in a device that sits between all traffic flowing between the APs and the wireline LAN, requires no changes to the AP or the STAs, and can be viewed as implementing a "Split-MAC" architecture. The objectives of WM were to manage various TCP performance related issues (such as the throughput "anomaly" when STAs associate with an AP with mixed PHY rates, and upload-download unfairness induced by finite AP buffers), and also to serve as the controller for VoIP admission control and handovers, and for other QoS management measures. In this paper we report our experiences in implementing the proposals in [1]: the insights gained, new control techniques developed, and the effectiveness of the WM approach in managing TCP performance in an infrastructure WLAN. We report results from a hybrid experiment where a physical WM manages actual TCP controlled packet flows between a server and clients, with the WLAN being simulated, and also from a small physical testbed with an actual AP.