Modeling Equitable Distribution of Water: Dynamic Inversion-Based Controller Approach

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.

Fuzzy optimization model for water quality management of a river system - Closure

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.

An imprecise fuzzy risk approach for water quality management of a river system

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.

The potential of certification for conservation and management of wild MAP resources

Medicinal and aromatic plants (MAPs) are an integral part of our biodiversity. In majority of MAP rich countries, wild collection practices are the livelihood options for a large number of rural peoples and MAPs play a significant role in socio-economic development of their communities. Recent concern over the alarming situation of the status of wild MAP resources, raw material quality, as well as social exploitation of rural communities, leads to the idea of certification for MAP resource conservation and management. On one hand, while MAP certification addresses environmental, social and economic perspectives of MAP resources, on the other hand, it ensures multi-stakeholder participation in improvement of the MAP sector. This paper presents an overview of MAP certification encompassing its different parameters, current scenario (Indian background), implementation strategies as well as stakeholders’ role in MAP conservation. It also highlights Indian initiatives in this direction.

Optimal management of beaver population using a reduced-order distributed parameter model and single network adaptive critics

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.

Optimal crop planning and conjunctive use of water resources in a coastal river basin

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.

Ecological Assessment of Lentic Water Bodies of Bangalore

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).

Application of Artificial Neural Networks and Particle Swarm Optimization for the Management of Groundwater Resources

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.

Biogeochemical facsimile of the organic matter quality and trophic status of a micro-tidal tropical estuary

Seasonal studies were carried out from 21 stations, comprising of three zones, of Cochin Estuary, to assess the organic matter quality and trophic status. The hydographical parameters showed significant seasonal variations and nutrients and chlorophylls were generally higher during the monsoon season. However, chemical contamination along with the seasonal limitations of light and nitrogen imposed restrictions on the primary production and as a result, mesotrophic conditions generally prevailed in the water column. The nutrient stoichometries and delta C-13 values of surficial sediments indicated significant allochthonous contribution of organic matter. Irrespective of the higher content of total organic matter, the labile organic matter was very low. Dominance of carbohydrates over lipids and proteins indicated the lower nutritive aspect of the organic matter, and their aged and refractory nature. This, along with higher amount of phytodetritus and the low algal contribution to the biopolymeric carbon corroborated the dominance of allochthonous organic matter and the heterotrophic nature. The spatial and seasonal variations of labile organic components could effectively substantiate the observed shift in the productivity pattern. An alternative ratio, lipids to tannins and lignins, was proposed to ascertain the relative contribution of allochthonous organic matter in the estuary. This study confirmed the efficiency of an integrated biogeochemical approach to establish zones with distinct benthic trophic status associated with different degrees of natural and anthropogenic input. Nevertheless, our results also suggest that the biochemical composition alone could lead to erroneous conclusions in the case of regions that receive enormous amounts of anthropogenic inputs.

An eels study of water, methanol, formaldehyde and formic acid adsorbed on clean and oxygen-covered zinc(0001) surfaces

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.

Ultrafine powders of SrTiO3 from the hydrothermal preparation and their catalytic activity in the photolysis of water

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.

Ce0.67Cr0.33O2.11: A New Low-Temperature O-2 Evolution Material and H-2 Generation Catalyst by Thermochemical Splitting of Water

Ce0.67Cr0.33O2.11 was synthesized by hydrothermal method using diethylenetriamine as complexing agent (Chem. Mater. 2008, 20, 7268). Ce0.67Cr0.33O2.11 being the only compound likes UO2+delta to have excess oxygen, it releases a large proportion of its lattice oxygen (0.167 M [O]/mole of compound) at relatively low temperature (465 degrees C) directly and it has been utilized for generation of H-2 by thermo-splitting of water. An almost stoichiometric amount of H-2 (0.152 M/Mole of compound) is generated at much lower temperature (65 degrees C). There is an almost comparable amount of oxygen release and hydrogen generation over this material at very low temperature comparedto other CeO2-MOx (Mn, Fe, Cu, and Ni) mixed-oxide solid solutions (O-2 evolution >= 1300 degrees C and H-2 generation at 1000 degrees C). The reversible nature of oxygen release and intake of this material is attributed to its fluorite Structure and coupling between the Ce4+/Ce3+ and Cr4+/6+/Cr3+ redox couples. Compound shows reversible oxygen release and intake by H2O absorption and subsequent hydrogen release to gain parent structure and hence this material can be utilized for generation of H-2 at very low temperature by thermo-chemical splitting of water.

Enhanced Tetrahedral Ordering of Water Molecules in Minor Grooves of DNA: Relative Role of DNA Rigidity, Nanoconfinement, and Surface Specific Interactions

Confinement and Surface specific interactions call induce Structures otherwise unstable at that temperature and pressure. Here we Study the groove specific water dynamics ill the nucleic acid sequences, poly-AT and poly-GC, in long B-DNA duplex chains by large scale atomistic molecular dynamics simulations, accompanied by thermodynamic analysis. While water dynamics in the major groove remains insensitive to the sequence differences, exactly the opposite is true for the minor groove water. Much slower water dynamics observed in the minor grooves (especially in the AT minor) call be attributed to all enhanced tetrahedral ordering (< t(h)>) of water. The largest value of < t(h)> in the AT minor groove is related to the spine of hydration found in X-ray Structure. The calculated configurational entropy (S-C) of the water molecules is found to be correlated with the self-diffusion coefficient of water in different region via Adam-Gibbs relation D = A exp(-B/TSC), and also with < t(h)>.

Two-Phase Thermodynamic Model for Efficient and Accurate Absolute Entropy of Water from Molecular Dynamics Simulations

Presented here is the two-phase thermodynamic (2PT) model for the calculation of energy and entropy of molecular fluids from the trajectory of molecular dynamics (MD) simulations. In this method, the density of state (DoS) functions (including the normal modes of translation, rotation, and intramolecular vibration motions) are determined from the Fourier transform of the corresponding velocity autocorrelation functions. A fluidicity parameter (f), extracted from the thermodynamic state of the system derived from the same MD, is used to partition the translation and rotation modes into a diffusive, gas-like component (with 3Nf degrees of freedom) and a nondiffusive, solid-like component. The thermodynamic properties, including the absolute value of entropy, are then obtained by applying quantum statistics to the solid component and applying hard sphere/rigid rotor thermodynamics to the gas component. The 2PT method produces exact thermodynamic properties of the system in two limiting states: the nondiffusive solid state (where the fluidicity is zero) and the ideal gas state (where the fluidicity becomes unity). We examine the 2PT entropy for various water models (F3C, SPC, SPC/E, TIP3P, and TIP4P-Ew) at ambient conditions and find good agreement with literature results obtained based on other simulation techniques. We also validate the entropy of water in the liquid and vapor phases along the vapor-liquid equilibrium curve from the triple point to the critical point. We show that this method produces converged liquid phase entropy in tens of picoseconds, making it an efficient means for extracting thermodynamic properties from MD simulations.