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ID: 60720
Title: Harnessing solar energy for wastewater treatment.
Author: Ritesh Jain, Jaspal Singh and Sunil Garg.
Editor: Dr.D.G.Regulwar, Dr.K.A.Patil, Dr.U.J.Kahalekar, Dr.P.A.Sadgir.
Year: 2008
Publisher: Excel India Publishers
Source: Centre for Ecological Sciences
Reference: Sustainable Water Resources Development and Management, 347-353, June (2008)
Subject: Sustainable Water Resources Development and Management
Keywords: Solar distillation, wastewater, water, BOD.
Abstract: The quality and quantity of water of any area is of paramount importance not only for human beings but for other purposes such as irrigation. Due to urbanization and industrialization, resources of drinking water are depleting day by day and pollution level has increased resulting into water having physical, chemical or bacteriological impurities. Therefore it is the right time to make use of wastewater after suitable treatment. Researchers focused their study on waste-water in order to obtain fresh potable water by treatment of this water. The treatment of sewage water commercially is an extremely laborious and expensive task, as it requires installation of a large treatment plant. Amongst various techniques, treatability of wastewater can be achieved by harnessing natural resources of energy using solar distillation still. The authors have carried out a study on treatability of wastewater using solar distillation still.
Location: T E 15 New Biology Building.
Literature cited 1: Thomas, Deniel, Pratt and Whitney A. ?Study of performance of single effect solar distillation still, ?International Journal for Scientists, Engineers and Technologists in Soar Energy and its application, 44 (1), 1990, pp. 43-55. Kumar, A. and Tiwari G.N. ?Transient analysis of double slope double basin solar distiller, ?Energy Conversion Management, 31, 1991, pp. 129-39.
Literature cited 2: Adhikari R.S., Kumar A. and Sootha G.D. ?Steady state performance of multistage, stacked tray solar still, ?Comparison between basin type solar still and solar evaporator,? International Solar Energy Society, 56 (1), 1996, pp. 199-212. Sartori and Ernani. ?Comparison between basin type solar still and solar evaporator, ?International Solar Energy Society, 56 (1), 1996, pp. 199-212.

ID: 60719
Title: Bioenergy recovery during treatment of organic wastes.
Author: Dr. M.M. Ghangrekar
Editor: Dr.D.G.Regulwar, Dr.K.A.Patil, Dr.U.J.Kahalekar, Dr.P.A.Sadgir.
Year: 2008
Publisher: Excel India Publishers
Source: Centre for Ecological Sciences
Reference: Sustainable Water Resources Development and Management, 334-346, June (2008)
Subject: Sustainable Water Resources Development and Management
Keywords: Organic Waste, methane, bio-ethanol, bio-electricity, microbial fuel cell.
Abstract: A paradigm shift in the mind set of the waste manager is required. Instead of calling unwanted material as waste, it can be considered as a resource to recover valuable byproduct from it, simultaneously reducing pollution load on the environment. This paper highlights some of the ways to recover byproducts from the organic fraction of solid waste and organic wastewaters. The byproducts such as methane and ethanol can be recovered from the solid waste; and methane, biomass and other useful chemicals can be recovered from the biodegradable organic liquid waste using fermentation process. New concept of wastewater treatment is coming up in the form of microbial fuel cell (MFC). Application of microbial fuel cell will make it possible to recover direct electricity for onsite application with simultaneous treatment of wastewater.
Location: T E 15 New Biology Building.
Literature cited 1: AngenentL. T., Khursheed K., Muthanna H. Al-D., Brain A. Wrenn and Rosa Domyguez-Espinosa. ?Production of bioenergy and biochemicals from industrial and agricultural wastewater, ?TRENDS in Biotechnology, 22 (9), 2004. Boeriu C.G. van Dam J.E.G., Sanders J.P.M. Biomass valorization for sustainable development. In Biofuels for Fuel cells, Ed.Lens Piet, Westermann Peter, Haberbauer Marianne and Moreno Angelo, IWA publishing, London. 2005.
Literature cited 2: Chen S., Liao W. Liu C., Wen Z., Kincaid RL, Harrison J.H., ?Use of animal manure as feedback for bio-products? In: Proc. Of Ninth International Animal, Agriculture and Food processing Wastes Symp, 2003, pp. 50-7. Chen S., Liao W. Liu C., Wen Z., Kincaid RL,Harrison J.H., et al. Value-added chemicals animal manures. Northwest Bioproducts Research Institute Technical Report.US Department of Energy Contract DE-AC06 -76 RLO 1830; 2004, pp 135.

ID: 60718
Title: Moving towards 24X7 continuous water supply system.
Author: Dr. Sanjay Dahasahasra and Mrs. Madhuri Mulay
Editor: Dr.D.G.Regulwar, Dr.K.A.Patil, Dr.U.J.Kahalekar, Dr.P.A.Sadgir.
Year: 2008
Publisher: Excel India Publishers
Source: Centre for Ecological Sciences
Reference: Sustainable Water Resources Development and Management, 323-333, June (2008)
Subject: Sustainable Water Resources Development and Management
Keywords: None
Abstract: One of the impediments to achieve the Millennium Development Goals is the intermittent water supply in developing countries. In India no city provides 24 x 7 continuous water supply to their residents. And in Asia very few cities have this hallmark. There have been various attempts to achieve this most challengeable task. Objective of this paper, therefore, is to present a methodology which can be transform an intermittent water supply of a city into 24x 7 continuous water system. It also unfolds various characteristics of the hydraulic model that has been prepared to simulate the real time conditions in the distribution system and describes how it could be applied for developing countries. The approach has been discussed in details along with its application and a case study of Badlapur
Location: T E 15 New Biology Building.
Literature cited 1: Chary ?24-Hour Water Supply: A Goal Achievable? Nagari, A Publication of ASCI, Hyderabad, 2005. Walski H. and et al, ?Advanced Water Distribution Modeling and Management,?Haested Methods, First Edition, 2003.
Literature cited 2: SIWI report (2004) A Report of World Bank, October 2005.

ID: 60717
Title: RBF neural network to forecast seasonal reservoir inflow
Author: Alka Kote and S.B. Charhate.
Editor: Dr.D.G.Regulwar, Dr.K.A.Patil, Dr.U.J.Kahalekar, Dr.P.A.Sadgir.
Year: 2008
Publisher: Excel India Publishers
Source: Centre for Ecological Sciences
Reference: Sustainable Water Resources Development and Management, 315-319, June (2008)
Subject: Sustainable Water Resources Development and Management
Keywords: Artificial neural network; RBF network; Reservoir inflow; Time series.
Abstract: Hydrologic forecasting helps improve planning and operation of hydro-systems, especially under flood and drought conditions. Similarly inflow prediction based on daily as well as monthly in any reservoir is a key element for reservoir planning and operation. This paper discusses an approach of radial basis function (RBF) type of artificial neural networks (ANNs) to forecast average daily as well as monthly reservoir inflow for seasonal period (June to October). The ANN models are developed for Koyna reservoir located in Krishna River Basin to evaluate their performances. Forty-four years daily and monthly reservoir inflow data were used for the study. It was found that the three previous values of daily or monthly inflow were found sufficient to predict next month inflow. Standard statistical parameters including mean, standard deviation, skewness and kurtosis of the forecasted tie series were compared with observed inflow values .Error criteria and Goodness-of-fit measures such as correlation coefficient (R), root mean square error (RMSE) and mean absolute error (MAE) were used to compare the performance of the models. The forecast made using RBF network for average daily inflow showed excellent results.
Location: T E 15 New Biology Building.
Literature cited 1: Box G.E.P, and Jenkins G.M. Time Series Analysis, Forecasting & Control, Holden Day Inc., San Fransisco, California, USA, 1976. Nokes D.J., Mcleod I, and Hipel K.W. ?Forecasting monthly river flow time series,? International Journal of Forecasting, 1, 1985, pp. 179-190.
Literature cited 2: T he ASCE Task Committee, ?Artificial neural networks in Hydrology-I: Preliminary concepts,?J. of Hydrologic Eng., 5 (2), 2000, pp. 115-123. The ASCE Task Committee, ?Artificial neural networks in Hydrology-II: Hydrologic applications,?J.of Hydrologic Eng., 5 (2), 2000, pp.124-137.

ID: 60716
Title: Correlating stream gauging stations using Ann.
Author: Dr. S.N. Londhe and S.B. Charhate
Editor: Dr.D.G.Regulwar, Dr.K.A.Patil, Dr.U.J.Kahalekar, Dr.P.A.Sadgir.
Year: 2008
Publisher: Excel India Publishers
Source: Centre for Ecological Sciences
Reference: Sustainable Water Resources Development and Management, 309-314, June (2008)
Subject: Sustainable Water Resources Development and Management
Keywords: stream gauging; correlation, Artificial neural network.
Abstract: Flood forecasting is an essential tool in the production of effective flood warnings. Many flood forecasting systems generally have relied upon traditional hydrological modeling approaches. These often feature the use of a rainfall-runoff model to simulate flow in the upper catchment. The resulting flow is then routed to the lower catchment via a routing model. It has been suggested that a neural network approach may provide an attractive alternative to the traditional flood forecasting techniques, especially for data-limited catchments. The present work deals with correlation of discharge at two stations Mandaleshwar and Rajghat along Narmada River using the soft computing technique of Artificial Neural Networks. Four separate models are developed to estimate daily average discharge at Rajghat using the same at Mandaleshwar for the monsoon to estimate daily average discharge at Rajghat using the same at Mandaleshwar for the monsoon months of July, August, September and October. For non-monsoon months a single model is developed .The developed models show reasonable accuracy in flow estimation at Rajghat.
Location: T E 15 New Biology Building.
Literature cited 1: Moore R.J., Jones DA, Bird PB, Cottingham MC.?A basin-wide flow forecasting system for real-time flood warning, river control and water management, ?In River Flood Hydraulics. Institute of Hydrology: Wallingford, 1990. Lees M, Young PC, Beven K.J., Ferguson S, Burns J. ?An adaptive flood warning system for the River Nith at Dumfries. In River Flood Hydraulics, White WR, Watts J (eds). Institute of Hydrology: Wallingford, 1990.
Literature cited 2: Khondker M.U.H., Wilson G, Klinting A.?Application of neural networks in real time flash flood forecasting, ?In Hydroinformatics ' 98, Babovic V, Larsen LC (eds). Balkema: Rotterdam, 1998, pp 777-781. Kneale P.E., See L, Kerr P.?Developing a prototype neural net flood forecasting model for use by the Environment Agency, ?Proceedings 35th MAFF Conference of River and Coastal Engineers, 5-7 July, University of Keele, 2000a, 11.03.1-11.03.4.

ID: 60715
Title: Air quality modeling using Ann- A case study of Pune
Author: Ms S.S. Tikhe, Dr. S.N.Londhe and Dr. Mrs. K.C. Khare
Editor: Dr.D.G.Regulwar, Dr.K.A.Patil, Dr.U.J.Kahalekar, Dr.P.A.Sadgir.
Year: 2008
Publisher: Excel India Publishers
Source: Centre for Ecological Sciences
Reference: Sustainable Water Resources Development and Management, 303-308, June (2008)
Subject: Sustainable Water Resources Development and Management
Keywords: Air pollution, RSPM, Artificial Neural networks
Abstract: Air quality modeling is the most essential prerequisite of modern pollution studies. The air quality parameters such as RSPM (Respirable Suspended Particulate Matter) Sox (Oxides of Sulphur), NOx (Oxides of Nitrogen) are measured at various planes for different time intervals. The measured data in the form of time series can further be used to forecast these parameters. At least for few steps in advance using either statistical or data driven modeling approaches. Such an advent would prove to be very useful as far as severity of pollution problem is concerned. Pune is the 8th largest city in India and one of mostly polluted cities all the around the world. The present work aims at predicting RSPM at one of the busiest squares in Pune city using the previous values of RSPM measured at the same place. Data of daily average concentrations of RSPM measured at the same place. Data of daily average concentrations of RSPM values is available for the months of April to July for a period of 3 years from 2005 to 2007. As the previous values of RSPM are to be used the data driven approach of Artificial Neural Network is used to develop a RSPM model for forecasting RSPM concentration 2 days in advance. The 3 layered feed forward network performs reasonably well as evident by a higher correlation coefficient of 0.81 between the observed and network predicted RSPM values. The paper also presents a study about effect of length of training data on network testing. The technique of ANN can thus be explored further to model more pollution parameters owing to the highly encouraging results obtained in this work.
Location: T E 15 New Biology Building.
Literature cited 1: Antonacci 1 G, Franceschi M., and Zardi M.?Numerical Air Quality Modelling along the Brenner South Route Within the Alpnap Project,? Proceedings of the 29th International Conference on alpine Meteorology, Chambery, France, 2007, pp. 206-213. Barai S.V, Dikshit A.K., and Sameer Sharma ?ANN for Air quality Prediction-A comparative Study, ?Advances in Soft computing, Springer Berlin Publication, 39, 2007, pp.290-305.
Literature cited 2: Bose N.K., and Liang P.?Neural Network Fundamentals with Graphs, Algorithms and Applications, ?Tata McGraw-Hill publication 1998. Camposa I.C.B., Pimentela A.S., S.M. Correa a, b, and G. Arbilla, ?Simulation of Air Pollution from Mobile Source Emissions in the City of Rio de Janeiro,? Journal of Brazilian chemical Society, 10 (3), 1999, pp. 203-208.

ID: 60714
Title: Analysis of pipe distribution network for irrigation by genetic algorithm & computational fluid dynamics.
Author: Maya M. Karulekar and Sagar A. Giri.
Editor: Dr.D.G.Regulwar, Dr.K.A.Patil, Dr.U.J.Kahalekar, Dr.P.A.Sadgir.
Year: 2008
Publisher: Excel India Publishers
Source: Centre for Ecological Sciences
Reference: Sustainable Water Resources Development and Management, 294-302, June (2008)
Subject: Sustainable Water Resources Development and Management
Keywords: Irrigation, Pipe distribution network, Genetic Algorithm, Computational Fluid Dynamics.
Abstract: Declining investment in the irrigation sector, increasing environmental concerns and long gestation period in turning the irrigation potential into a functional system are shifting the focus to improving existing irrigation systems rather than creating more potential. System performance monitoring, evaluating and diagnostic analysis are the keys to an improved irrigation management. One of the system performance monitoring matrices is to evaluate water demand and supplies in the irrigation system and identify the water deficit and surplus areas for corrective measures. Pipe distribution network is one of the best solutions to satisfy water requirement of field, as the overall efficiency of pipe system is more compared to open canal system. This paper presents an analysis of pipe distribution network for irrigation of Kasner Minor Irrigation Tank. Cost analysis carried out by using Genetic Algorithm results into various configurations. Flow analysis is carried out by using Computational Fluid Dynamics. It is observed that the selected set of dimensions for the network satisfies the requirements of the discharge.
Location: T E 15 New Biology Building.
Literature cited 1: Afshar M.H.and Marino M.A. ?A Convergent Genetic Algorithm for pipe Network Optimization, ?Scientia Iranica, Sharif University of Technology, 2005, pp 392-401. Hossein M.V. Samani and Alireza M. ?Optimization of Water Distribution Networks Using Integer Linear Programming, ?J.Hydr.Engrg? 132 (5), 2006, pp. 501-509.
Literature cited 2: Zecchina A.C., Simpsona A.R., Maiera H.R., Leonarda M. Robertsb A.J., Berrisforda M. ?Application of two ant colony optimization algorithms to water distribution system optimization, ?Mathematical and Computer Modelling, 44, 2006, pp. 451-468. Cisty M. ?Advantages of using Genetic Algorithm over Deter, inistic Methods in Optimal Design of the Water Networks Rehabilitation,? Proceedings of Algoritmy 2000 Conference on Scientific Computing, pp. 293-300.

ID: 60713
Title: Analysis of pipe distribution network for irrigation by genetic algorithm & computational fluid dynamics
Author: Maya M. Karulekar and Sagar A. Giri.
Editor: Dr.D.G.Regulwar, Dr.K.A.Patil, Dr.U.J.Kahalekar, Dr.P.A.Sadgir.
Year: 2008
Publisher: Excel India Publishers
Source: Centre for Ecological Sciences
Reference: Sustainable Water Resources Development and Management, 290-293, June (2008)
Subject: Sustainable Water Resources Development and Management
Keywords: Irrigation, Pipe distribution network, Genetic Algorithm, Computational Fluid Dynamics.
Abstract: Declining investment in the irrigation sector, increasing environmental concerns and long gestation period in turning the irrigation potential into a functional system are shifting the focus to improving existing irrigation systems rather than creating more potential. System performance monitoring, evaluating and diagnostic analysis are the keys to an improved irrigation management. One of the system performance monitoring matrices is to evaluate water demand and supplies in the irrigation system and identify the water deficit and surplus areas for corrective measures. Pipe distribution network is one of the best solutions to satisfy water requirement of field, as the overall efficiency of pipe system is more compared to open canal system. This paper presents an analysis of pipe distribution network for irrigation of Kasner Minor Irrigation Tank. Cost analysis carried out by using Genetic Algorithm results into various configurations. Flow analysis is carried out by using Computational Fluid Dynamics. It is observed that the selected set of dimensions for the network satisfies the requirements of the discharge.
Location: T E 15 New Biology Building.
Literature cited 1: Afshar M.H.and Marino M.A. ?A Convergent Genetic Algorithm for pipe Network Optimization, ?Scientia Iranica, Sharif University of Technology, 2005, pp 392-401. Hossein M.V. Samani and Alireza M. ?Optimization of Water Distribution Networks Using Integer Linear Programming, ?J.Hydr.Engrg? 132 (5), 2006, pp. 501-509.
Literature cited 2: Zecchina A.C., Simpsona A.R., Maiera H.R., Leonarda M. Robertsb A.J., Berrisforda M. ?Application of two ant colony optimization algorithms to water distribution system optimization, ?Mathematical and Computer Modelling, 44, 2006, pp. 451-468. Cisty M. ?Advantages of using Genetic Algorithm over Deter, inistic Methods in Optimal Design of the Water Networks Rehabilitation,? Proceedings of Algoritmy 2000 Conference on Scientific Computing, pp. 293-300.

ID: 60712
Title: Watershed development & management by use of GIS Tool.
Author: Varade Dipak D and Dr. Sunil Kute
Editor: Dr.D.G.Regulwar, Dr.K.A.Patil, Dr.U.J.Kahalekar, Dr.P.A.Sadgir.
Year: 2008
Publisher: Excel India Publishers
Source: Centre for Ecological Sciences
Reference: Sustainable Water Resources Development and Management, 283-289, June (2008)
Subject: Sustainable Water Resources Development and Management
Keywords: watershed development, thematic maps, GIS.
Abstract: Environment and development are the two wheels of the cart. However, they become antagonists at some points. It has been witnessed many a times that development is done at the cost of environment. Analysis and assessment tools like GIS have proved to be very efficient and effective and hence useful for management of natural resources. Watershed areas are prone to degradation accelerated by human interventions. Wastelands like gullied or ravenous land, upland with or without scrub, degraded pasture, degraded land under plantation; industrial waste-lands are found prevalently in watershed areas. Effectual management tools can be designed only with backup from various GIS tools. Wasteland developments in the watershed areas can be mitigated substantially by the proper and wide-ranging use of GIS. The management tools like leveling of gullies or ravines, gully plugging, contour bunding, contour trenching, can be implemented as per the characteristic of wasteland. Thus, wastelands can be managed and converted to arable land by the use of this refined method. The study was carried out with the objectives such as to prepare various thematic maps to find out the potential which contribute to the development of wastelands and to suggest appropriate mitigatory measures for the area.
Location: T E 15 New Biology Building.
Literature cited 1: N.C. Mondal et al, ?Modelling for pollutant migration in the tannery belt,?Dindigul Tamil Nadu India, Current Science, 89 (9), 2005, pp. 1600-1606
Literature cited 2: V.K. Saxena et al, ?Impact of pollution due to tanneries on groundwater regime, ?Current Science, 88 (12), 2005, pp.1988-1994.

ID: 60711
Title: Environmental decision support system for rational selection of wastewater treatment alternatives.
Author: Mammo Beriso and Dr. Shyam R. Asolekar..
Editor: Dr.D.G.Regulwar, Dr.K.A.Patil, Dr.U.J.Kahalekar, Dr.P.A.Sadgir.
Year: 2008
Publisher: Excel India Publishers
Source: Centre for Ecological Sciences
Reference: Sustainable Water Resources Development and Management, 276-282, June (2008)
Subject: Sustainable Water Resources Development and Management
Keywords: EDSS, Expert system, Wastewater treatment.
Abstract: Rational selection of the most appropriate technological alternative to deal with diverse environmental problems and issues, including wastewater treatment, is a big challenge in the field. The interrelated and complicated nature of the problem has made the process even more difficult. There are many environmental, public and cost related issues to be addressed while selecting best technological alternatives. Therefore, there is a need to have a simplifying tool to help in decision making. Environmental decision support systems (EDSS) are specific computer systems that are designed to help decision makes, managers, and advisors locate relevant information and carry out optimal solutions to problems using special tools and knowledge. In this paper a detailed discussion of TMSES, an expert decision support system we have developed to assist in making preferences over some secondary wastewater treatment technologies, is given. The paper also gives overviews to expert systems.
Location: T E 15 New Biology Building.
Literature cited 1: : Poch M., Comas J., Roda, I.R., Marre M.S., and Cortes, U. ?Designing and building real environmental decision support systems?, Environmental Modeling & Software 19, 2004, pp.857-873. Davis J.R., and Clark J.L. ?A selective bibliography of expert systems in natural resource management, ?AI Applications, 3, 1989, pp. 1-18.
Literature cited 2: Moninger, W.R., and Dyer, R.M. ?Survey of past and current AI work in the environmental sciences, ?AI Applications, 2, 1988, pp. 48-52. Akerkar R. ?Introduction to Artificial Intelligence, ?Prentice-Hall of India limited. 2005.

ID: 60710
Title: Recent trends in water resources systems modeling and management.
Author: Dr. M Janga Reddy.
Editor: Dr.D.G.Regulwar, Dr.K.A.Patil, Dr.U.J.Kahalekar, Dr.P.A.Sadgir.
Year: 2008
Publisher: Excel India Publishers
Source: Centre for Ecological Sciences
Reference: Sustainable Water Resources Development and Management, 263-275, June (2008)
Subject: Sustainable Water Resources Development and Management
Keywords: Evolutionary computation; genetic algorithms; swarm intelligence; particle swarm optimization; ant colony optimization; decision making.
Abstract: Recently many advanced technologies have been evolved for solving engineering problems such as evolutionary computation, swarm intelligence techniques and machine learning methods etc. Meta-heuristic techniques such as, Genetic Algorithms, Particle Swarm Optimization, Ant Colony Optimization etc have been developed for systems optimization. These methods have several attractive features and advantages, enable easy handling of complex relationships and help effective modeling of the engineering field, which requires use of such advanced computational tools for effective planning, design, and management of large scale projects. This keynote presentation will provide a brief introduction to the advanced optimization methods and their adoption to water resources management.
Location: T E 15 New Biology Building.
Literature cited 1: Deb K. Optimization for engineering design: Algorithms and examples. New Delhi, Prentice-Hall., 1996 Holland J.H. Adaptation in Natural and Artificial Systems, The MIT Press, 1975.
Literature cited 2: Goldberg, D.E. Genetic algorithms in search, optimization, and machine learning, Reading, MA: Addison-Wesley, 1989. Michalewicz Z. Genetic Algorithms + Data Structures +Evolution Programs, Springer, 1999.

ID: 60709
Title: Optimal Irrigation planning in Fuzzy Environment
Author: Sadhna M. Pawar and Dr. D.G. Regulwar
Editor: Dr.D.G.Regulwar, Dr.K.A.Patil, Dr.U.J.Kahalekar, Dr.P.A.Sadgir.
Year: 2008
Publisher: Excel India Publishers
Source: Centre for Ecological Sciences
Reference: Sustainable Water Resources Development and Management, 254-260, June (2008)
Subject: Sustainable Water Resources Development and Management
Keywords: Optimization, fuzzy linear programming, cropping pattern.
Abstract: The resources planners usually aim at identification or development of possible resources system, design or management plans and evaluation of their economic, ecological, environmental and social impacts. In this, single or combined decisions are sought on selection, sizing, target fixing, operation, capacity expansion, and financial planning etc in respect of a system. Since the late 1950s, system methodology has been successfully used to develop various techniques for solving classical systems planning problems and their extensions and as such many techniques namely, linear programming, nonlinear programming, mixed integer programming, Dynamic programming, simulation etc. are being widely used nowadays. In the present study a model is developed for maximizing the returns with the associated utilities assigned to each crop by fuzzifying the cost coefficients of each crop. Then an optimal cropping pattern which gives maximum returns from the command area under specified constraints, namely irrigation intensity, land and socio-economy is selected.
Location: T E 15 New Biology Building.
Literature cited 1: S. Vedula, P.P. Majumdar and G.Chandra Sekhar, ?Conjunctive use modeling for multicrop irrigation. Agricultural water management.2004. J.M.Evers R.L.Eliiott and E.W. Stvens?Integrated Decision Making for Reservoir Irrigation, and Crop Management.?Agricultural systems, 58 (4), 1984, pp. 529-554.
Literature cited 2: Yoo?Planningof distribution and application systems by mixed integer linear programming ?Agricultural Water Management, 10, 1985, pp. 265-282. Upchurch D.R., Mahan J.R., Wanjura D.F. and Burke J.J., ?Concepts in deficit irrigation: defining a basic for effective management.?World Water Congress, EWI, 2005, pp. 173-182.

ID: 60708
Title: Flood routing in natural channels: A genetic programming approach
Author: Satishkumar S. Kashid
Editor: Dr.D.G.Regulwar, Dr.K.A.Patil, Dr.U.J.Kahalekar, Dr.P.A.Sadgir.
Year: 2008
Publisher: Excel India Publishers
Source: Centre for Ecological Sciences
Reference: Sustainable Water Resources Development and Management, 244-253, June (2008)
Subject: Sustainable Water Resources Development and Management
Keywords: None
Abstract: The Muskingum method of natural stream flow routing, first developed by McCarthy [1] for flood control studies in the Muskingum River basin in Ohio, is a widely used hydrologic method, for routing flood waves in rivers and channels. The application of the Muskingum model to flood routing in natural channels has some limitations because of its inherent assumption of a linear relationship between channel storage and weighted flow. Many nonlinear forms of the Muskingum model are also proposed by recent researchers, for better prediction of better outflow hydrograph of a river reach. However, recently, a soft computing based tool, Genetic Programming (GP), which is an offshoot of Genetic Algortithms, has shown to have the ability to recognize input-output relationships. It is a relatively new approach for solving flood routing problems which is found to give excellent results with minimum errors. Hence, an evolutionary algorithm-based modeling approach ' Genetic Programming ' is proposed for flood routing in natural in natural channels, which is found to route complex flood hydrographs also with highest accuracy as compared to all traditional methods. The proposed method is applied to standard example of single peak hydrograph from a data set from Wilson [2], as well as for routing of a multi-peaked hydrograph through a natural river channel reach, along the Sabinal River, Texas (USA). It is observed that the GP model performs extremely well with a root mean square error (RMSE) 0.3396 m3 /S for single peak hydrograph and 0.359 m3/S for multi-peak flood hydrograph. These RMSE valued are almost twenty five percent of second best method in routing single peak and multi-peak hydrographs.
Location: T E 15 New Biology Building.
Literature cited 1: McCarthy G.T. ?The unit hydrograph and flood routing.? Unpublished paper presented at the Conference of the North Atlantic Division, Corps of Engineers, U.S. Army, New London, Connecticut, 24 June 1938. Printed by U.S. Engr. Office, Providence Rho de Island, 1938. Wilson E.M. ?Engineering hydrology,? McMillan, Hong Kong, 1990.
Literature cited 2: Gill M.A. ?Flood routing by Muskingum method.? Technical Notes (B), Journal of Hydrology, 36 (1978) 353-363, Elsevier Scientific Publishing Company, Amsterdam, 1978. Chow V.T., Maidment D. and Mays L.W. ?Applied Hydrology.?McGraw-Hill, New York, 1988.

ID: 60707
Title: Assessment of flood vulnerability considering critical infrastructural facilities for Mumbai city.
Author: Chaitanya Kurle, Atit K Tilwankar and Dr. Shyam R. Asolekar
Editor: Dr.D.G.Regulwar, Dr.K.A.Patil, Dr.U.J.Kahalekar, Dr.P.A.Sadgir.
Year: 2008
Publisher: Excel India Publishers
Source: Centre for Ecological Sciences
Reference: Sustainable Water Resources Development and Management, 237-243, June (2008)
Subject: Sustainable Water Resources Development and Management
Keywords: Disasters, Critical Infrastructure, Vulnerability, GIS.
Abstract: Flood is the most devastating natural phenomenon that affects the society, especially poor people who are vulnerable to disaster due to limitation of their resources. Most of the natural disasters in Mumbai are related to flood and causing maximum damage to lives and properties in comparison to other disasters. India is one of the worst flood-affected countries, being second in the world after Bangladesh and accounts for one fifth of global death count due to floods. About 40 million hectares or nearly 1/8th of India ' s geographical area is flood-prone. Critical facilities being the backbone of any economy or society, any damage to these infrastructures may cripple the economy of the country. So, this study was carried out to create flood vulnerability map of Mumbai City using GIS techniques.
Location: T E 15 New Biology Building.
Literature cited 1: Lisa, K.F., Russel, W., Jackson, and David, N.S.Community Vulnerability Assessment Tool Methodology, Natural Hazards Review, 2002. Guidance on the Assessment of tangible flood damages, Queens land Government, 2002.
Literature cited 2: See:http://www.nrw.qld.gov.au/compliance/wic/pdf/guidelines/flood_risk_management/tangible_flood_damages.pdf Literature Cited 2: http://www.karmayog.com/cleanliness/mcgmwardnos.htm

ID: 60706
Title: Performance evaluation of biological unit of sewage treatment plant.
Author: Neeraj D. Sharma and Jayesh A. Shah.
Editor: Dr.D.G.Regulwar, Dr.K.A.Patil, Dr.U.J.Kahalekar, Dr.P.A.Sadgir.
Year: 2008
Publisher: Excel India Publishers
Source: Centre for Ecological Sciences
Reference: Sustainable Water Resources Development and Management, 231-236, June (2008)
Subject: Sustainable Water Resources Development and Management
Keywords: Sewage Treatment plant, performance Evaluation, Activated Sludge Process.
Abstract: The performance of sewage treatment plant is natural expectation from sustainable environment which is found frequently fluctuated in its own. There may be numerous reasons for such fluctuation and they may be rectified with necessary measures by inspecting various operations of sewage treatment plant ranging from macro level to micro level. But an essential element is to monitor the performance of sewage treatment plant which is nothing but the performance evaluation of sewage treatment plant. There are various methods available for the same but the present era needs fast computing techniques for the determination of such performance and computers are the best solution in such regard. This paper is an attempt in the direction of preparation of methodology which merely gives a tentative approach of performance evaluation of activated sludge process for small to medium scale sewage treatment plant.
Location: T E 15 New Biology Building.
Literature cited 1: Andrew, K.J. Application Development with GUI, Prentice Hall India Publishing, New Delhi, 2000. Arceivala, S.J. Wastewater Treatment for Pollution Control. Tata McGraw hill publishing company Ltd., New Delhi, 2000.
Literature cited 2: Benefield and Randall. Process Design for Wastewater Treatment, Prentice-Hall Publishers, 1980. Sharma, N.D. Computer Aided Analysis and Design of Activated Sludge Process, Post Graduate Thesis, Environmental Engineering, Civil Engineering Department, S.V. National Institute of Technology Surat, (INDIA), 2004.