IIT Madras is a public technical and research university located in Chennai, Tamil Nadu. Founded in 1959, it is recognised as an Institute of National Importance.

IIT Madras has been ranked as the top engineering institute in India for four years in a row by the National Institutional Ranking Framework of the MHRD

It currently offers undergraduate, postgraduate and research degrees across 16 disciplines in Engineering, Sciences, Humanities and Management. About 596 faculty belonging to science and engineering departments and centres of the Institute are engaged in teaching, research and industrial consultancy.

IIT Madras

This paper describes the recently developed 'Guideline s for the design and control of intermittent water distribution systems'. These guidelines outline a new approach to the design of urban water distribution systems for developing countries in order to maintain adequate and equitable supplies under the common conditions of water resource shortage. The guidelines are novel in that they recognise the reality of intermittent supply and hence provide new methods of analysis and design, appropriate for such systems. Design objectives specifically tailored to intermittent systems are developed and drive the design process. These objectives are expressed in terms of equity in supply, adequate pressure at water connections and duration or time of supply that are convenient to the consumers. The modifications required to model such systems have been incorporated into a new network analysis simulation tool coupled with an optimal design tool. © 2007 International Water Resources Association.

Department Of Civil Engineering

Water International

Intermittent water supply under water scarcity situations

Reservoirs are built usually to serve multiple purposes, viz. irrigation, municipal and industrial water supply, hydro-power and flood control. Because of high variability of annual rainfall and conflicting demands on scarce water resources, the study and operation of reservoir systems has assumed great significance to meet the short and long-term requirements. The reservoir managers do not find previous techniques of complex optimization models are difficult to adopt practically. New methods have to be developed, which are simple to understand and can be effectively adopted for the existing systems. Artificial intelligent tools like Genetic programming, Neural Networks and fuzzy logic methods are increasingly becoming popular in Water resources applications. The fuzzy-rule-based systems are very much suitable for inferring developed operating policies. In the present work a rule-based Fuzzy model is attempted for long-term operation a multi-reservoir system. The model was developed on monthly basis for operation and the model was demonstrated with a case of two serial reservoirs on River Godavari sub-system located in South India. The uniqueness of the present paper is that the model was developed based on the historical operation so that the model may be acceptable to reservoir managers, since the departmental expertise was the basis for the model development. The performance of the model was tested with both calibrated and validation periods. The performance of model during two crop seasons of year was reported. © 2006 by World Scientific Publishing Co. Pte. Ltd. All rights reserved.

Advances in Geosciences: Volume 1: Solid Earth (SE)

Fuzzy logic model for multi-reservoir operation

An artificial neural network (ANN) model has been developed to generate the multisite streamflows and the results are compared with the classical multsite streamflow generation model developed by Hydrologic Engineering Centre named HEC-4. Both the models have been applied to the case study of Upper Krishna River Basin to evaluate their performances. Important statistical parameters, namely, mean, standard deviation, correlation coefficient of the historical and generated streamflows are compared for the evaluation. Hurst ratio has bem used to' evaluate the strength of persistence of the generated streamflows. This study shows that the streamflows predicted with simple ANN model are more satisfactory than the HEC-4 model in case of multisite streamflow generation.

Journal of the Institution of Engineers (India): Civil Engineering Division

Comparative study on multisite streamflow generation model HEC-4 and ANN model

Extraction of chromium (III) using D2EHPA (di 2-ethylhexyl phosphoric acid) in kerosene was carried out. A study was carried out to optimize the conditions, namely pH, carrier D2EHPA, aqueous and organic ratio, and reaction time. The effect of chloride and sulphate concentration on the extraction process was studied. The tri-butyl phosphate (TBP) was used as a phase modifier to facilitate the extraction process. In the stripping process, remarkable amount of chromium was recovered from the loaded organic phase using hydrogen peroxide as a stripping agent. When the stripped organic solution was reused for chromium extraction, it showed appreciable extraction efficiency under optimum conditions. The chromium (VI) present in the electroplating wastewater was reduced to chromium (III) with ascorbic acid, and under optimized conditions the removal of chromium from electroplating wastewater was found to be satisfactory. Copyright © Taylor & Francis, Inc.

GENERAL

Separation Science and Technology

Recovery of chromium from electroplating wastewater using di 2-(ethylhexyl) phosphoric acid

Industrialisation is causing the environment and in particular groundwater to be affected by pollution. It is therefore imperative to adopt remediation techniques to control this contamination. In this study, the hydraulic containment method using extraction wells was adopted as the remediation technique. An optimisation model is developed to minimise costs of pumping used for the containment of groundwater contamination. The output from this is used to train a neural network model that has been developed for optimal evolution of pumping strategies. Neural networks are proving to be useful decision-making tools because they are able to store knowledge and can consider nonlinear relationships, fuzzy relations, etc. The optimisation model developed and the neural network model is applied in a case study. The feed forward neural network is adopted with the input nodes storing the water levels at the wells (five observation wells and one pumping well are considered) and the output node storing the optimal pumping rate for these water levels, which is obtained using the optimisation model. This neural network is trained with six input nodes, one output node and eleven nodes in the hidden layer. This neural network is trained with 45 patterns and tested with four patterns. The trained neural network proved to be very useful in making decisions on the number of pumping wells, and in obtaining the optimal pumping rate for each well. The user, on specifying a set of inputs (the water levels in the wells) to the network, can obtain the optimal pumping rate at all the extraction wells in order to ensure that the contaminant plumes have been contained within the specified area. © 2005 EPP Publications Ltd.

Land Contamination and Reclamation

Application of a neural network model for the containment of groundwater contamination

Different infiltrations models were tested at 50 locations in a basin based on the soil type and land use variations at Neyveli. Infiltration models namely Green Ampt model, Modified Kostiakov model and Horton model were found to be fit to the observed field data to estimate infiltration rates at any given time and their parameters were determined using least square method. The basin is divided into four zones based on location of rain gauge stations. Ground water recharge was estimated using three infiltration models for each zone. Their results were compared with that of the standard SWAT (Soil and Water Assessment Tool) model developed by the USDA agricultural research service (ARS). Horton model was found to be high correlated with SWAT model when compared to the other two infiltration models. It can be concluded that Horton model is the most appropriate infiltration model for estimating recharge in Neyveli region. © 2005 Taylor & Francis Group, LLC.

ISH Journal of Hydraulic Engineering

Recharge estimation using infiltration models

Reservoirs are built usually to serve multiple purposes, viz. irrigation, municipal and industrial water supply, hydro-power and flood control. Due to high variability of annual rainfall and conflicting demands on scarce water resources, the study and operation of reservoir systems has assumed great significance to meet the short term and long-term requirements. The reservoir managers do not find previous techniques of complex optimization models are difficult to adopt practically. New methods have to be developed which are simple to understand and can be effectively adopted for the existing systems. Any reservoir problem is usually site specific in nature and hence any general modeling methodology cannot be directly applied to study the system behavior. Artificial intelligence approaches are now being adopted to effectively simulate the reservoir system based on the experience of human knowledge and expertise. These methods are simple to understand for the reservoir managers and also may be acceptable since the model is being developed with the output and opinion of experts who are really operating the reservoir system. The Fuzzy rule based systems are very much suitable for inferring developed operating policies. In the present work a rule based fuzzy model is attempted for long-term operation a multi reservoir system. The present model was developed on monthly basis for operation and the model was demonstrated with a case of two serial reservoirs on River Godavari sub system located in South India when they are operated individually. The recent artificial intelligence tools like Genetic programming, Artificial Neural networks and Fuzzy logic are increasingly used as soft computing techniques to address modelling issues. The main advantage of these techniques lies in handling noisy data, addressing non - linear and dynamic systems. These tools also useful when it is difficult to explain the physical relationship are not fully understood in order to enhance the performance of the system. The present paper is aimed to present a fuzzy logic methodology for long-term reservoir operation. In this method a monthly fuzzy rule based model was developed based on the historical operation. The performance of the model was tested with calibrated period and validation period.

Artificial Intelligence Applications and Innovations - IFIP TC12 WG12.5 - 2nd IFIP Conference on Artificial Intelligence Applications and Innovations, AIAI 2005

Fuzzy logic model for multi - Purpose multi - Reservoir system

The study aims at developing a GIS based contamination Risk Assessment procedure in water distribution systems. Water distribution network analysis model EPANET 2.0 was integrated with ArcGIS 8.3 for the water quality analysis retrieving data from the GIS database. Water supply system of Zone VIII of Guntur, India was selected for the case study. The results of water quality simulation were displayed in the GIS interface and the areas affected were mapped with the spatial analyst tool of GIS. Data on number of household connections and standpipes affected by a particular event of contamination was also retrieved from the GIS database. The events resulting in high risk were identified from the GIS maps. This information helps in the decision making process of prioritizing the maintenance activities particularly, in case of limited fund availability. Since the resource availability for maintenance activities are limited in developing countries, prioritizing the activities using GIS helps to achieve maximum risk reduction.paper.

People-Centred Approaches to Water and Environmental Sanitation: Proceedings of the 30th WEDC Conference

Development of GIS based contamination risk assessment in water distribution systems

Pollution of ground water has been growing incessantly in several of the country particularly due to the indiscriminate discharge of waste water from the industries, which either do not have or have inadequate treatment facilities. These industries discharge their waste water into the immediate neighbourhood open channels which ultimately confluences with ponds; streams, rivers etc., The chemical constituents of the waste material often seeps down from the entire course and from the stagnated points into the ground water system. Once the ground water system gets polluted, cleaning and redemption is prohibitively costly. Hence a systematic and scientific management of this vital resource is essential to achieve optimum results.

Journal of the Institution of Engineers (India): Environmental Engineering Division

Modelling of pollutant transport in ground water

An optimization model has been formulated to maximize the net benefit from a tank command with conjunctive use of surface water from the tank and ground water from wells and community well in the tank area. The Kannangudi tank in Pudukkottai district, Tamil Nadu, India has been taken as the case study. Six crops were found in the command area and are considered for arriving the optimal cropping pattern. The study result shows that, the wells and community well in a tank command contributes to a sustainable irrigation and apparently maximize the net benefit from that tank command.

Community wells for sustainable irrigation in tank commands: A case study

The paper presents a GIS based spatial decision support system for modelling contaminant intrusion into water distribution system. Three models have been developed to simulate the process and risk of contamination. A seepage model predicts the contaminant zone of pollution sources and the change of concentration during migration through soil. A pipe condition assessment model ranks the condition of water pipe in terms of the potential of contaminant ingress. An ingress model combines the geometry algorithm with contaminant zone to obtain the potential pollution areas of water distribution pipe. The three models were integrated with ArcView GIS for supporting decision making for risk mitigation. Zone VIII of water supply system in Guntur, India was selected for the case study. The contaminant ingress potential and potential pollution area of water pipes were displayed as thematic maps in GIS. The areas resulting in high risk were identified from the GIS maps. The availability of resources for maintenance activities are limited in developing countries. Thus GIS based spatial decision support system helps to achieve maximum risk reduction.

A GIS based spatial decision support system for modelling contaminant intrusion into water distribution systems

Journal of Indian Water Works Association

Reverse osmosis process for wastewater reuse : Performance evaluation models - Part II

The safety and performance of many existing irrigation systems could be improved by doing the preventive maintenance activities. Modeling canal irrigation systems in terms of condition and performance that can be directly correlated with particular canal system maintenance activities. There are two categories of scheduled maintenance activity in irrigation maintenance systems: maintenance may be targeted towards restoring deliveries ("Restorative maintenance"), or towards reducing the risk of failures ("Preventative maintenance"). This paper covers the latter kind of maintenance scheduling by 'Risk Analysis'. The purpose of this risk analysis is to forecast the impact of preventative maintenance on deliveries from the main channel systems. After gaining the experience from the preliminary risk analysis through questionnaire based survey and failure history of past record, a 'Fuzzy Fault Tree (FFT)' method is developed for the rapid risk assessment and it is necessitated for the irrigation system manager/engineer. 'Risk Analysis' of irrigation systems from the point of view of maintenance is studied and applied to the Tirunelveli Channel Systems located in India. The effectiveness is calculated for each preventative maintenance tasks and it is ranked according to the Effectiveness/Cost ratio.

IEEE International Conference on Industrial Informatics (INDIN)

Evaluation of risk in canal irrigation systems due to non-maintenance using Fuzzy Fault Tree approach

Reverse osmosis process for waste water reuse : Performance study - Part-I

Transit route network design for urban bus systems involves the selection of a set of routes and the associated frequencies that achieve the desired objective, subject to the operational constraints. This can be formulated as an optimization problem that minimizes the total system cost, which can be expressed as a function of bus operating cost and passenger total travel time. In the first phase of a two-phase solution process, a large set of candidate route is generated using a candidate route generation algorithm. In the second phase, a solution route set is selected from the candidate route set using genetic algorithms, a search and optimization method based on natural genetics. The simultaneous route and frequency coded model proposed in this investigation considers the frequency of the route as the variable, thus differing from the earlier models in terms of coding scheme adopted. A sample study on a medium-sized network has established that the coding scheme adopted for the route network design enhanced the performance of the model.

Journal of Transportation Engineering

Transit route network design using frequency coded genetic algorithm

A combined optimization-simulation approach was used to develop and evaluate the alternate priority-based policies for operation of surface and groundwater systems and is demonstrated with a case study. An optimization model was used to find optimal cropping pattern with and without the conjunctive use of surface and groundwater, as well as with and without socio-economic constraints. The optimization model, based on linear programming, maximizes the net benefit from irrigation activities subject to various physical, economical, and social constraints. A simulation model was used to evaluate the conjunctive operation of the system using the optimal cropping pattern derived from the optimization model. The developed policies have been verified with long-generated stream flow sequences. Three alternate priority-based policies differing in level of groundwater pumping and area of cultivation of rice crop have been evaluated: (1) irrigation with surface water only (Policy-1); (2) irrigation with conjunctive use of surface and groundwater, without socio-economic constraints (Policy-2); and (3) irrigation with conjunctive use operation and with socio-economic constraints (Policy-3). It was found that the use of available groundwater within three meters below ground level (Policy-2) to be optimal, and these results were used in simulation for further evaluation of policies. It was also found that the policy-3 of conjunctive use operation with a priority of 75 percent of maximum possible rice area (using groundwater available within four meters below ground level) resulted in a better scenario. Thus the conjunctive use Policy-2 and Policy-3 with 75 percent of maximum possible rice crop area can be used as better policies for the system studied. © 2003 Taylor & Francis Group, LLC.

Development of Priority-Based Policies for Conjunctive Use of Surface and Groundwater

Rational methods for setting priorities for maintenance of irrigation systems are developed. The methods, which are aimed for use by irrigation system managers, describe the link between maintenance activities and the consequent improvement in the performance of an irrigation system. Hydraulic analysis methods are developed for assessing potential 'restorative maintenance' tasks, which are usually undertaken to increase the deliveries of water to the outlets. The new methods use inputs that have been limited to those easily available from scheme records, the knowledge of irrigation agency staff and from infrastructure inspections. Two alternative methods are developed, one based on Fuzzy Logic and one on numerical modelling. Risk analysis methods are also developed for assessing 'preventative maintenance', to reduce the probability of supply failures. Benefit-cost ratios are derived that allow direct comparison between maintenance tasks of each type. The methods are tested at two irrigation systems in Tamil Nadu, India.

Irrigation and Drainage Systems

A rational approach to scheduling main-system maintenance

A fuzzy linear programming model (FLP) is formulated to derive optimal crop plans for an irrigation system with the aim of conjunctive utilization of water from surface reservoir and ground water aquifer, and demonstrated with a case study. The results of FLP model were compared with classical linear programming model (LP). The LP model model maximizes the net benefits from irrigation activities subject to various physical, economical, and water availability constraints. The fuzziness involved in the input variables such as inflows and ground water pumpage are considered in the FLP model. The FLP model maximizes the degree of satisfaction or truthness subject to object function, physical and economic constraints involving the fuzziness in the input variables. The increase in the degree of satisfaction or the truthness with increase in number of fuzzy variables was studied and the results are reported. It was found that the fuzziness in the ground water pumpage plays a prominent role in deriving the optimal operational strategies. From the optimal results it was found that the FLP model has resulted an optimal crop plan with a degree of truthness of 0.78 taking into account the fuzziness in different variables.

Fuzzy system modelling for optimal crop planning

Irrigation has been practised in India from ancient time. Even now, India has the largest area under irrigation. Tamilnadu state in India stands one among the few states in successfully harnessing and utilising the available water. Future development and management of available water resources can be achieved through optimisation techniques. Water management at farm level is one of the most important activities to be carried out for optimal use of water. Evapotranspiration is the most important variable next to rainfall in the context of irrigation to crops. In this paper, the results of the comparative study on crop water requirements estimation by two methods namely FAO-Penman method and Duty-delta method are reported. It is found that duty-delta method underestimates the crop water requirements.

Crop Water Requirements in a Command Area - A Comparative Analysis

Neural networks as models for waste treatment systems have been studied. A brief summary about the neural network approach and its application to two case studies have been discussed. The study shows that with both long series and short series of data on waste treatment processes, the neural networks have produced comparable results. Neural network models are robust and provide good predictions for the performance of the waste treatment systems. These neural network models appear to provide a promising alternative for waste treatment systems modelling.