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

In this study, the characterisation of the solid waste and the effect of the leachate from the major dumping site in Perungudi, Chennai city, on groundwater is investigated. Various physical and chemical parameters were estimated: this includes pH, total hardness, electrical conductivity, and total dissolved solids, major cations such as Ca2+, Mg2+, NA+ and K+, major anions such as NO3- CI- and SO42- and heavy metals such as Pb, Cu, Mn, Cd, Cr and Zn. Perungudi dumping site receives 1650 tonnes of Municipal Solid Waste (MSW) daily from the Chennai Corporation. The leachate is a result of anaerobic decomposition of MSW. The results of the analysis of the groundwater samples showed that dumping site leachates constitute a serious threat to the local aquifers. Copyright © 2009, Inderscience Publishers.

Department Of Civil Engineering

International Journal of Environment and Waste Management

Solid waste characterisation and the assessment of the effect of dumping site leachate on groundwater quality: A case study

Determination of status of water quality of a river or any other water sources is highly indeterminate. It is necessary to have a competent model to predict the status of water quality and to advice for type of water treatment for meeting different demands. One such model (UNIQ2007) is developed as an application software in water quality engineering. The unit operates in a fuzzy logic mode including a fuzzification engine receiving a plurality of input variables on its input and being adapted to compute membership function parameters. A processor engine connected downstream of the fuzzification unit will produce fuzzy set, based on fuzzy variable viz. DO, BOD, COD, AN, SS and pH. It has a defuzzification unit operative to translate the inference results into a discrete crisp value of WQI. The UNIQ2007 contains a first memory device connected to the fuzzification unit and containing the set of membership functions, a secondary memory device connected to the defuzzification unit and containing the set of crisp value which appear in the THEN part of the fuzzy rules and an additional memory device connected to the defuzzifiation unit. More advantageously, UINQ2007 is constructed with control elements having dynamic fuzzy logic properties wherein target non-linearity can be input to result in a perfect evaluation of water quality. The development of the fuzzy model with one river system is explained in this paper. Further the model has been evaluated with the data from few rivers in Malaysia, India and Thailand. This water quality assessor probe can provide better quality index or identify the status of river with 90% perfection. Presently, WQI in most of the countries is referring to physic-chemical parameters only due to great efforts needed to quantify the biological parameters. This study ensures a better method to include pathogens into WQI due to superior capabilities of fuzzy logic in dealing with non-linear, complex and uncertain systems.

Air, Soil and Water Research

Fuzzy logic water quality index and importance of water quality parameters

Flood routing through rivers and channels is an essential activity in hydrological analysis and this is particularly important because of the increasing emphasis that has been placed on dam-safety worldwide and due to the increasing urbanization near river channels. The routing of flood through river channels may be accomplished using two basic approaches namely hydrologic routing approach and hydraulic routing approach. There are different methods currently in usage and the Muskingum method is the most popular method and generally used by hydrologists and engineers. However, the reliability of this method is heavily depends upon the accuracy of the parameters namely K and x or C0, C1 and C2 of the model. These parameters are usually estimated by trial and error procedure. Muskingum model together with the Model proposed by Loucks (1989) have been considered for the present study and the parameters of these models were estimated using genetic algorithms, new search procedures for function optimization that apply the mechanics of natural genetics and natural selection to explore a given search space. This paper presents the results of the study of application of genetic algorithm for optimal parameter estimation of both linear and non-linear flood routing models to a case study. The sensitivity analysis of these estimated parameters was also carried out. The results had clearly depicted that the genetic algorithm is an efficient and robust means for estimation of flood routing model parameters. © 2009 ASCE.

Proceedings of World Environmental and Water Resources Congress 2009 - World Environmental and Water Resources Congress 2009: Great Rivers

Application of genetic algorithms for estimation of flood routing model parameters

The purpose of this study was to investigate the possibility of the utilization of coal fly ash as a low cost adsorbent material for the adsorption of heavy metal ions (Zn, Pb, Cd, Mn and Cu) present in the municipal solid waste leachate. Batch experiments were conducted to determine the effect of contact time and fly ash dosage on adsorption of heavy metals. Experimental data were evaluated to find out kinetic characteristics of the adsorption process. The isothermal data could be well described by the Freundlich adsorption model. Kinetic parameters of adsorption such as the pseudo first-order constant, pseudo second-order constant and the intraparticle diffusion rate constant were determined. The fly ash concentration required to achieve maximum heavy metal removal was found to be 2 g/L with the removal efficiencies of 39%, 28%, 74%, 42% and 71% for Cu, Mn, Pb, Zn and Cd respectively. The results of the study demonstrated that the fly ash could be used as an effective low cost adsorbent for the removal of heavy metal ions from municipal solid waste leachate. © 2009 Elsevier B.V. All rights reserved.

Journal of Hazardous Materials

Removal of heavy metal ions from municipal solid waste leachate using coal fly ash as an adsorbent

Water distribution network that includes supply reservoirs, overhead tanks, consumer demand nodes, interconnecting pipes, lifting pumps, and control valves is the main mode of water supply for majority of the communities especially in urban areas. Supply of required quantity of water and at right time is the primary objective of water distribution network analysis. The analysis of water distribution networks can be broadly classified into design and operation problems and both problems have been the focus of many researchers over the past three decades. In the water distribution network design problems, the target is attaining the cost effective configuration that satisfies the minimum hydraulic head requirement at the demand nodes. In this paper, a new algorithm for design of water distribution network namely "heuristics-based algorithm" which completely utilizes the implicit information associated with the water distribution network to be designed has been proposed and validated with two water distribution networks. It is found that the proposed algorithm performs well for the least-cost design of water distribution networks. © 2009 ASCE.

Journal of Computing in Civil Engineering

Water distribution network design using heuristics-based algorithm

Water-sharing in a river basin by different users as well as between different stakeholders along the river basin has been a serious problem and becomes more complex when there is an acute shortage of supply in the river basin. Many negotiations and interactions take place between the farmers as well as between the watersupplier and the farmers before the actual water allocation takes place. This paper presents a novel approach of agent based modeling for solving the water allocation problem. Agent based modeling using a multi-agent approach has been used to represent the various interactions between stakeholders during the process of water allocation. The spatial multi-agent programming model has been used for assessing the performance of the water allocation strategies. It is found that the developed model could provide the various possible scenarios and their consequences to the decision makers. The developed model is very generic and consists of a group of farmers with different farm sizes and crops, and a water supplier who does the allocation. The water allocation rules are built into the functioning of the models and are used to evaluate the performance of the developed rules. The performance indicators adopted in this model include individual farmers view point where one could observe the water needs and water allocated per unit area, global viewpoint with the overall yield, and the ethical viewpoint with disparities in water allocation and yields. It is found that the developed model has been proved to be successful to evolve a compromise and effective solution for the water allocation problem, when the model was applied to a case-study in Tamilnadu, India. © 2009 ASCE.

Agent based models for simulation of watersharing in a river basin

Water quality management though a very important part of overall water resources management programs is also unfortunately given the last priority among all the other objectives like water supply for irrigation, drinking purpose, hydropower. flood mitigation etc. hi the present paper a multiobjective waste load allocation (MOWLA) model has been developed. Though there are many MOWLA models with cost minimization and DO maximization, there are very few models which have adequately addressed the issues of equity in waste load allocation models. The present paper includes equity as one of the objective and shows that by introducing equity in the objective function the solution obtained is more fair when compared to the overall cost minimization solution. However the decision maker has different satisfaction levels to different solutions. To address this uncertainty or ambiguity in a decision maker's (DM) satisfaction level, fuzzy membership functions are introduced for each objective function, thus by introducing fuzziness in the objective functions, a modeler can give a wide range solutions from which the DM can select the most satisfying solution for himself. Copyright © 2009 by IICAI.

Proceedings of the 4th Indian International Conference on Artificial Intelligence, IICAI 2009

Development and application of multiobjective fuzzy waste load allocation model

The quantity of water available for irrigation is getting scarce in many countries and it assumes great importance for assured crop production, especially in view of the erratic behavior of the monsoon. Thus, there is a pressing need to improve the water efficiency of irrigation systems. One-way of improving the efficiency of the irrigation system is reusing the return flow from the irrigation system. This task requires quantification of return flow, which still remains as a grey area in irrigation water management. The estimation of return flow from the irrigation system is usually obtained using thumb rules depending upon the site-specific conditions like command area conditions and soil properties. In this paper, a hierarchical modeling technique, namely, regression tree is developed for return flow estimation. Regression tree is built through binary recursive partitioning. The effective rainfall, inflow, consumptive water demand, and percolation loss are taken as predictor variables and return flow is treated as the target variable. The applicability of the hierarchical model is demonstrated through a case study of Periyar-Vaigai Irrigation System in Tamil Nadu, India. The model performance shows a good match between the simulated and the field measured return flow values. Results of statistical analysis indicated that the correlation coefficients are high for both single as well as double crop seasons. © 2008 Elsevier B.V. All rights reserved.

GENERAL

Agricultural Water Management

Prediction of irrigation return flows through a hierarchical modeling approach

The numerical simulation of multicomponent reactive transport has become a dynamic field of subsurface hydrology. Efficient simulation models are necessary which are capable of representing a multitude of parameters influencing geochemical reactions. The mathematical structure of reactive transport problems in porous media is determined by the decision in the chemical model part whether reactions are kinetically controlled or whether a local equilibrium assumption is made between various species involved in the geochemical reactions. The assumptions made in deterministic models are not hold true for reactions involving chemical species of low concentration. Here the emergent phenomenon evolving out of the random fluctuations of the species is difficult to be captured. The stochastic behaviour of the physicochemical processes can be modelled at mesoscopic level by application of stochastic algorithms. The proposed model was verified by comparing the results of Gillespie's algorithms with a deterministic solution for PCE and BTEX degradation reactions. © 2007 Springer-Verlag.

Computing and Visualization in Science

Multicomponent reaction modelling using a stochastic algorithm

ISH Journal of Hydraulic Engineering

Genetic algorithm applications in water resources

This paper reports the results of the study on the performance of low-cost adsorbent such as raw rice husk (RRH) and phosphate treated rice husk (PRH) in removing the heavy metals such as lead, copper, zinc and manganese. The adsorbent materials adopted were found to be an efficient media for the removal of heavy metals in continuous mode using fixed bed column. The column studies were conducted with 10 mg/l of individual and combined metal solution with a flow rate of 20 ml/min with different bed depths such as 10, 20 and 30 cm. The breakthrough time was also found to increase from 1.3 to 3.5 h for Pb(II), 4.0 to 9.0 h for Cu(II), 12.5 to 25.4 h for Zn(II) and 3.0 to 11.3 h for Mn(II) with increase in bed height from 10 to 30 cm for PRH. Different column design parameters like depth of exchange zone, adsorption rate, adsorption capacity, etc. were calculated. It is found that the adsorption capacity and adsorption rate constant were increased and the minimum column bed depth required was reduced when the rice husk is treated with phosphate, when compared with that of RRH. © 2007 Elsevier B.V. All rights reserved.

Fixed bed column study for heavy metal removal using phosphate treated rice husk

In this paper, the results of a study on removal of copper from synthetic aqueous solutions as well as from industrial wastewater by adsorption onto Casuarina Equisetifolia bark have been reported. Experiments were conducted to understand the effects of particle size, adsorbent dosage, pH, initial concentration, and contact time on the adsorption of Cu(II) on the bark. Quantitative removal of Cu(II) from a solution containing 10 mg/L Cu(II) by 2 g of 0.6 mm particle size of Casuarina Equisetifolia bark per liter was observed for 6 h with a pH value of around 5 and the percentage removal was higher at lower concentration. It has been established that the adsorption isotherm follows both Frieundlich and Langmuir isotherms. The adsorption capacity of Casuarina Equisetifolia bark was estimated as 16.58 mg/g for a concentration of 10 mg/L at pH being equal to 5 and the removal efficiency Cu(II) ion was found to be about 96%. The results also revealed that the retention capacity of the bark is reduced during each cycle, and the Cu(II) ion removal efficiency decreases when other metal ions were present in the solution. The suitability of Casuarina Equisetifolia bark for treating electroplating wastewater containing copper was tested through column experiments and it was found that the removal efficiency of Cu(II) from this waste water is about 93%. The regeneration study established that the bark can be used continuously without much reduction in removal efficiency and without any significant leaching of adsorbed Cu(II) ions. © Mary Ann Liebert, Inc. 2008.

Environmental Engineering Science

Removal of Cu (II) by adsorption using Casuarina Equisetifolia bark

The number of drought events derived from the historic streamflow or rainfall series will be limited and produce results that are not very reliable. This study proposes a drought simulation methodology that uses a long sequence of synthetically generated monthly streamflow/rainfall series, from which it is possible to drive a large sample of drought events and the prediction of drought characteristics will be reliable. The modified Herbst method has been used to identify droughts in the generated streamflow and rainfall series. The drought simulation procedure is illustrated with a case study of the Bhadra reservoir catchment in Karnataka State, India. Monthly droughts were derived from both historic and generated monthly streamflow and rainfall series. The important drought characteristics were determined and the suitable probability distribution for each parameter was arrived at after studying seven different probability models. The use of the probability curves thus derived has been illustrated with examples (referred to in Part 1 as 'point droughts'). Similarly, the development and application of stochastic models for the prediction of regional drought parameters have been illustrated with examples in the accompanying paper (Part 2: regional droughts). Copyright © 2007 John Wiley & Sons, Ltd.

Hydrological Processes

Stochastic simulation of droughts. Part 1: Point droughts

The anaerobic digestion of kitchen waste was studied in both batch and continuous modes. The effect of increasing loading rates on pollutant removal and biogas production was investigated for single-phase digestion and twophase digestion systems. The anaerobic biodegradability of the kitchen waste obtained from the batch study was 83.5%. Single-stage digestion of kitchen waste was subjected to varying organic loading rates (OLR) ranging from 1.5 kg volatile solids (VS) m-3 d-1 to 5.5 kg VS m-3d _1, with a common, hydraulic retention time (HRT) of 15 d. The optimum performance of the system was observed at an OLR of 4.5 kg VS m -3 d-1 in terms of pollutant removal efficiency and biogas production. The removal rates for chemical oxygen demand (COD) and VS at this optimal OLR were 81% and 79%, respectively. Maximum, production of the methane was 0.288 m3/kg of VS added. Beyond the optimal OLR, the volatile fatty acids concentration increased and reached its maximum value (9.2 g/L) at the higher loading rate tested (5.5 kg VS m3 d-1). Anaerobic digestion of the kitchen waste was earned out in a two-stage reactor with different loading rates of 4, 6, and 8 kg VS m3 d-1. The retention time given to both hydrolysis and methanogenesis phases was 5 d, for a total HRT of 10 d. Best performances were observed in the third run with the OLR of 8 kg VS m-3 d-1. High removal efficiencies for COD and VS were found as 92% and 94%, respectively. A total of 0.22 m3 of methane was produced by 1 kg of VS added. Responses to the fluctuations in the loading rates were sudden and many times unfavourable in the singlestage system, while the fluctuations were suppressed or overcome at a faster rate in. the two-stage reactor, without creating too many problems. Comparison of the overall performance showed that phase-separated digesters or the two-stage digesters may offer the best choice for high efficiency, concerning pollutant removal. © 2008 NRC Canada.

Journal of Environmental Engineering and Science

Effect of phase separation on anaerobic digestion of kitchen waste

In Part 1 we demonstrated the applicability of stochastic models to predicting the characteristics of point drought events within any planning period by means of a case study (Mohan S, Sahoo PK (2007) Hydrological Processes 21: this issue). In addition, studies on regional droughts are important in the context of regional level planning and evolving management strategies. The small number of drought events from a particular streamflow or rainfall series, when subjected to statistical analysis in order to predict future occurrences, produces results that are not very reliable. To overcome this difficulty, we propose using a long sequence of synthetically generated annual rainfall series at various rain-gauge stations of a region, and multiyear regional droughts were derived from both historic and generated series. The key parameters for a successful regional multiyear drought study are the critical area ratio and the critical level, and the area affected by the drought can be ascertained using these parameters. The important regional drought parameters were determined and their suitable probability distributions were arrived at by studying a total of nine possible probability models; these models can be used in predicting the longest regional drought duration and the greatest regional drought severity with a given return period. The effect of change of critical parameters on the regional drought parameters is also studied and reported. Copyright © 2007 John Wiley & Sons, Ltd.

Stochastic simulation of droughts. Part 2: Regional droughts

In this paper, two models for determining the optimal operation policies have been developed and applied to a tank irrigation system. The tank irrigation system almost occupies one-third of the irrigation in the state of Tamilnadu and there are no well established operational guidelines or the rule curves a vailable for these tanks. An attempt has been made to develop tank opera tional policies in the form of simple regression equations or rule curves using implicit and explicit stochastic methods, respectively. The methodology a dopted in this paper for deriva tion of optimal opera tion policies consists of three phases. In the first phase, accurate determination of the effective rainfall and the irrigation requirements of crops was carried out. Development of Implicit and explicit stochastic reservoir operation optimization models constitutes the second phase. In the third phase, simulation models were developed to compare the performance of optimal opera tion policies derived from these stochastic modelsas wellas with the actual releases. The performance of the derived operational rules was found to be superior for the tank irrigation system studied.

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

Optimal operation of a tank irrigation system

In rainfall-runoff studies, it is often necessary to change the duration of a given unit hydrograph. Nash's Instantaneous Unit Hydrograph (IUH) is an ideal method that eliminates the hydrograph duration. This paper presents the results of the application of search algorithms, namely a genetic algorithm and hill climbing, to develop the IUH that minimizes the error between the observed and generated hydrographs. Also the performance of these methods has been compared with that of the classical method used for estimation of IUH, namely the method of moments. The genetic algorithm is a popular search procedure for function optimization that applies the mechanics of natural genetics and natural selection to explore a given search space. Hill climbing is an optimization technique that belongs to the family of local search and algorithms can be used to solve problems that have many solutions, with some solutions better than others. The results obtained from both the genetic algorithm and hill climbing algorithm for estimation of Nash's WH parameters were compared with the results obtained by the method of moments for storms from two river basins that are located in different climatic regions. It was found that both the genetic algorithm and hill climbing provided improved and consistent results. Copyright © 2008 John Wiley & Sons, Ltd.

Estimation of Nash's IUH parameters using stochastic search algorithms

Anaerobic digestion of wastewater from jam industries was studied in a continuous reactor with different organic loading rates (OLR) and the optimum organic loading rate was 6.5 kg COD/m3/day when it was operated with three days HRT. The biodegradability of wastewater in batch experiments was about 90%. The removal efficiency of total COD and soluble COD were found to 82% and 85%, respectively. The specific methane production was 0.28 m3/kg of COD removed/day. © 2006 Elsevier Ltd. All rights reserved.

Bioresource Technology

Study on biomethonization of waste water from jam industries

A heuristic simulation based optimization model has been developed to optimize the operation of a multiple reservoir using dynamic programming and soft computing techniques. Soft computing based tools including Adaptive Neuro Fuzzy Inference systems (ANFIS) and Genetic Algorithms (GA) are used here to tackle the complexity of deriving the operational policies. This heuristic approach involves three stages in the model development. In the first stage GA is used to develop initial trajectories for DP model and then DP model results are used to adopt training data set for ANFIS model. Finally, a general operating policy is developed for multi-reservoir system operations. The demonstration is carried out through application of Parambikulam Aliyar Project systems in India. The performance of the proposed GA-DP-ANFIS is compared with simulation based multi regression model. Rule curves are developed for different scenarios like current operating policy, rezoning pattern, improved irrigation management and increase of available water potentials. Copyright © 2007 IICAI.

Proceedings of the 3rd Indian International Conference on Artificial Intelligence, IICAI 2007

Development of water resources management policies for multi-reservoir systems using simulation-based soft computing models approach

Opencast mines operating in an area with dominant groundwater features may face hydrology-related problems such as heaving and bursting of the mine floor due to excessive uplift pressure. A proper groundwater control system has to be implemented to solve these problems. But the groundwater control system, which includes dewatering and depressurization wells may also create impacts on local groundwater flows. Therefore, an optimization-based development of the groundwater control system is required to ensure that local and regional hydrogeological impacts are within acceptable limits. This note presents a case study where an optimization program based on the simulated annealing technique was developed and applied to a three-dimensional seven-layer groundwater model. The calibrated groundwater flow model, which is based on MODFLOW, was used as the simulation component in the linked simulation-optimization model. The combined model was then used to identify the optimum depressurization strategy. The results show that this combined simulation and optimization methodology is a viable approach for solving large-scale groundwater management problems. © 2007 ASCE.