Department of Civil Engineering
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Item Application of Fuzzy Multi-criteria Approach to Assess the Water Quality of River Ganges(Springer, 2017-11) Singh, Ajit Pratap; Srinivas, RallapalliThe purpose of this study is to develop a fuzzy multi-criteria decision-making framework to evaluate the water quality status of a river basin. The rampant and indiscriminate growth in the urban, agricultural, and industrial sector has directly or indirectly disrupted the water quality of the major rivers by discharging mammoth quantities of wastewaters. Regular and accurate evaluation of water quality of a river has become an important task of water authorities. However, the conventional way of evaluating water quality index has been unsuccessful in incorporating uncertainties and subjectivities associated with water quality analysis. Such limitations can be dealt effectively by using fuzzy logic concepts. The present study proposes an Interactive Fuzzy Water Quality Index (IFWQI) to evaluate the water quality status of river Ganges at Kanpur city, India. Multi-Criteria Decision-Making (MCDM) tool namely Fuzzy Inference System (FIS) of MATLAB has been used to obtain a qualitative and quantitative measure of water quality index at six different sites of Kanpur throughout the year by taking into consideration the six important water quality parameters. The results indicate a significant improvement in the accuracy of the index values and thus providing emphatic information to the planners to decide the remedial measures for sustainable management of river Ganges.Item Development of a comprehensive fuzzy based approach for evaluating sustainability and self-purifying capacity of river Ganges(Taylor & Francis, 2017-11) Singh, Ajit Pratap; Srinivas, RallapalliWith accelerated and uncontrolled developments, large amount of untreated wastes is discharged into river water courses through various open drains. Though rivers possess self-purifying capacity, water withdrawals for different beneficial uses have impacted it significantly by reducing its flow. Presently, sustainability has also become an important affair of river basin planning and management. Therefore, assessment of behavior of river under sustainability criteria is necessary. However, the uncertainty and complexity associated with the sustainability criteria, randomness of hydrologic variables, decision-makers, and missing data have become a concern for water managers. Such problems can be modeled under fuzzy logic framework. The present work develops a comprehensive artificial intelligence approach, namely ‘MATLAB Fuzzy Inference system’ to determine the self-purifying capacity of the River Ganges. Thirty-three wastewater drains are identified, which discharge untreated wastes along Kanpur–Varanasi stretch of Ganges. Critical water quality parameters have been analyzed and impact of discharge of river at 12 sampling stations is studied. The model developed to measure the sustainability is flexible to incorporate spatial/temporal changes. Final results give emphatic information to water authorities to maintain adequate flow in the river needed to dilute the waste and also in determining the treatment technology and capacity for open drains.Item A Scenario Based Impact Assessment of Trace Metals on Ecosystem of River Ganges Using Multivariate Analysis Coupled with Fuzzy Decision-Making Approach(Springer, 2017) Singh, Ajit Pratap; Srinivas, RallapalliAbstract The growing consciousness about the health risks associated with environmental pollutants has brought a major shift in global concern towards prevention of hazardous/trace metals discharge in water bodies. Majority of these trace metals gets accumulated in the body of aquatic lives, which are considered as potential indicators of hazardous content. This results in an ecological imbalance in the form of poisoning, diseases and even death of fish and other aquatic lives, and ultimately affect humans through food chain. Trace metals such as Cd, Cr, Cu, Mn, Ni, Pb and Zn originated from various industrial operations containing metallic solutions and agricultural practices, have been contributing significantly to cause aquatic pollution. The present study develops a novel approach of expressing sustainability of river’s ecosystem based on health of the fish by coupling fuzzy sensitivity analysis into multivariate analysis. A systematic methodology has been developed by generating monoplot, two dimensional biplot and rotated component matrix (using ‘Analyze it’ and ‘SPSS’ software), which can simultaneously identify critical trace metals and their industrial sources, critical sampling stations, and adversely affected fish species along with their interrelationships. A case study of assessing the impact of trace metals on the aquatic life of river Ganges, India has also been presented to demonstrate effectiveness of the model. The clusters pertaining to various water quality parameters have been identified using Principal Component Analysis (PCA) to determine actual sources of pollutants and their impact on aquatic life. The fuzzy sensitivity analysis reveals the cause-effect relationship of these critical parameters. The study suggests pollution control agencies to enforce appropriate regulations on the wastewater dischargers responsible for polluting river streams with a particular kind of trace metal(s).Item Evaluation and Quantification of Pollution Caused by Open Drains in Ganges River Basin Using Multivariate Cluster Analysis(IOS, 2019-09) Srinivas, Rallapalli; Singh, Ajit PratapThe colossal expansion and pace of global development have completely deteriorated the water quality of major river basins of the world such as Amazon, Ganges, Nile etc. Rivers have become receivers of wastewater discharged from industrial, agricultural and domestic sectors. Ganges river basin of India is considered as one of the heavily polluted river basin with 144 open drains entering into the river body without proper treatment. Therefore, monitoring and analysing the water quality of these drains and their sources is essential not only to suggest proper treatment procedures but also to ensure sustainability of the river ecosystem. The present study conducts an exhaustive quality analysis of 85 drains carrying both industrial and domestic sewage, either directly into river Ganges or indirectly through tributaries (Kali-East, Ram Ganga and Pandu) in ‘Haridwar to Kanpur’ stretch. Multivariate technique namely Principal Component Analysis (PCA) and Cluster Analysis (CA) have been employed using ‘Analyse it’ software to evaluate the intensity and sources of pollution. The methodology generates monoplots and two dimensional biplots to identify the relationships among pollutants and their sources. Finally, quality assessment of drains has been performed by calculating the water quality index of each drain, and sensitivity analysis is carried out to evaluate the effect of critical water quality parameters. Results direct the policy makers to identify the industries responsible for polluting the drains above critical levels and further measures are suggested to improve the deteriorating quality of drains.