Department of Civil Engineering

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Author: search.filters.author.Singh, Ajit PratapEnd date: 2019

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    Application of Fuzzy Multi-criteria Approach to Assess the Water Quality of River Ganges
    (Springer, 2017-11) Singh, Ajit Pratap; Srinivas, Rallapalli
    The 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.
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    Groundwater Quality Assessment in Some Selected Area of Rajasthan, India Using Fuzzy Multi-criteria Decision Making Tool
    (Elsevier, 2015) Srinivas, Rallapalli; Singh, Ajit Pratap
    Groundwater is one of the primary sources for drinking and irrigation in Bikaner district of Rajasthan, India. However its quality is deteriorating due to population growth, agricultural runoff and urbanization. In this paper, fuzzy inference tool has been used to develop a model for assessing groundwater quality in Dungargarh block of Bikaner district in Rajasthan. Eleven water quality parameters have been considered as important indicators to evaluate water quality status in 15 groundwater wells located in the region. The model predicts status of groundwater quality along with measure of its sustainability. The ranking of the wells corresponding to both drinking and irrigation uses also provides clarity to the decision makers to formulate suitable policies for treatment processes and sustainable planning of groundwater resources in the region.
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    Water quality assessment of a river basin under fuzzy multi-criteria framework
    (Inder Science, 2015-07) Singh, Ajit Pratap; Srinivas, Rallapalli
    In this paper fuzzy analytical hierarchy process (FAHP) has been developed to evaluate status of water quality at eight selected stations along river Yamuna. A decision support mechanism has been introduced to select and prioritise stations with specific reference to five important beneficial uses namely, domestic, irrigation, aquatic life, industrial, and recreational activities. Various water quality parameters have been considered as criteria to evaluate water quality status at a given station with respect to particular usage. Pairwise comparisons of the criteria and the stations have been performed to assess water quality using linguistic variables. The eight stations chosen for the study in Yamuna basin are Hathnikund, Sonepat, Palla, Nizamuddin-Delhi, Mathura, Agra, Etawah and Allahabad. Analysis of results reveal that first three stations score highest rank with respect to all beneficial uses as they are relatively free from industrial and municipal contamination. However as the water enters Delhi, it gets heavily contaminated mainly due to wastewater discharged from several municipal drains and industrial activities. The prioritisations of stations with respect to designated uses presented herein are helpful to the decision makers and the implementing agencies to formulate suitable strategies for effective and sustainable utilisation of water in the river basin
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    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, Rallapalli
    With 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.
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    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, Rallapalli
    Abstract 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).
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    Holistic approach for quantification and identification of pollutant sources of a river basin by analyzing the open drains using an advanced multivariate clustering
    (Springer, 2018-11) Singh, Ajit Pratap; Srinivas, Rallapalli
    Global scarcity of freshwater has been gearing towards an unsustainable river basin management and corresponding services to the humans. It needs a holistic approach, which exclusively focuses on effective river water quality monitoring and quantification and identification of pollutant sources, in order to address the issue of sustainability. These days, rivers are heavily contaminated due to the presence of organic and metallic pollutants released from several anthropogenic sources, such as industrial effluents, domestic sewage, and agricultural runoff. It is astonishing to note that even in many developing countries, most of these contaminants are carried through open drains, which enter river premises without proper treatment. Such practice not only devastates riverine ecosystem but also gives rise to deadly diseases, such as minimata and cancer in humans. Considering these issues, the present study develops a novel approach towards simultaneous identification of major sources of pollution in the rivers,
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    Development of a HEC-HMS-based watershed modeling system for identification, allocation, and optimization of reservoirs in a river basin
    (Springer, 2017-12) Srinivas, Rallapalli; Singh, Ajit Pratap
    One of the primary objectives of river basin planning and management is to assess the behavior of the river towards man-made and natural changes. In recent times, the self-purifying capacity of the river is found to be substantially affected because of extensive use of water for agricultural and industrial purposes. Any variation in the flow regime of a river poses a severe impact on the aquatic ecosystem, which affects its self-purifying capacity. Diverting river water for industrial and agricultural uses through dams and barrages reduces the natural flow rate of the river. The present study develops a novel approach by couplingWatershed Modeling System (WMS ver. 10.1) with linear optimization to provide an alternate means of water supply for such users. To explain the effectiveness of the model, a case study on the Ganges river basin of India has been considered. The ecosystem of the Ganges provides such a magnificent biological fabric, that its self-purifying capacity exceeds that of any other river water across the globe. However, the industries found in the river’s most polluted stretch consume around 1200 million liters of water every day. In addition, 80% of the river water diverts at Narora barrage for agricultural purposes. As a result, the flow of the river in dry seasons is as less as 300 m3/s.
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    An integrated fuzzy-based advanced eutrophication simulation model to develop the best management scenarios for a river basin
    (Springer, 2018-01) Srinivas, Rallapalli; Singh, Ajit Pratap
    Assessment of water quality status of a river with respect to its discharge has become prerequisite to sustainable river basin management. The present paper develops an integrated model for simulating and evaluating strategies for water quality management in a river basin management by controlling point source pollutant loadings and operations of multi-purpose projects. Water Quality Analysis and Simulation Program (WASP version 8.0) has been used for modeling the transport of pollutant loadings and their impact on water quality in the river. The study presents a novel approach of integrating fuzzy set theory with an “advanced eutrophication” model to simulate the transmission and distribution of several interrelated water quality variables and their bio-physiochemical processes in an effective manner in the Ganges river basin, India. After calibration, simulated values are compared with the observed values to validate the model’s robustness. Fuzzy technique of order preference by similarity to ideal solution (F-TOPSIS) has been used to incorporate the uncertainty associated with the water quality simulation results. The model also simulates five different scenarios for pollution reduction, to determine the maximum pollutant loadings during monsoon and dry periods. The final results clearly indicate how modeled reduction in the rate of wastewater discharge has reduced impacts of pollutants in the downstream. Scenarios suggesting a river discharge rate of 1500 m3/s during the lean period, in addition to 25 and 50% reduction in the load rate, are found to be the most effective option to restore quality of river Ganges. Thus, the model serves as an important hydrologic tool to the policy makers by suggesting appropriate remediation action plans.
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    Sustainable management of a river basin by integrating an improved fuzzy based hybridized SWOT model and geo-statistical weighted thematic overlay analysis
    (Elsevier, 2018-08) Srinivas, Rallapalli; Singh, Ajit Pratap
    Sustainable river basin planning and management is a complex and uncertain phenomenon involving social, economic, environmental and several technical criteria. Despite global advancement, the problems associated sustainability have not been sufficiently addressed, due to mismanaged governance, poorly implemented policies, lack of suitable data and over-exploitation of river resources. Therefore, major rivers basins across the globe need an integrative and comprehensive strategic approach considering the diverse stakeholder’s perspective and conflicting criteria pertaining to sustainable management. The present study develops a decision support framework to assess the sustainability by coupling an improved fuzzy based hybridized strength-weakness-opportunities and threats model (FH-SWOT) with a geostatistical approach. To demonstrate the effectiveness of the model Ganges river basin, India has been taken as a case study. The novelty of the study is to devise six different hybrid mechanisms under FH-SWOT framework to reach best possible strategic alternatives along with nominal, optimistic and pessimistic perspectives of the stakeholders. To enhance the model’s productivity, it is coupled with weighted overlay geo-statistical approach to identify/prioritize the most vulnerable/critical locations, which needs suitable implementation of strategic alternatives derived using FH-SWOT model. The FH-SWOT model developed herein simultaneously delineates strategic alternatives and corresponding priority zones, while addressing the uncertainties related to stakeholder’s conflicts and imprecise data to reach optimal, pessimistic and nominal viewpoints, which leads to development of an innovative and comprehensive decision-support framework for assessing sustainability. The key policies derived from the study involve enforcing regulations on disposal of heavy metals, developing hydropower, adaptation of organic farming, education and participation of stakeholders, regulations on dams and barrages with a score of 0.2453, 0.2205, 0.2088, 0.1898, and 0.1288 respectively. Also, Kanpur- Varanasi stretch has been delineated as very high priority zone followed by regions located along the banks of Ganges. Sensitivity analysis proves that the model is robust and can be used by the environment managers towards sustainable planning and management of any river basin, lakes, wetlands or any major water body of the world.
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    Evaluation and Quantification of Pollution Caused by Open Drains in Ganges River Basin Using Multivariate Cluster Analysis
    (IOS, 2019-09) Srinivas, Rallapalli; Singh, Ajit Pratap
    The 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.