Integrating Decision Science and Fuzzy Logic to Evaluate and Improve Water Quality: A Pathway to Operational Excellence in Environmental Management

Ajoy Kanti Das (), Nandini Gupta, Suman Das, Rakhal Das, Carlos Granados () and Suman Patra
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Ajoy Kanti Das: Tripura University, Department of Mathematics
Nandini Gupta: Bir Bikram Memorial College, Department of Environmental Science
Suman Das: NIT Agartala, Department of Education (ITEP)
Rakhal Das: The ICFAI University Tripura, Department of Mathematics
Carlos Granados: Universidad de Antioquia, Estudiante de Doctorado en Matemáticas, Magister en Ciencias Matemáticas
Suman Patra: Tripura University, Department of Mathematics

Chapter 4 in Decision Sciences for Quality and Productivity Improvement, 2026, pp 77-109 from Springer

Abstract: Abstract This chapter presents a comprehensive study using a Fuzzy Soft Expert System (FSES) to evaluate and improve water quality in the Manu River, Tripura, India, focusing on the anthropogenic influences over the period 2020–2021. By integrating decision sciences with fuzzy logic, the study captures complex interactions between various water quality parameters and human activities. Multi-criteria decision-making (MCDM) models are employed to analyze pre-monsoon, monsoon, and post-monsoon seasonal variations, offering a dynamic and robust approach to water quality management. The results provide insights into key water quality indicators, such as pH, dissolved oxygen, and biochemical oxygen demand, allowing for the development of strategies aimed at operational excellence in environmental management. These findings contribute to both academic research and practical applications, emphasizing how decision sciences can enhance the quality and productivity of water resource management systems. Furthermore, the approach highlights how fuzzy logic-based systems can support policy-making and operational decision-making, ensuring sustainable environmental practices and improved water quality standards.

Keywords: Decision sciences; Fuzzy soft expert system; Water quality assessment; Anthropogenic influences; Environmental management; River water quality; Productivity improvement (search for similar items in EconPapers)
Date: 2026
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DOI: 10.1007/978-981-95-7545-9_4

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