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

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.