The study focuses on the prediction of water quality parameters (WQP) in rivers, particularly during periods of drought, in order to minimize the impact of pollution. It utilizes computational fluid dynamics (CFD) as a valuable tool for developing detailed models that analyse the dispersion of WQPs in rivers.The research aims to establish the relationship between WQPs and key flow parameters. The turbulence model employed in the study demonstrates a strong correlation between parameters such as pH, dissolved oxygen (DO), biochemical oxygen demand (BOD), cadmium (Cd), iron (Fe), phosphate, and flow parameters including velocity, shear stress, and pressure. The software tool ANSYS Fluent is utilized for conducting the analysis, with AutoCAD used for geometry import, and MATLAB and artificial neural networks (ANN) employed for data validation.The specific study area investigated in this research is a section of the Haora River located in the state of Tripura. By comparing the results obtained from the CFD simulations with experimental data, the study demonstrates good agreement, with an error rate of approximately 15%.The overall goal of this work is to contribute to the understanding of how WQPs in rivers are affected by flow parameters, enabling better prediction and management of water quality during water scarcity events and aiding in the mitigation of pollution impacts. The study area is a section of Haora River in Tripura state.