Calibration is the most critical phase in any water quality modelling process. This study proposes a sequential calibration methodology for any water quality model using reach-specific estimates of model parameters, which would aid in the improved prediction of river water quality characteristics. The proposed methodology accounts for the heterogeneity of river reaches, i.e., diverse characteristics of different reaches on the river stretch. The water quality model, QUAL2K, is coupled with MATLAB, a computing platform, to facilitate sequential estimation of reach-wise model parameters using a grid-based weighted average optimization. The Delhi segment of the Yamuna River is selected as study river stretch. Observations of water quality variables, dissolved oxygen and biochemical oxygen demand are used to calibrate and validate QUAL2K. Desirable performance measures are obtained during the calibration and the validation period. The methodology proves superior to the existing calibration methodologies applied over the study region. The proposed technique also captures the system behaviour effectively, through a systematic, efficient and user-friendly way. The proposed approach is expected to aid decision-makers in formulating better reach-wise management decisions and treatment policies by providing a simpler and efficient way to simulate water quality parameters.