Particle Swarm Optimization for Automatic Calibration of Large Scale Water Quality Model (CE‐QUAL‐W2): Application to Karkheh Reservoir, Iran

An automatic calibration of water quality model is developed in this research. Automatic calibration as the process to determine the parameters appearing in the equations of a 2‐dimensional, hydrodynamic, and water quality models (CE‐QUAL‐W2) is carried out with Particle Swarm technique as an optimization tool. In the calibration of the CE‐QUAl‐W2 model, evaporation as a significant parameter influences the thermal profile and water surface elevation in reservoir, simultaneously. Therefore to consider the simultaneous effects of the water temperature variations on water surface elevation in the reservoir, a multi objective technique is used to minimize the weighted sum of total deviations of temperature from field data at check points on monitoring days and those of water surface elevation on daily monitoring period. The proposed approach overcomes the high computational efforts required if a conventional calibration search technique was used, while retaining the quality of the final calibration results. The automatic calibration approach is applied in temperature and water budget calibration of Karkheh reservoir in Iran. Applying the proposed automatic calibration approach, shows the produced results by the CE‐QUAL‐W2 model with the calibrated coefficients agree closely with a set of field data.