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Ultraviolet-visible (UV-Vis) spectroscopy technology is used to measure chemical oxygen demand (COD) of water. The standard samples are prepared using potassium hydrogen phthalate. With different pretreatment methods and various modeling methods, the COD prediction models’ performance based on raw spectra are compared, and the sensitive wavelengths are selected on basis of the prediction results. In order to build prediction models with optimal performance, the water quality parameters’ effects on the detection of COD are also researched, and the experiments are carried out to find the relationship between COD and the sample’s temperature, turbidity. Then a combined method based on UV-Vis spectrum and water quality parameters is developed. The samples’ temperature and turbidity data are normalized with Min-Max Normalization method, and then different coefficients are assigned to the two parameters to form a new data, basing on the correlation coefficients of the models established by fusing the spectral information with temperature and turbidity respectively. A prediction COD model with the fusion data of water quality parameters and spectral information is established, using Partial least Squares(PLS) method. The experimental results show optimal performance (Mean ARE=2.46; RMSEP=1.92) for the prediction set. And this COD detection method set the foundation for further implementation of online analysis of water quality.
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