紫外-可见光谱法水质检测中，检测设备面对多样性的地表水体容易受到悬浮颗粒物引起的浊度干扰，导致谱线整体非线性抬升，测量精度显著下降。研究了一种基于Mie散射理论的紫外-可见水质光谱浊度干扰补偿算法，借以提高可溶有机物含量的检测精度。通过截取水样本紫外-可见光谱中主要由颗粒物散射引起的450~1100 nm段光谱，采用基于Mie散射理论的光全散射颗粒物粒径分析法，重建了水样本所含颗粒物的粒径分布。利用粒径分布的二次反演，估计了220~450 nm可溶有机污染特征光谱段中由颗粒物引起的消光值，实现了对浊度干扰的精确补偿。实验结果表明，该算法对不同地表水样本均表现出了良好的浊度补偿效果，化学需氧量解算精度得到较大提高。且补偿算法无需大量实验获取先验数据，可提高紫外-可见光谱法水体可溶有机物检测的准确性和检测部署的灵活性与适应性，具备实用价值。

A turbidity disturbance compensation algorithm based on the Mie scattering theory for water quality measurement by ultraviolet-visible spectroscopy is studied in order to reduce the turbidity disturbance caused by light scattering from suspended particles in the waterbody. The disturbance leads to a nonlinear lifting of the spectrum and results in significant decrease of the measurement accuracy. By the total light scattering method based on the Mie scattering theory, particle size distribution of the water sample can be reconstructed through the ultraviolet-visible spectrum in the region from 450 nm to 1100 nm, which is mainly related to the particle scattering. Then, with the secondary inversionary of the particle size distribution, extinction spectrum caused by particle scattering in the wavelength region of 220-450 nm which is the characteristic spectrum region of the organic pollutant can be estimated. So the accurate compensation of the turbidity distribution is realized. Experimental results show that a good effect of turbidity compensation for different water samples is achieved by the algorithm without a lot of prior experimental data. Calculation accuracy of the chemical oxygen demand has been greatly improved. It is of practical value for increasing the accuracy, flexibility and adaptability in the ultraviolet-visible spectroscopy for water soluble organic measurement.