一定浓度氮磷水样的紫外吸收光谱数据量非常大，采用基于软阈值的小波变换可以对这些光谱数据进行有效压缩.不同浓度氮磷水样的紫外吸收光谱信号之间存在很强的相关性，利用偏最小二乘回归(PLSR)方法对光谱信号的强度和水样中氨氮浓度之间的关系进行回归建模可以降低这种相关性的影响，提高所建模型的拟合精度.实际水样测试数据的建模结果表明，用这种方法所建立的模型，氮磷浓度检测的最大相对误差为8.9%，完全满足检测精度的要求.

Data of the UV absorption spectra from the water samples with a certain concentration of the nitrogen and phosphorus is very large. Wavelet transformation (WT), based on the soft-threshold, can be effectively used to compress the spectrum signal of UV absorption spectra. High correlation often exists among the spectral intensity for the water samples with different concentration of the nitrogen and phosphorus. Partial least square regression (PLSR) can be used to decrease such correlation and to build an effective regression model for the sampled water. The detection precision is also increased in this way. Simulation of the tested water samples showed that the maximum relative error in the concentrations of nitrogen and phosphorus was 8.9%. The model can fully meet the requirements of detection precision.