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Water quality monitoring model construction by integration of multi-source data: a case study in Whangpoo River upper region

The method by the integration of multi-source data including remote sensing data, ground spectral measurement data and other in situ monitoring data, is presented in this paper to construct a quantitative water quality inversion model. The upper region of Whangpoo River in Shanghai is selected as a study area and the dissolved oxygen is chose as a typical water quality indicator. We first process the remote sensing imagery and field spectrometer data to obtain the accurate water reflectance. An inversion model of dissolved oxygen is then derived from the modeling analysis between the water quality data and the reflectance. The accuracy of the model is further confirmed, and this model is applied to invert the dissolved oxygen distribution in Whangpoo River upper region. The inverted water quality distribution has a high consistency with the practical case. This proves that the method by integration of multi-source data is an effective way to monitor the water quality.