## 3 Results and Discussion  
### The Results of the PARAFAC Analysis  
In this study, 3D-EEMs were analyzed by the PARAFAC method, which will obtain the correct component number and component maps of 3D fluorescence data [31]. We collected a total of four types of 3D fluorescence data online as well as through field sampling, including a total of 416 samples, with the least amount of FU datasets containing 45 samples. PARAFAC analysis requires a split-half test analysis, so a data volume greater than 21 is more appropriate [32]. After the analysis of these four types of datasets by PARAFAC analysis, four components (FU), four components (F), five components (PU), and six components (P) were obtained, respectively. PARAFAC analysis is conducted separately for each type of dataset. The process of analysis and component maps are shown in Figure 7.  
Figure 6: (**a**) is the single-layer network structure of VGG11; (**b**) is the structure of the whole fitting network. In (**a**), the input is a grayscale image of size 60 \(\times\) 60 and the output is a vector of size 3600. The output vector can be reshaped as a matrix of size 60 \(\times\) 60. VGG11 network contains 5 convolution-batch norm-pooling layers and 3 fully connected layers. The first and second fully connected layers are followed by a dropout layer, which can prevent the network from overfitting. VGG11 network is trained by the MSE loss function, and the training effect is verified by the cosine similarity. FU_C1 in this figure represents 1 st component map of FU, as the other 3 component maps. Each layer represents a group of “convolution-batch norm-relu-Max pooling”. Input is the grayscale image of the network (taking the FU sample as an example), and the target is the label fitted by the convolution network. In (**b**), four types of 3D-EEMs samples are first classified by the VGG16 classification network. After obtaining the classification results, combined with the component map number from PARAFAC analysis, the classification results and original 3D-EEMs are input into the CF-VGG11 network, and the component maps of 3D-EEMs can be obtained through CF-VGG11 network fitting. Among them, FU_4 indicates that the FU samples contain 4 component maps. VGG11-C1 represents the convolution network used to fit the first component. By inputting each type of 3D-EEMs to VGG11-C1, the first component map of each type of data can be obtained, which is similar to the other 5 subnetworks of CF-VGG11. In the experiment we performed PARAFAC analysis on all datasets (Figure 8 and Table 2 show the results of the PARAFAC analysis on FU dataset). Then, we uploaded the PARAFAC results to the OpenFluor database [33] for comparison and obtained the possible matter of these four 3D fluorescence components. Among them, the comparison results show that the similarity scores of components exceed 95% except component-three (94%). The characteristics of C1 were characterized by a peak at 350 nm excitation with 440 nm emission wavelengths and associated with a group of high molecular weight and aromatic molecules of terrestrial origin [34]. The characteristics of C2 were characterized by a peak at 300 nm excitation with 400 nm emission wavelengths, which is sensitive to the UV-A \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Component** & **EXmax/Emmax** & **Description** & **Number of OpenFluor Matches** \\ \hline C1 & 350 nm/440 nm & terrestrial humic-like, high relative & 21 \\ C2 & 300 nm/400 nm & UV-A humic-like, low molecular weight [35] & 14 \\ C3 & 290 nm, 400 nm/480 nm & humic-like [35] & 4 \\ C4 & 280 nm/320 nm & autochthonous protein-like, sensitive to & 11 \\  & & microbial degradation [36; 37] & 11 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Spectral characteristics of EEMs from comparing result of PARAFAC components and OpenFluor database. Figure 8: The results of PARAFAC analysis on FU dataset. The loading maps on the right show the result of split-half validation. Figure 7: PARAFAC analysis process and result (taking FU dataset as an example).