Spatial differences of dissolved organic matter composition and humification in an artificial lake

In recent years, there has been a gradual increase in the impact of human activities and climate change on the eutrophication of lakes, such that these impacts can lead to the accumulation of dissolved organic carbon (DOC) (Liu et al. 2021; Li et al. 2022; Nai et al. 2023). The spatial and temporal dynamic distribution of DOC in lakes has an extremely complex impact on the lake carbon cycle and is currently at the forefront of lake carbon cycle research (Liu et al. 2022). Dissolved organic matter (DOM), as a complex heterogeneous complex (Jeong & Kwak 2021; Huang et al. 2022), is used as a good tracer of DOC sources in lakes (Wickland et al. 2007). Most of the current studies have focused on the distribution of DOM in plateau lakes (Song et al. 2019), freshwater lakes (Huang et al. 2022), and saltwater lakes (Du et al. 2016), while there is a relative lack of studies on the vertical dynamic distribution of DOM composition structure and degree of humification in artificial lakes (which are most affected by human activities). According to previous studies (Liu et al. 2020; Ke et al. 2023), the composition and structure of DOM show large variations by various human activities. Therefore, elucidating the effects of depth variation in artificial lakes on the composition structure and degree of humification of DOM is of great scientific significance for an in-depth understanding of lake eutrophication and carbon cycling.

Estuaries connect lake–lake, lake–river (Zhou et al. 2019), and lake–ocean ecosystems and are key areas of the global carbon cycle (He et al. 2022). These ecosystems are significantly affected by human activities, estuarine circulation is driven by vertical and lateral advection, and spatial and temporal changes in the phytoplankton community structure and biomass due to discharge currents (Geyer & MacCready 2014; Zhou et al. 2021; Perrot et al. 2023; Phlips et al. 2023). Estuaries can bring a large amount of DOM into the lake, making the source of DOM at different depths in the lake estuary, and the composition varies greatly (Jaffé et al. 2004). The estuarine environment is subject to natural and anthropogenic influences and the re-suspension of sediments into the lake (Harfmann et al. 2021), the further release of DOM from the sediment into the lake makes the differences further significant. However, these differences also limit the understanding of lake eutrophication and carbon cycling. Therefore, revealing the dynamic patterns of DOM composition and humification with depth in artificial lake estuaries is a primary task in assessing lake eutrophication and carbon cycling.

Three-dimensional excitation–emission matrix fluorescence spectroscopy (3D EEM) is a technique widely used to characterize the fluorescent properties of DOM (Coble 1996; Wufuer et al. 2014; Yuan et al. 2023). However, due to the complexity and heterogeneity of DOM compositions, overlapping fluorescence spectroscopy cannot be identified accurately in 3D EEM (Song et al. 2018). The 3D EEM combined with fluorescence regional integration (3D EEM-FRI) can be used to determine the integration of the volume below each region of the 3D EEM in the DOM and quantify the fluorescence intensity (FI) in the specified region (Hua et al. 2007; Wu et al. 2011; Song et al. 2017). Additionally, the 3D EEM coupling with parallel factor analysis (3D EEM-PARAFAC) has the advantage of decomposing the fluorescence signal of DOM into relatively independent fluorescent components to reduce the interference between fluorescent components (Chen et al. 2003; Zhang et al. 2011; Sgroi et al. 2017; Zhao et al. 2017). Both 3D EEM-FRI and 3D EEM-PARAFAC have been applied widely to analyze 3D EEM spectral characteristics of DOM from aquatic environments (Chen et al. 2003; Du et al. 2016; Song et al. 2019). Therefore, both 3D EEM-FRI and 3D EEM-PARAFAC can be applied to analyze the dynamics of DOM composition structure with depth in the estuary of an artificial lake. Biological index (BIX) and humification index (HIX) are powerful fluorescence indices, and are commonly used to investigate the source of DOM and the degree of humification (Du et al. 2021). The values of HIX and BIX suggested that Lakes-Yangtze River DOM was dominated by freshly-generated compounds with low terrestrial humic contents (Du et al. 2021). Therefore, the combination of the 3D EEM-FRI/PARAFAC method and fluorescence indices will support the chemical characteristics (e.g. degree of humification) and the vertical distribution characteristics of the constituents of DOM in the artificial lake estuary, and construct a fluorescence index system to predict the degree of humification of DOM in the artificial lake estuary, providing theoretical support for understanding eutrophication and carbon cycling in the artificial lake estuary.

In this study, Lake Hongfeng, the largest artificial lake in Guizhou Province, was selected as the subject. 3D EEM, FRI/PARAFAC and fluorescence indexes were used to study the spatial distribution of DOM structure in the lake. The objectives were as follows: (1) to study the vertical changes of fluorescence components and humification degree of DOM in estuarine and lake center; (2) to study the vertical variation of DOM fluorescence index; (3) develop and propose a new method for evaluating the humification degree of DOM based on fluorescence index.

Lake Hongfeng is a typical artificial lake in the upper and middle of the Maotiao River, a first-level tributary of the Wujiang River in Guizhou plateau, China. With a lake surface area of 57.2 km² and a water retention time of 0.325 years, the lake provides multiple services including irrigation, aquaculture, functioning as a drinking water source, and improving peripheral ecosystems (Supplementary material, Figure S1) (Wang et al. 2009). Water samples were collected in March 2023 from the estuary (marked as HF-1) and centre (marked as HF-2) of Lake Hongfeng (Supplementary material, Figure S1). The 24 samples were collected from HF1 with depths of 0, 1, 3, 5, 7, 9, 11, 13, 15, 17, and 19 m, and from HF-2 with depths of 0, 2, 4, 6, 8, 10, 12, 14, 16, 18, 20, 22 and 24 m, respectively. All water samples were stored in plastic bottles in the dark at 4 °C. All water samples were transported to the laboratory and filtered through 0.45 μm glass fiber filters (pre-combusted at 450 °C for 6 h) within 10 h. The pH and DOC of all collected samples ranged from 6.8 to 7.8 and 1.3–2.1 mg/L, respectively.

The 3D EEMs of DOM were obtained with the emission wavelength (Em) from 250 to 500 nm with 2 nm increments, and the Ex from 220 to 400 nm with 5 nm increments using a fluorescence spectrometer (Hitachi F-4500, Japan). The slit widths for Em and Ex were 10 and 5 nm, respectively. The scanning speed and PMT voltage were set at 1,200 nm·min⁻¹ and 400 V, respectively. The inner filter effects were established by diluting the Lake Hongfeng with pure water (Milli-Q, 18.2 MΩcm), and the inner correction was unnecessary for our samples based on UV-Vis absorbance (Guo et al. 2015). The inner effects of DOM were also ignored during the investigation of natural lake waters, and sea waters, as well as simulating water with fulvic acids and humic acid with low concentration of DOM (Guo et al. 2015).

The possible effects of Rayleigh and Raman scatters were minimized with two steps. First, subtracting the 3D EEMs of Milli-Q water from each 3D EEM of solution samples. Second, the area without fluorescence (Em < <Ex) is inserted as a series of zero values (Bahram et al. 2006). The 2–7 component models that based on PARAFAC, using residual analysis and half-split analysis to determine the appropriate number of PARAFAC components in DOM. The maximum FI of PARAFAC components was used to represent the concentration of the PARAFAC component (Bahram et al. 2006; Guo et al. 2015). The 3D EEM-PARAFAC was performed by use of MATLAB 2009a (MathWorks, Inc., USA) with drEEM toolbox (www.models.life.ku.dk). The Pearson correlation analysis and principal component analysis (PCA) for P_i,n, FI, HIX and BIX of DOM were also calculated using SPSS 16.0 software.

Based on the FRI theory, five regions in the 3D EEMs of the DOM from different sources represent the following Regions I (Ex/Em: 220–250/250–330 nm) and II (Ex/Em: 220–250/330–380 nm), region III (Ex/Em: 220–250/380–500 nm), region IV (Ex/Em: 250–400/250–380 nm), region V (Ex/Em: 250–400/380–500 nm) (Chen et al. 2003). Peaks A and B are located in Region III and Region V, respectively (Figure 1, Supplementary material, Table S1). Regions III, V, and II were represented as fulvic- and humic-like materials (Figure 1, Supplementary material, Table S1). This result was consistent with the 3D EEM categorization results above.

The values of P_i,n are shown in Supplementary material, Figure S2. The fluorescent materials measured in HF1-DOM and HF2-DOM, in descending order of content, were humic-like materials > fulvic-like materials > protein-like materials. The ratio of humic-like (P_V,n) : fulvic-like (P_III,n) : tyrosine-like (P_I,n and P_II,n) : tryptophan-like (P_IV,n) materials is about 12:4:2:1 according to 3D EEM-FRI analysis of both HF1-DOM and HF2-DOM. In detail, the P_V,n values of the DOM were the greatest at 61.1 ± 1.1% and 65.8 ± 1.2% for HF-1 (HF1-DOM) and HF-2 (HF2-DOM), respectively, indicating that humic-like materials were the primary fluorescent components in Lake Hongfeng (Supplementary material, Figure S2). Fulvic-like materials (P_III,n) accounted 22.2 ± 1.0% and 20.1 ± 0.3% for HF1-DOM and HF2-DOM, respectively (Supplementary material, Figure S2). Tyrosine-like materials (P_I,n and P_II,n) accounted 9.9 ± 0.5% and 9.1 ± 0.6% for HF1-DOM and HF2-DOM, respectively (Supplementary material, Figure S2). Tryptophan-like materials (P_IV,n) accounted for 6.8 ± 0.6% and 5.1 ± 0.3% for HF1-DOM and HF2-DOM, respectively (Supplementary material, Figure S2). Tryptophan- and tyrosine-like materials were classified as protein-like materials (Song et al. 2019). The consistency of the DOM composition ratio between the estuarine and lake center can prove the similarity of DOM composition in the whole region of Lake Hongfeng.

Overall, the HF1-DOM located in the estuarine position contains higher levels of protein-like materials (16.7%) than the HF2-DOM (14.2%), indicating a greater human influence on the composition of the DOM at the estuarine location. This result is consistent with those obtained in previous studies (Du et al. 2021; He et al. 2022). The most significant variation with depth in protein-like and fulvic acid-like fractions (>50%) was found in HF1-DOM at the estuarine location, likely due to human influence and sediment suspension in this area (Zhou et al. 2018; Harfmann et al. 2021). The large difference between the HIX of the middle layer of HF1-DOM (1.35) and that of the surface layer and the middle layer further indicates that the unstable water conditions at the estuary lead to an unstable microbial degradation process, resulting in DOM stratification. Additionally, a previous study found that vertical and lateral advection significantly contributes to the stratification of the water column at estuarine locations (Geyer & MacCready 2014; Zhou et al. 2021; Perrot et al. 2023; Phlips et al. 2023). This natural phenomenon may also play a role in DOM stratification.

Significant positively linear corrections (r = 0.992, p < 0.01) was observed for FI_C1 vs. FI_C4, whereas the negatively significant correlations were exhibited between FI_C3 vs. FI_C4 (r = −0.680, p < 0.01) and FI_C2 vs. FI_C4 (r = −0.851, p < 0.01), respectively (Supplementary material, Figure S3a–3c, Table 2). The PARAFAC components representing different sources may exhibit significant correlations, especially protein-like components that are more relevant to human activity inputs (Song et al. 2019). In addition, the greater positive significant correlations of FI_C4 vs. FI_C1 (r = 0.992, p < 0.01) suggested that the humic-like components containing more conjugated π-electron systems with electron-withdrawing substituents and fulvic-like components in DOM might have the same source of origin. However, the greater negative significant correlations of FI_C4 vs. FI_C2 (r = −0.851, p < 0.01) suggested that the humic-like components containing less carboxylic-like and phenolic-like groups and fulvic-like components in DOM might have a different source of origin. The different correlations shown by FI_C1 and FI_C2 with FI_C4 also support PARAFAC's analysis of subtle structural differences in the same components. The significant correlations of humic- and fulvic-like components suggested might have the same source of region reported by Song et al., who studied depth-dependent of DOM in Lake Baihua using fluorescence spectroscopy (Song et al. 2019).

The HIX was negatively correlated with BIX (r = −0.598, p < 0.01) and P_I+II+IV,n/P_III+V,n (r = −0.720, p < 0.01), and positively correlated with FI_C1 (r = 0.576, p < 0.01), FI_C4 (r = 0.584, p < 0.01), and the radio of fulvic-like to protein-like components (FI_C4/FI_C3) (r = 0.772, p < 0.01) (Table 2). There were no significant correlations between HIX and FI_C2 and FI_C3. That is, the degree of humification of the DOM decreased as the increase of the values of BIX and P_I+II+IV,n/P_III+V,n, as well as the decrease of the values of FI_C1, FI_C4, and FI_C4/FI_C3. The fluorescence indices P_I+II+IV,n/P_III+V,n, FI_C1, FI_C4, and FI_C4/FI_C3 can be used to indicate the degree of humification of DOM in artificial lakes. Furthermore, the minimum P_I+II+IV,n/P_III+V,n value (0.15–0.2) and the maximum FI_C4/FI_C3 value (1.59–2.00) occurred at the depths of 9 and 14 m showed the least content of protein-like component and the highest humification level of DOM, which is consistent with the results of the HIX analysis.

PCA was performed on the fluorescence indices of the DOM (Figure 5(b)). The principal components PC1 and PC2 had variance contributions of 71.23% and 20.03%, respectively. The greater sum of variance contributions (91.26%) indicated that PC1 and PC2 could be used to reflect the degree of humification and the influence of human activities on Lake Hongfeng, respectively. The fluorescence indices including HIX and FI_C4/FI_C3 related to fulvic-like and humic-like materials had large positive loadings with PC1, indicating that PC1 could be presented as the degree of humification. The greater values of HIX and FI_C4/FI_C3 indicated the greater content of humic-like and fulvic-like materials, as well as the greater degree of humification in Lake Hongfeng. The fluorescence indices including BIX and P_I+II+IV,n/P_III+V,n related to protein-like materials presented the large positive loadings of PC2 according to PCA analysis (Figure 5(b)), indicated that PC2 could present the influence of human activities. The fluorescence indices P_I+II+IV,n/P_III+V,n and FI_C4/FI_C3 can be used to indicate the degree of humification and the influence of human activities of DOM in artificial lakes. From the perspective of Lake Hongfeng as a whole, the humification degree of the middle water is higher and the influence of human activities is lower. More importantly, the low P_I+II+IV,n/P_III+V,n and FI_C4/FI_C3 values of the estuarine also indicate that the water body in the estuarine has a low degree of humification and is greatly affected by human activities.

Characterizing changes in the composition and humification of DOM with depth in estuaries of artificial lakes can aid in assessing water quality and predicting the fate of various pollutants in aquatic systems. Moreover, the combined multi-fluorescence indices of DOM can be utilized to respond to sudden water quality deterioration, design water supply system intakes, and manage the sustainability of water ecosystems. Understanding depth-dependent changes in DOM will provide valuable insights for water quality assessment and contamination risk prediction at different depths in estuaries.

Based on 3D EEM-FRI, the composition of DOM in Lake Hongfeng is consistent and not affected by the region where it is located. Humic acid is an important part of DOM in Lake Hongfeng. Changes in the composition of HF1-DOM and HF2-DOM with increasing lake depth were observed in three stages, including surface, middle, and bottom stages. The composition of HF1-DOM and HF2-DOM did not change significantly in both the surface and bottom stages, whereas the composition of HF1-DOM located at the estuarine location varied more in the middle stage with no obvious pattern, probably due to the estuarine location being subject to human influence and sediment suspension. The BIX (0.67–0.77) and HIX (4.74–7.02) indicated that the DOM had relatively weak autogenic characteristics in the surface stage and relatively strong terrestrial characteristics in the middle and bottom stages. The HIX had negatively correlated with P_I+II+IV,n/P_III+V,n (r = −0.720, p < 0.01), and positively correlated with FI_C2/FI_C3 (r = 0.772, p < 0.01), indicating that P_I+II+IV,n/P_III+V,n and FI_C4/FI_C3 can be used to indicate the degree of humification of DOM in artificial lake. The results of each index show that the middle water body of Lake Hongfeng is less affected by human activities, the estuary is more affected by human activities, and the humification degree is significantly lower than that of the center of the lake. It is noteworthy that in terms of quantifying the uncertainty in optical changes, the variations in DOM are primarily concentrated in the fluorescence component. More advanced techniques are required to quantify changes in the molecular structure of DOM, rather than simply making direct comparisons of fluorescence changes. Despite the need to consider certain finer limitations and uncertainties, the multi-indicator coupled assessment system for the degree of humification in artificial lakes established by this study will significantly enhance our understanding of the biogeochemical processes in artificial lake systems.

This work was supported jointly by the Shanghai Post-doctoral Excellence Program (2023331).

All relevant data are included in the paper or its Supplementary Information.

The authors declare there is no conflict.