Comprehensive study of the occurrence and characteristics of carbon, nitrogen, and phosphorus in sediments and riparian soils of large drinking water reservoir

doi:10.21203/rs.3.rs-1715329/v1

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Comprehensive study of the occurrence and characteristics of carbon, nitrogen, and phosphorus in sediments and riparian soils of large drinking water reservoir

https://doi.org/10.21203/rs.3.rs-1715329/v1

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The contamination of nutrients has caused considerable worry about the environment, resource value, and ecological worth of drinking water reservoirs. Therefore, we comprehensively studied the abundance, sources, distribution, and environmental behavior of carbon, nitrogen, and phosphorus in Fengshuba Reservoir (FSBR) (a large drinking reservoir, China). Seasonal hydrological circumstances had little influence on the nutrient abundance and structural component of the FSBR, while carbon, nitrogen, and phosphorus abundance, composition, and environmental behavior varied significantly between various environmental media (sediment and soil phases). Microbial-derived humus (C1), terrestrial-derived humus (C2), and protein-like tryptophan (C3) were identified as the three primary fluorescence components using parallel factor analysis. The abundance of colored dissolved organic matter (CDOM), molecular weight, aromatization degree, and humification degree of dissolved organic matter (DOM) in the sediment were lower than in the soil, whereas the authigenic component was greater than in the soil, according to spectral index analysis. The main sources of humus in FSBR were biogenic contributions. Principal component analysis indicated that three components were closely associated to phosphorus in the sediment phase, whereas nitrogen and phosphorus in the soil phase were mainly related to C1 and C2. In summary, in the management and control of water environment nutrients in reservoirs, soil media in the riparian zone must be carefully considered.

Fengshuba Reservoir

Sediment/soil phase

Nutrients

Dissolved organic matter

Geo-chemical behavior

Extensive construction of dams has facilitated the formation of more and more reservoirs (Chen et al. 2020, Humbsch &Bielitz 2018). Reservoir systems, as modern water environmental systems arising from the human transformation of rivers, support basic human needs in terms of drinking water, food, energy, human health and general well-being (Guo et al. 2021). The reservoir system acts as a filter and buffers through its dilution, diffusion, sedimentation, and decomposition (Ruogu et al. 2021). Sediment as a more stable environmental medium in the reservoir water environment, has become a "sink" for all nutrients and pollutants, and may also become a "source" under certain conditions. Moreover, it has become a hot spot for research in the field of water science (Fonseca et al. 2011, Hou et al. 2014a). In addition, it is noteworthy that the role played by the soil in the water environment as a "lung" in recent years has gained the attention of scholars at home and abroad, especially in large drinking water source reservoirs (Hu et al. 2021). Therefore, in view of the role of water sediment and soil in the geochemical cycle of elements, it is important to actively carry out research on nutrient availability and morphology in sediment and soil of large water source reservoirs.

Biogeochemical cycles of carbon (C), nitrogen (N) and phosphorus (P) in sediments and riparian soils of aquatic environment can influence eutrophication of water body (Gaget et al. 2017), environmental behavior of persistent organic pollutants (Stubbins et al. 2014), morphology and toxicity of heavy metals (Li et al. 2018), and structure and functional response of microbial communities (Zingel et al. 2018). Some factors/conditions, like temperature, redox conditions, pH, and the concentrations of other inorganic species such as sulfide and iron in the sediment and the water column can also influence the carbon, nitrogen, and phosphorus and environmental behavior (Hayakawa et al. 2015, Ribeiro et al. 2008). An increase in temperature generally reduces phosphorus adsorption by mineral particles in the sediments (Perkins &Underwood 2001). Anoxic conditions in the hypolimnion can intensify denitrification and promote the release of nitrogen from sediments (Hou et al. 2014b). It also causes the release of phosphorus, thereby contributing in eutrophication (Fonseca et al. 2011). Therefore, a systematic study of occurrence and morphology of carbon, nitrogen, and phosphorus in reservoir sediments/riparian soils will help to understand and improve the biogeochemical cycle of the water environment.

However, the reports of carbon, nitrogen, and phosphorus in the aquatic systems are generally focused on rivers (Linyan et al. 2019), lakes (Wang et al. 2009b), and oceans (Yu et al. 2012). There are a lack of comprehensive studies on nutrients in water source reservoirs, especially sediments (Jiang et al. 2011) and the soil phase (Li et al. 2020) of the water level drop zone of the reservoir. Located at the head of the Dongjiang River in southern China, Fengshuba Reservoir (FSBR) provides drinking water to nearly 40 million people in the surrounding cities of Longchuan, Shenzhen and Guangzhou., and can be used as a typical study of large water source reservoirs. With the rapid economic development of Dongjiang River Basin (Yanhu et al. 2013), the FSBR may be polluted by nutrients, which will threaten the ecological environment and human health in the basin (Rong et al. 2017). Hence, investigating the occurrence and morphology of nutrients in the FSBR is crucial. FSBR was selected as the case study, to (1) elucidate the level of nitrogen and phosphorus pollution and the characteristics of different forms of nitrogen and phosphorus; (2) analyze the occurrence and sources of DOM; and (3) analyze the key factors affecting organic carbon, nitrogen and phosphorus.

2.1 Study area and sampling

The main catchment sources of FSBR are the Beiling river (watershed area 2363 km²) and the Xunwu river (watershed area 2697 km²). FSBR has a water surface area of about 16.45 km² and a water depth of 70 to 100 m (Chen et al. 2017). Detailed descriptions of the basic hydrological information of the reservoir were shown in Table 1. Samples were collected from five sampling sites (S1-S5) from July 18 to 20 (2015, summer), November 25 to 27 (2015, autumn) and March 14 to 16 (2016, spring), respectively (Fig. 1). Surface sediment samples (~ 15 cm) were collected using a gravity settling sampler. Additionally, surface soil samples (~ 15 cm) were collected from the drawdown area at the corresponding sampling sites only in March 2016 (spring), when the reservoir water level dropped (Chen et al. 2020). To reduce sampling error, all the samples at each site were collected in triplicate. Samples were immediately transported to the laboratory and stored in acidic plastic bottles at − 20°C.

Table 1

Monthly description of the basic hydrological information of Fengshuba Reservoir. Average hydraulic retention times were calculated as volume of reservoir divided reservoir outflow.
	Air Temperature (℃)	Water Temperature (℃)	Rainfall (mm)	Beiling River Inflow (m3/s)	Xunwu River Inflow (m3/s)	Reservoir Outflow (m3/s)		Hydraulic Retention Time (days)
Summer	27.3–28.4	18.7–32.9	218	76.6	87.4	110	1.16	122
Autumn	15.6–18.0	21.1–25.0	28.5	29.2	33.4	62.7	1.33	246
Spring	14.3–16.5	15.5–19.0	316	175	200	264	1.11	49

2.2 Nutrient analysis

Total carbon (TC), total organic carbon (TOC), and total inorganic carbon (TIC) in the sediments were determined by Multi N/C3000 in Jena, Germany. Total nitrogen (TN) was divided into transformable nitrogen (TF-N) and non-transformable nitrogen (NTF-N). TF-N consists of ion-exchange nitrogen (IEF-N), carbonate bound nitrogen (CF-N), iron-manganese oxidized nitrogen (IMOF-N), and organic sulfide nitrogen (OSF-N). Total phosphorus (TP) was divided into inorganic phosphorus (IP) and organic phosphorus (OP) by the SMT method. IP was composed of iron/aluminum bonded phosphorus (NaOH-P) and calcium bonded phosphorus (HCl-P), and OP was calculated by the difference between TP and IP. Synchronously, standard stream sediment GBW07301 was used to verify the reliability of the method and correct the accuracy of monitoring results in the whole process of nitrogen and phosphorus speciation determination in sediment/soil.

2.3 Determination of dissolved organic matter spectrum

Firstly, the sediment and soil samples pretreatment were carried out as follows: after screening (100 mesh), 2g sediment/soil samples were dissolved in 20 mL deionized water, shaken for 24 h (220 r/min,25℃), centrifuged for 10 min (5000 r/min), then filtered through 0.45 µm glass fiber filter membrane to obtain the filtered supernatant (dissolved extracted DOM). Uv-visible absorption spectrometry was determined by Cary60 of Agilent Company (United States). The spectrophotometer was equipped with a 1cm quartz cuvette and scanned at 1nm intervals in the 200–800 nm wavelength. 3D fluorescence spectrometry was performed by a Hitachi F-7000 fluorescence spectrometer equipped with a 150 W ozone-free xenon lamp (PMT voltage = 400 V). The excitation wavelength (Ex) ranges from 200 to 450 nm, and the scanning interval is 5 nm. The emission wavelength (Em) ranges from 200 to 600 nm, and the scanning interval is 5 nm. Both the excitation and emission monochromator slit widths are 10 nm. Scanning was performed at scanning speed of 1200 nm/min. Raman scattering peak effect of water can be corrected by the instrument built-in system by deducting Mili-Q water, and the Raman signal of its fluorescence intensity is defined by Raman unit. The correction of the internal filtering effect and the elimination of Raleigh scattering were performed according to the experimental manual (Murphy et al. 2013).

2.4 Optical indices and Parallel factor analysis

Uv-visible absorption spectrum parameters used in this paper mainly include absorption coefficient a (350), SUVA₂₅₄, and spectral Slope Ratio (S_R). a (350) refers to the absorption coefficient of colored dissolved organic matter (CDOM) at 350 nm wavelength (Zhang et al. 2009b). Specific UV absorbance at 254 nm (SUVA₂₅₄) was determined as A₂₅₄/DOC (Chen et al. 2013). The spectral slope ratio (S_R) is the ratio of S_{275 ~ 295} and S_{350 ~ 400} (Helms et al. 2009). The fluorescence spectrum parameters used in this study mainly include the biological origin index (BIX), humification index (HIX), and fluorescence index (FI). BIX refers to the ratio of fluorescence intensity at the emission wavelength of 380 nm to the maximum fluorescence intensity at the wavelength of 420–435 nm at the excitation wavelength of 310 nm. HIX refers to the ratio of integral fluorescence intensity of 435–480 nm wavelength and 300–345 nm wavelength when the excitation wavelength is 254 nm. FI refers to the ratio of fluorescence intensity at 470 nm and 520 nm when the excitation wavelength is 370 nm. Three-dimensional fluorescence spectral matrix data of DOM was analyzed using the PARAFAC model in this study.

2.5 Nitrogen and phosphorus risk evaluation

The integrated pollution index evaluation method was used to evaluate the degree of nitrogen and phosphorus pollution in sediments (Ji et al. 2016, Zhao et al. 2021), and the integrated pollution index was obtained from the individual pollution index equations (1) and (2):

${S}_{i}={C}_{i}/{C}_{s}$ (1)

$$FF=\sqrt{\frac{{F}^{2}+{F}_{max}^{2}}{2}}$$

${C}_{i}$ and ${C}_{s}$in the above formula were expressed as the actual concentration and evaluation standard content of evaluation factor $i$, ${S}_{i}$ is a single evaluation index, and where C_STN = 0.67 g/kg, C_STP = 0.44 g/kg. In addition, $FF$ is the integrated pollution index, $F$ is the average evaluation index of n evaluation factors, and ${F}_{max}$is the maximum single evaluation index among evaluation factors.

2.6 Data analysis

Excel 2016, OriginPro 2018 (originLab, USA), and SPSS 21.0 (IBM, USA) were used for data analysis, chart-making, and statistical examination. ArcGIS 10.7 (ESRI, USA) was used for the geographic distribution of sampling points. Correlation analysis was performed using the R studio platform (Corrplot packet). Principal component analysis (PCA; Canoco 5.0) was further used to explore relationships between DOM components and nutrient properties, as well as the associations between with spectral indices. During data analysis, ANOSIM analysis based on Bray-Curtis distance was performed to determine group differences, and statistical significance was analyzed using a permutation test. In this study, group values were expressed as mean ± standard error (SD), and the levels of statistical significance were mainly divided according to: extremely significant, P < 0.01; significant, 0.01 ≤ p ≤ 0.05; not significant, P ≥ 0.05.

3.1 Occurrence and distribution of nitrogen

The composition of sediment, the degree of water disturbance, and hydrological circumstances, among other factors, determine sediment particle size, which is the most important physical feature of sediment medium. We divided the grain sizes into three categories in this study: clay (< 0.004 mm, %), silt (0.004–0.063 mm, %), and sand (0.063-2 mm, %). The distribution of particle size, TOC, TN, and TP concentrations in FSBR sediments and riparian soils is shown in Table S1. The sediments are mostly made up of silt (41.6–51.2%) and sand (40.8–53.0%). Grain size analysis of the soil also indicates that silt (37.3–57.0%) and sand (31.8–58.7%) are also the main components, which differs from the Paiva Castro Reservoir, which is dominated by clay and silt (Cardoso-Silva et al. 2018a), but is similar in composition to the silt-dominated Lagoon of Venice (Molinaroli et al. 2009) and the sand-dominated Jianxi Basin. ANOSIM analysis revealed substantial variations in the particle size composition structure of sediments and riparian soils based on Bray-Curtis distances (Fig. S2, Table S3), and Ye et al. reached the corresponding conclusion (Ye et al. 2017).

The reservoir sediments have a TN concentration of 2.0-2.8 g/kg (Table S1, Fig. S1), that is greater than the soil background value, which is in line with previous study (Wu et al. 2011, Zhang et al. 2017). The integrated pollution index approach (Ji et al. 2016) was used to determine the pollution level, which was based on the sediment pollution level grading assessment standard S_TN (Table S2). The study discovered that the yearly distribution range of S_TN in the reservoir sediment was 2.99–4.18. As a result, it was determined that the total quantity of nitrogen pollution was severely contaminated. TF-N concentrations varied from 249.07 to 346.44 mg/kg, representing 9.22–15.46% of TN (Fig. 2a). In terms of TF-N, all the sediments in the reservoir exhibited rank is IEF-N > OSF-N > IMOF-N > CF-N (Fig. S1, Fig. 2a), with IEF-N content of 152.58-218.07 mg/kg and proportion of 54.46–74.35% in TF-N, which differed from Mochou Lake, Xuanwu Lake, and Daming Lake, where OSF-N and IMOF-N were prominent (Wang et al. 2009a). Since IEF-N is the nitrogen form with the weakest binding capability in sediments, it is easily released from sediments into water when external variables are present. Thus, IEF-N might become one of the most significant nitrogen sources in water (Wang et al. 2009a). Based on the PCoA analysis (Fig. 2b), an ANOSIM analysis was conducted to match the profiles of nitrogen forms, the distribution patterns of nitrogen forms exhibited no distinct differences according to the seasonal factor (ANOSIM, R = 0.043, P = 0.271) (Table S3), indicating that seasonal variations and hydrological conditions may not significantly affect the occurrence levels of TN and various nitrogen forms in the reservoir sediments (Farmaki et al. 2014).

In riparian soils, TN concentrations varied from 1.2 to 4.2 g/kg, with TF-N levels ranging from 90.54 to 136.25 mg/kg (Table S1, Fig. S1). The occurrence level of TF-N in the riparian soil is substantially lower than the occurrence level of TF-N in the sediment (P < 0.01), especially IEF-N, showing that the sediment is still an important occurrence location of nitrogen release in the overlying water column (Wang et al. 2009a). The rank of IMOF-N > OSF-N > IEF-N > CF-N was found in riparian soils as a whole (Fig. S1, Fig. 2a), indicating that ferromanganese oxidized nitrogen is the predominant form of TF-N in the soil. This composition differs from the major nitrogen form of TF-N in the sediment, indicating that the fraction of ion-exchange nitrogen in riparian soil is minimal and has little impact on the nitrogen occurrence level in overlaying water bodies (Wang et al. 2009a). Furthermore, the distribution patterns of nitrogen forms were explored using the PCoA and ANOSIM Analysis. Environmental media had significant effects on the distribution patterns of nitrogen forms (ANOSIM, R = 0.85, P = 0.001) (Fig. S2, Table S3), and PCoA based on Bray-Curtis distance for nitrogen forms showed obvious separations among the sediment phase and soil phase (Fig. 2b). This implies that diverse environmental media have an impact on the environmental behavior of nutrients in the aquatic environment (Ye et al. 2017).

3.2 Occurrence and distribution of phosphorus

The TP content of the reservoir sediment ranged from 646.9 to 955.9 mg/kg (Table S1, Fig. S3). It should be noted that the TP level in the sediment was a little more than the critical level of 0.6 mg/g for polluted sediments as described by Katsaounos et al., which indicated that the studied river was to a certain extent disturbed by human activities and contamination (Katsaounos et al. 2007). We discovered that the S_TP yearly distribution range is 1.01–1.49, and the total phosphorus pollution level is moderate polluted, using the comprehensive pollution index method based on the sediment pollution level evaluation standard S_TP (Table S2). IP accounts for 67.17–73.14%, with a content of 456.30-666.06 mg/kg, is the main component of TP in sediments (Fig. 3a). This conclusion is congruent with Dongting lake (Wang &Liang 2016) and Jianxi Basin (Ye et al. 2017) in China. In regard to IP, iron/aluminum bonded phosphorus (NaOH-P) is the most abundant component (74.93–89.04%), with a content of 381.13-549.92 mg/kg (Fig. 3a, Fig. S3), indicating that IP is mainly bound to iron and aluminum oxides rather than calcium oxides in FSBR sediments (Peng et al. 2020, Yi et al. 2017). NaOH-P is mainly derived from production and domestic wastewater and, to some extent, is one of the main indicators for determining the source of IP contamination in sediments because it reflects the intensity of bioavailable phosphorus transport associated with anthropogenic contamination of sediments. (Ruban et al. 1999, Wang et al. 2016). Hence, it also indicates that the sediments of FSBR have been seriously contaminated by human beings through the migration of exogenous phosphorus and granular sedimentation in water. Based on the PCoA analysis (Fig. 3b), ANOSIM analysis was conducted to match the profiles of phosphorus forms, the structural composition of phosphorus forms exhibited no distinct differences according to the seasonal factor (ANOSIM, R = 0.167, P = 0.067) (Table S3), indicating that seasonal variations and hydrological conditions probably will not significantly affect phosphorus contamination levels in FSBR sediments (Farmaki et al. 2014). However, it is important to note that the high abundance of NaOH-P and OP in FSBR sediments has potential effects on phosphorus cycling at the sediment-overlying water interface and eutrophication in the water column due to their strong bioavailability under changing external water conditions (Yi et al. 2017).

TP concentration was 332.61-731.81 mg/kg in riparian soils (Table S1, Fig. S3), having IP a major constituent of TP. This is in consistent with Jianxi Basin’s findings (Ye et al. 2017). Although the occurrence level of phosphorus in riparian soils is relatively low as compared to the occurrence of different phosphorus forms in sediments, manifesting sediments are still a crucial area for the occurrence and storage of phosphorus in the aquatic environment. (Young &Ross 2016) remarked that these differences are related to various factors such as acidity, conductivity, redox potential, particle size composition, bacterial activity, pollution source, and other relevant environmental factors related to soil and sediments. However, it is worth noting that OP and NaOH-P with high activity in riparian soils may still be released into the overlying water under alternate wetting and drying conditions (Ruban et al. 1999). The PCoA and ANOSIM analyses were also used to investigate the distribution patterns of phosphorus forms. The structural composition of phosphorus forms was significantly affected by environmental media (ANOSIM, R = 0.931, P = 0.001) (Fig. S2, Table S3). PCoA based on Bray-Curtis distance for phosphorus forms revealed clear separations between the sediment phase and soil phase (Fig. 3b). This again suggests that the environmental behavior of nutrients in aquatic settings is influenced by various environmental media (Ye et al. 2017). Furthermore, the high content of different phosphorus forms in S1 of the Dingnan water inlet area indicates a relatively high level of phosphorus contamination in the sediment and riparian soil of the Dingnan water inlet, and the possible causes of this phenomenon are attributed to the influence of anthropogenic activities caused by the presence of many waterfront agrotourism sites in these two areas (Abdala et al. 2015, Cardoso-Silva et al. 2018b).

3.3 Abundance and properties of DOM

Seasonally composites of DOC, a (350), S_R, and SUVA₂₅₄ determinations may be representative of FSBR DOM and CDOM temporal and geographical distribution (Fig. 4a). The DOC content of reservoir sediments varied from 28.84 to 74.86 mg/L, which was much higher than that of Taihu and Hongze lakes (Chen et al. 2018). The reservoir sediment was investigated as a whole in different periods, and no significant seasonal variation observed (P > 0.05) in the DOM concentration. This indicates that the level of DOM in reservoir sediments is relatively stable and less influenced by external factors. The DOC concentrations in the riparian soil ranged from 17.67 to 46.87 mg/L, with a significant difference (P < 0.05) compared to the sediment, which has been proved to affect DOM assignment status in various different environmental media. It has been demonstrated that riparian soils may carry surface and point source pollutants from further upstream into the water column and sediment, increasing the possibility for DOM transfer between different media (Ye et al. 2017).

Zhou et al., pointed out that the UV-vis absorption coefficient of DOM at a specific wavelength could be utilized to describe the relative properties of DOM (Zhou et al. 2016a). In this study, the extracted state a (350), SUVA₂₅₄, and S_R values in the reservoir sediments ranged from 30.18 to 89.06 m^− 1, 1.64 to 5.33 L·(mg m)⁻¹. and 0.67 to 1.37 (mean: 53.79 m^− 1, 3.54 L·(mg m)⁻¹, and 0.92), respectively. Literature quantified the presence of CDOM using the value of a (350) (Zhang et al. 2009b, Zhou et al. 2016b), Chen et al., confirmed that SUVA₂₅₄ is mostly employed to represent the degree of DOM aromaticity, with a greater value indicating the stronger aromaticity (Chen et al. 2013). Meanwhile, it has been established that S_R has a negative relationship with DOM molecular weight (Helms et al. 2009). Based on ANOSIM analysis we found that the UV spectral parameters composition in this study did not show significant seasonal variations (ANOSIM, R = 0.156, P = 0.098) (Table S2), indicating that the CDOM content, DOM molecular weight and aromatization degree in reservoir sediments were relatively stable and not significantly affected by external factors. In riparian soils, the extracted state a (350), SUVA₂₅₄, and S_R values ranged from 51.12 to 167.74 m^− 1, 3.12 to 11.24 L·(mg m)⁻¹, and 0.50 to 0.72 (mean: 118.59 m^− 1, 7.10 L·(mg m)⁻¹, 0.59), respectively. When compared to the soils of the drawdown area, the sediments showed the following significant trends: a (350) in sediment ˂ a (350) in soil (P < 0.01), SUVA₂₅₄ in sediment ˂ SUVA₂₅₄ in soil (P < 0.01), and S_R in sediment ˃ S_R in soil (P < 0.01). This phenomenon indicated that the level of CDOM occurrence, DOM molecular weight, and aromatization in sediments is lower than that in riparian soils. Boosting microbial physiological activity in soils can facilitate bioturbation and indirectly promote the release of DOM (Zhou et al. 2016a), and the DOC-rich soil possess larger quantities of aromatic compounds (SUVA) (Frank et al. 2000). Moreover, highly aromatic DOM is typically linked with a large molecular weight and complicated structure (Ishii &Boyer 2012).

According to fluorescence spectral characteristics (BIX, HIX, and FI), the sediment indices varied from 0.79 to 0.85, 1.73 to 2.62, and 2.02 to 2,18, respectively, whereas the soil indices ranged from 0.43 to 0.89, 1.56 to 10.8, and 1.90 to 2.55 (Fig. 4b). BIX is an indicator of recently produced CDOM as a result of biological activity (Huguet et al. 2009), and HIX is used to characterize the degree of humification of DOM (Huguet et al. 2009). Similarly, FI can differentiate between microbial and terrestrial sources and is a useful indicator of the aromaticity of the sample (Bowen et al. 2017). In this study, fluorescence spectral index were analyzed by ANOSIM based on Bray-Curtis distance (Permutation test) showing significant variability in the sediment and soil phases (Fig. S2, Table S3). This suggests that the sediment has a strong autochthonous source component, whereas the DOM component of the riparian soil is highly variable and human activities do not bring in too much of the autochthonous source component (S1 and S5). In riparian soils, HIX levels are greater than that in sediments (P < 0.01). Higher HIX values (10–16) are associated with highly humified terrestrial material with high aromaticity and molecular weight, while lower HIX values (< 4) are associated with autochthonous material with low aromaticity and low molecular weight, as shown by the SUVA₂₅₄ and S_R distribution characteristics described above (Fig. 4a). Interestingly, despite the fact that riparian soils had a higher degree of humification than sediments, the fluorescence index revealed that humus in both sediments and riparian soils was mostly produced from biogenic sources (Nebbioso &Piccolo 2013).

3.4 Major fluorescent DOM components

The three fluorescence components (including two humus-like components (C1 and C2) and one protein-like component (C3)) and the maximum values (λ_Ex/ λ_Em) were obtained. EEMs spectrum (AEC) and excitation-emission load (DEF) of the three components obtained by PARAFAC modeling are shown in Fig. 5. The comparisons with other studies are shown in Table S4. The C1 component (Ex/Em = 240,310 nm/405 nm) has two excitation peaks and one emission peak, which is similar to the combination of the A peak and M peak of humus-like substances in traditional classification (Zhang et al. 2009a). Studies show that it mainly comes from the by-products generated in the process of microbial transformation of DOM in inland water bodies, so C1 is defined as microbial humus in this study (Bowen et al. 2017, Zhang et al. 2011). The C2 component (Ex/Em = 270,360 nm/460 nm) also has two excitation peaks and one emission peak, which is similar to the A and C peaks of terrestrial humus (Ishii &Boyer 2012, Milbrandt et al. 2010), and is now uniformly classified as terrestrial humus. Compared with C1, C2 has an obvious red shift in emission wavelength, indicating that C2 has higher aromatization and molecular weight, and its molecular structure is relatively stable(Nie et al. 2016). The C3 component (Ex/Em = 270,360 nm/460 nm) has only one excitation peak and one emission peak, which is defined as the tryptophan-like fluorescent component and is also believed to be increased by polypeptide substances produced by microbial activities, such as human sewage or algae eutrophication. At present, it has been recognized as a characterization index of human pollution activities and microbial activities (Zhou et al. 2016b).

As shown in Fig. 6a, the fluorescence intensities of the C1, C2, and C3 components in the sediment were 0.20–0.36 R.U, 0.24–0.45 R.U, and 0.15–0.25 R.U, respectively. Based on the fluorescence structural composition of the various components, a principal coordinate analysis (PCoA) (Fig. S4) was used at the geographical and temporal scales to rank the sediment and the soil system, respectively. The fluorescence intensity of C1, C2, and C3 components in the sediment did not exhibit significant differences (P > 0.05) over time, and the findings of the one-way ANOSIM test also showed that the structural composition of DOM in the sediment system did not show significant differences (P > 0.05) over time (Table S2). These findings all point to the fact that FDOM in reservoir sediments is relatively stable, implying that reservoir hydrological processes have less influence on FDOM in sediments. The fluorescence intensity of components C1 and C2 was higher at S1, S3, and S5 than at the other two locations (S2 and S4), according to the geographical distribution characteristics (Fig. 6a). The latter is in the reservoir’s open region, while the former is in a canal that is somewhat small. As a result, the narrow channel areas, may exhibit more active microbial activity in sediments and soils, promoting the enhancement of microbial source components (Wang et al. 2014).

The fluorescence intensity of C1 and C3 components (0.18–0.96 R.U and 0.03–0.22 R.U, respectively) was substantially lower (P < 0.01) in the riparian soil compared to the sediment, but for C2 component (0.14–0.36 R.U), it was significantly greater (P < 0.01) in the riparian soil. This means that microbial fluorescence composition in sediment is higher than in soil, and fluorescence composition of terrestrial humus is lower. This might be due to microorganisms in sediments, which are more active in converting fluorescent components than in soils, which is the primary source of terrestrial humus (Huguet et al. 2009). The allocation percentage of fluorescence intensity of each component is displayed in Fig. 6b to further explain the conversion of DOM in different media. In sediments, the C1 and C2 components contribute much more than the C3, and the C2 contributes the most in riparian soils. The greater molecular size and stable structure of the terrestrial humus component in the soil may be the cause for this phenomenon (Jacquin et al. 2017), as well as the increased input of foreign terrestrial DOM from human agricultural operations (Liu et al. 2020). The likelihood of microbial conversion of tryptophan-like components to humic-like components account for the low percentage contribution of soil protein-like fluorescent components (Maqbool et al. 2016). Furthermore, Environmental media had significant effects on the distribution patterns of fluorescence DOM structural composition (ANOSIM, R = 0.868, P = 0.001) (Fig.S2, Table S3), and PCoA based on Bray-Curtis distance for fluorescence DOM structure composition showed obvious separations among the sediment phase and soil phase. Although riparian soils are an essential part of the aquatic environment, their FDOM structural composition differs from that of sediments, and it is probably this distinguishing environmental feature that permits riparian soils to assume a distinctive function in FDOM geochemical activity (Singh et al. 2010).

3.5 Potential influencing mechanism among nitrogen, phosphorus, and DOM

Based on the particle size distribution characteristics and the occurrence levels of TOC, TN and TP in sediments and riparian soils, Pearson's correlation analysis (Fig. S5) revealed that silt had a significant negative correlation with both TOC and TP (R² = -0.67, P < 0.01; R² = -0.52, P < 0.05). Similarly, sand had a significant positive correlation with both TOC and TP (R² = 0.62, P < 0.05; R² = 0.52, P < 0.05), indicating that various particle sizes of sediment play varied roles in TOC and TP buildup, with TOC and TP being more readily adsorbed on sand grains. Finer suspended matter was not deposited in substantial amounts due to water flow energy and erosion, whereas contaminants were deposited concurrently with sand grains through adsorption and co-sedimentation (He et al. 2011). Meanwhile, there was a significant positive correlation between TOC and TN (R² = 0.64, P < 0.01), but no significant correlation between TOC and TP, TN and TP, indicating that the nitrogen pollution in the FSBR sediment may be closely related to the mineralization process of organic matter, and the nitrogen and phosphorus in the sediment may come from different sources(Wen et al. 2019). Sand particles and NaOH-P had a significant positive correlation (R² = 0.71, P < 0.01), indicating that NaOH-P may be mostly adsorbed on sand particles in FSBR sediments. TP, OP, IP, and NaOH-P showed a significant positive correlation with each other (P < 0.01). Because the processes for determining OP, IP, and NaOH-P in sediments are somewhat difficult, it is suggested that the occurrence level of OP, IP, and NaOH-P in sediments of this reservoir region may be quickly assessed by employing TP content (Peng et al. 2020). Unlike the sediment medium, however, both silt and sand in the soil phase exhibited a high link with TOC and each nitrogen and phosphorus morphology, indicating that various particle sizes impact carbon, nitrogen, and phosphorus content and morphological changes in the riparian soil. The close relationship among C, N, and P in riparian soils shows that they may all derive from the same pollution source. External origin originates from diffuse sources (natural, agricultural) or point sources (industrial and household effluents), which are the primary polluting sources of nutrients in soil (Powers et al. 2016).

Figure 7 presents the correlations and PCA among fluorescence intensity of fluorescent components (C1, C2, and C3), DOM optical indices, and nutrient parameters of sediments and soils collected from FSBR. For reservoir sediments (Fig. 7a), SUVA₂₅₄ was found to be strongly negatively associated to S_R, implying that DOM with a high degree of aromaticity was usually contained high molecular weight and complex structure (Feng et al. 2021). As for DOM components, C1 and C2 exhibited significant positive correlation with HIX, while negative correlations between C1 and BIX. Microbial production was one of the origins of microbial humus and humus-like components were likely to result in this relationships with HIX (Feng et al. 2022). Humification of terrestrial humus components contained high molecular weight in the study (DeVilbiss et al. 2016) could also reflect this relationship. There were also significant correlations among the DOM components such as C₁ had a significant positive relationship with C2. This connection might explain how microbial humus components can be converted to terrestrial humus components (microbial synthesis) or terrestrial humus components can be transformed into microbial humus components (microbial degradation) (Feng et al. 2022).

In riparian soils, nutrient parameters (N, P, and their forms) were shown to have a significant positive relationship to S_R (Fig. 7b). This suggests that the smaller molecular weight of DOM was favorable to the presence of N and P, which differs somewhat from the findings of Feng et al., in the sediments of Nansi Lake, and also demonstrates the special habitat pattern of the riparian soils (Feng et al. 2022). Additionally, another investigation revealed that cyanobacterial bloom can lead to an increase in S_R (Chen et al. 2018). Therefore, N and P may affect DOM by providing nutrients to algae. Notably, C3, which represents the tryptophan-like component, had negative correlations with TN and its forms, whereas HIX showed positive correlations. Zhou et al., also reported that eutrophication promoted tyrosine-like component transfer to protein-like components with increased humification and molecular weight (Zhou et al. 2016b). As for DOM components, C1 and C2 exhibited significant positive correlations with HIX, whereas negative correlations with FI and BIX. C3, on the contrary, displayed an inverse relationship with fluorescence spectral indices. This discrepancy might be due to humic-like and tryptophan components (Zeng et al. 2017). C1 and C2 were significantly and positively correlated with a (350) and S_R, but C3 exhibited the opposite correlation. Previous research has found that S_R is usually closely associated with the intake of terrestrial-like humus (Fichot &Benner 2012, Helms et al. 2009, Zhang et al. 2011). Correspondingly, the protein-like tryptophan component was considered a simple substance with lower molecular weight, low humification, and low aromaticity. Thus, the relationship (C3 with optical indices) was in agreement with literature (Feng et al. 2021).

The two principal components identified by the PCA explained 50.23% of the variation in these parameters, with PC1 accounting for 34.14% of the variation (Fig. 7c), emphasizing the tight link in sediments. The negative half-axis of the PC1 axis contains DOM components and characteristics linked to nitrogen and phosphorus, implying that PC1 is negatively connected to carbon, nitrogen, and phosphorus concentrations and relative morphology. C1, C2, and C3 are strongly associated to phosphorus and share a negative PC2 load, but nitrogen has a very high positive PC2 value, indicating that PC2 may be favorably correlated with nitrogen occurrence levels and that nitrogen and phosphorus in the sediment vary. The strong association in riparian soils also corroborated by the PCA conducted between DOM components and nutrient properties (Fig. 7d). The PCA showed two principal factors explained 88.72% of the variation in these parameters, with PC1 accounting for 70.35% of the variation. C1 and C2 are closer to a (350), however C3 is further away, indicating that the protein-like peak has less influence on the CDOM component. However, the humic component’s trend is comparable to the CDOM intensity estimate, which is corroborated by previous literature (Singh et al. 2010). The possible reason is that the DOM in the reservoir area is influenced by agriculture, residential life, and the intensity of exogenous input varies, resulting in differences in fluorescence component changes on the one hand (Liu et al. 2020), and microorganisms can also absorb non-absorbent components while producing absorbent components on the other hand (Nelson et al. 2004). Zhou et al., also found that two humus-like components had the same correlation with a (350), TN, and TP, among other variables (Zhou et al. 2016b). Unlike sediment performance, riparian soils had higher positive PC1 value for C1, C2, nitrogen, and phosphorus, whereas C3 had negative PC1 value. Because C3 represents a protein-like component, it also confirms high level of humification of riparian soil. Nitrogen and phosphorus are strongly associated and jointly occupy a negative PC2 load, indicating that PC2 may be negatively related to nitrogen and phosphorus occurrence levels and that nitrogen and phosphorus have a very strong association in the riparian zone.

At the regional and temporal dimensions, the occurrence levels of the major nutrients in FSBR sediment/riparian soils were investigated separately. Seasonal hydrological processes have little effect on the amounts and structural composition of nitrogen and phosphorus in sediments and soils. The IEF-N was the most abundant kind of TF-N in reservoir sediments, whereas the IMOF-N was the most common type of TF-N in riparian zone soil. IP (NaOH-P), however, was the major component of TP in both reservoir sediments and riparian soils. The occurrence levels of DOM and CDOM, as well as the molecular weight and aromatization degree of DOM in reservoir sediments and riparian soils were all unaffected by seasonal reservoir hydrological processes. The quantities of DOM in the sediment differed from that of riparian soil, whereas the occurrence level of CDOM, the molecular weight of DOM, and the degree of aromatization in the sediment were all significantly lower than that of riparian soil. Microbial-derived humic compounds, terrestrial-derived humic substances, and tryptophan-like component were the three predominant fluorescence components of the study area. The structural composition of DOM components in sediment and soil phases differed significantly, according to PCoA and ANOSIM analyses. These findings, together with correlation and principal component analysis results for various environmental groups, imply that distinct environmental media in sediments/riparian soils influence nutrient and DOM occurrence characteristics and environmental behavior.

Acknowledgements: The authors are grateful for the financial support from the National Natural Science Foundation of China (Grant No. 42007330), and National Science and Technology Major Projects of Water Pollution Control and Management of China (Grant No. 2014ZX07206001).

Conflicts of Interest: The authors declare no conflicts of interest.

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Availability of data and materials

The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.

All data generated or analysed during this study are included in this published article (and its supplementary information files).

Competing interests

The authors declare that they have no competing interests.

Funding

National Natural Science Foundation of China (Grant No. 42007330)

National Science and Technology Major Projects of Water Pollution Control and Management of China (Grant No. 2014ZX07206001).

Authors' contributions

Kangping Cui conceived of the presented idea. Material preparation, data collection and analysis were performed by Yihan Chen. The first draft of the manuscript was written by Shuanggang Hu. Muhammad Hassan commented on previous versions of the manuscript. All authors read and approved the final manuscript.

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Comprehensive study of the occurrence and characteristics of carbon, nitrogen, and phosphorus in sediments and riparian soils of large drinking water reservoir

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Abstract

Figures

1. Introduction

2. Materials And Methods

2.1 Study area and sampling

2.2 Nutrient analysis

2.3 Determination of dissolved organic matter spectrum

2.4 Optical indices and Parallel factor analysis

2.5 Nitrogen and phosphorus risk evaluation

2.6 Data analysis

3. Results And Discussion

3.1 Occurrence and distribution of nitrogen

3.2 Occurrence and distribution of phosphorus

3.3 Abundance and properties of DOM

3.4 Major fluorescent DOM components

3.5 Potential influencing mechanism among nitrogen, phosphorus, and DOM

4. Conclusions

Declarations

References

Supplementary Files

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