Sources and routes from terrestrial exogenous pollutants affect phytoplankton biomass in reservoir bays

Reservoir bays, the boundary of terrestrial and water where water ﬂ uidity slows down and self-puri ﬁ cation ability turn weak, hence they are especially sensitive to terrestrial exogenous pollutants, even resulting in eutrophication. According to N:P, water nutrients types can be divided into N limited, P limited and N þ P limited classes. Phytoplankton biomass is represented by chlorophyll a, which is one of the sensitive indicators of water eutrophication. Comprehensively traced non-point pollution from terrestrial exogenous pollutants (fertilizer, soil release, anthropogenic discharge) to water nutrients that happen in reservoir bays is of great signi ﬁ cance. This paper identi ﬁ ed the dominant environmental variables and nutrients limited types of reservoir bays at storage and discharge periods, constructed partial least squares structural equation model (PLS-SEM) to explore the impacts of terrestrial exogenous pollutants. Results showed that in storage period water contamination mainly came from residential discharge and soil endogenous release, the total contribution rate reached 61%. In discharge period, with the increase of rainfall – runoff erosion, the explanatory ability of land use, topography and landscape pattern to water quality increased, up to 58%. The dominant nutrients limited types of reservoir bays were P limited (35% – 47%) and N þ P limited (35% – 59%) at both stages, N limited situations less than 20% and generally appeared in storage period. Whatever the nutrients limited type was, phosphorus always had a higher effect on phytoplankton biomass. In N limited situation, nitrogen mainly from soil release (total effect ¼ 0.6) and phosphorus from fertilizer (total effect ¼ 0.22) and soil release (total effect ¼ 0.17). In P limited situation, all three sources had almost high effects on nitrogen, phosphorus, and phytoplankton biomass. In N þ P limited situation, the anthropogenic discharge was the main source of nutrients and the primary threaten factor for phytoplankton biomass. The approaches employed in this study could be generalized to the other basin and the results were signi ﬁ cant to early warning and controlling water eutrophication. (cid:129) The effects and contributes of fertilizer, soil release and anthropogenic discharge to water nutrients and phytoplankton biomass were calculated.

• The effects and contributes of fertilizer, soil release and anthropogenic discharge to water nutrients and phytoplankton biomass were calculated.

INTRODUCTION
Hydraulic engineering has been greatly prevented and alleviated nature disasters caused by floods and droughts and plays a vital role in water supply, irrigation, power generation, etc (Chen et al. ). Until now there have been more than 50,000 dams height over 15 meters all over the world (Lehner et al. ), however, reservoir operation has changed the natural hydraulic mechanism of the river even water connectivity is prevented, which caused water self-purification capacity to decline and river ecological environment changed (Gao et al. ; Li et al. ; Xiang et al. ). These changes will further threaten water quality.
Reservoir bays, semi-enclosed water bodies at terrestrial and water boundaries, affected by its morphological characteristics, water mobility turned down in this place. Because they adjoin with land, make they become the most sensitive places to overland pollutants (Li et al. ). There have been quite a lot of reports of water eutrophication events in reservoir bays (Yang et al. ; Chuo et al. ; Huang et al. ) which have aroused extensive concern. What caused the nature of eutrophication in water is phytoplankton blooms, therefore, the key to controlling eutrophication is to inhibit the growth of phytoplankton in water.
Studies on water eutrophication showed that the input of nitrogen, phosphorus, and other nutrients was the vital inducement for algae outbreak and water quality deterioration (Paerl et al. ; Mamun et al. ). According to Liebig's law of the minimum, the required nutrients for plant growth were provided by the external environment, if the amount of a certain nutrient approaches the lower bound, then this nutrient was the limiting factor for plant growth (Chen et al. ). The ratio of N:P could serve as an index that represents the nutrient limitation for phytoplankton growth when compared with the average composition of nutrients assimilated in algae (C106:N16: P1) (Fujimoto et al. ). Early experimental research established that a high concentration of P and a low N:P supply ratio (<29:1) were favorable for the production of algae blooms (Smith ). There had been some successful practices that reducing phosphorus (P) inputs based on the premise that P universally limits primary productivity but not all (Elser et al. ; Lewis et al. ). The theory they based on was that nitrogen flow into the water could be degraded to gas form through denitrification and other biochemical processes, then circulated at the water-gas interface. However, phosphorus had no gas form in nature, so it was difficult for phosphorus to be degraded in the water. As the water flow slowed down, phosphorus was deposited in the water and became a part of internal pollution. Therefore, the accumulation rate of phosphorus in the water was higher than nitrogen. Many traditional views thought that water eutrophication could only control the input of phosphorus, thus ignoring the limitation of nitrogen (Schindler et al. ). Lately, researchers in China, America, Africa, and Europe had been discovered that many lakes exhibit varying nutrient limiting and cycling patterns, including periods of P or N limitation, as well as periods of N and P act in concert to facilitate biomass pro- Apart from the artificially added nutrients, soil inherent contains nitrogen, phosphorus, organic matter, and so on nutrients, which will also increase the contamination flow into the water in dissolved or particle states (Tong & Chen Human construct reservoir because of its indispensable roles in water resource supply, regulation and storage flood, agriculture irrigation, entertainment and so on, we should discover the hidden risk of non-pollution immediately and make scientific guidelines. In this work, we choose reservoir bays as the study area for its special morphological characteristics which made it the most sensitive place for the convergence of non-point pollution. Based on the priori causal path of terrestrial exogenous inputwater nutrients concentrationwater phytoplankton biomass, structural equation model were built to identify non-point pollution sources form terrestrial exogenous pollutants to water nutrients in both reservoir storage period and discharge period. The major objectives of this study were: (i) to identify the temporal and spatial distribution of chlorophyll-a concentration in storage and discharge periods of reservoir bays, (ii) to extract the dominant environmental variables that mainly contribute to water contamination, (iii) to elaborate the influence paths and effects across terrestrial exogenous input-water nutrientsphytoplankton biomass in DanJiang-Kou reservoir bays. The results will help researchers and local decision-makers to understand the source and dynamics of Chl a, therefore, it's essential to control the input of nonpoint pollution and eutrophication effectively. After the dam was raised, the ecological environment around the reservoir greatly changed, and water quality became an important concern for local and national policymakers. It is because the critical role of water supply and the high sensitivity for water quality security that we choose the DJK reservoir as a representive place to study the causes and sources of water quality variance.

Study area
The elevation of the study area ranges from 0 to 957 m, high and steep in the northwest, low and gentle in the southeast. This area has a typical subtropical monsoon climate, rain and hot during the same period. The average yearly temperature is À16 C, and the average annual precipitation between 800 and 1,000 mm, most of which falls during the monsoon season (June to October), thus lead to higher intensity rainfall and overland flow afflux into the reservoir.
According to the hydrometeorological rules and flood control requirements, the reservoir usually discharged water from June to October and stored water from May to November of the following year. Based on the regulation of reservoir operation, May was deemed to be the storage period, September was deemed to be the discharge period.
According to the Chinese soil classification system, the major soil types include yellow-brown soil, limestone soils and purple soil (National Soil Survey Office ), which correspond respectively to Alfisols, Entisols and Entisols in the USA Soil Taxonomy (Soil Survey Staff ). The main land-use type in this watershed is forest, nearly 70%.
Farmland and residential areas are concentrated along the river. The major crops are corn (Zea mays L.) and wheat (Triticum aestivum L.).

Stream water sampling and analysis
Reservoir bays were divided based on the digital elevation model (DEM) with a resolution of 25 m by 25 m. Using Geography Information System (GIS) technology practiced in hydrological analysis module, according to the threshold of the catchment area 500 ha to extract bay catchment areas.
Follow the rules of homogeneity and universality, we choose 62 reservoir bays which overall considered altitude, slope and land use types.
We sampled water at reservoir bays from 2015 to 2019 in May (storage period) and September (discharge period).
Laid three sample points at every bay, respectively boundary, center and mouth, the distance between points over 200 m. Water temperature(Temp), pH, dissolved oxygen (DO), turbidity (NTU) and the concentration of Chl a were measured in situ using a YSI EXO2 (YSI Inc., Yellow Springs, Ohio, USA) water quality multiparameter analyzer (Li et al. ), other water quality indexes were tested at the laboratory. The concentration of the total nitrogen (TN) was determined using the method of Alkaline potassium persulfate digestion -ultraviolet spectrophotometry (CSEPB ).
The concentration of total phosphorus (TP) was tested by ammonium molybdate spectrophotometry (CSEPB ).
The Nitrate nitrogen (NO 3 -N) and ammoniacal nitrogen (NH 4 -N) concentration were measured by AA3 flow analyzer (FLAstar 5,000 Analyzer). We collected water 10 m away from the shore, depth between 0 and 20 cm, then filled it into a 500 mm polythene plastic bottle, add H 2 SO 4 until pH less than 2, cold storage at 2-5 C, analyze within 24 hours. The total water quality indexes and analysis methods were shown in Table 1.

Environmental variables
The primary data used in this study included Digital export coefficient (the loads of TN or TP that were exported from each source per unit time, per unit area, in reservoir bays) from individual agricultural sources were using the output coefficient method to calculate (Li ) ( Table 2).
The export coefficient (E i ) describes the pollutant load exported from each land use type per unit area per unit time (t/km 2 ·yr) in the catchment. where L is the loss of nutrients (t), A i is the area of the catchment occupied by land-use type i (km 2 ), or the number of livestock type i, or people, I i is the input of nutrients to source i (t), and P is the input of nutrients from precipitation (t).
Landscape variables were obtained from the land-use map calculated by the software FRAGSTATS 4.1, which is widely accepted for landscape metrics quantification  Table 3.

Statistical analysis
To     In structural model (Inner model), the linear relationships between the latent variables ξ j is written as: β ji is the route coefficients of the latent variables ξ j .
Where ζ j is a random error.
In measurement model (Outer model), each latent (unobservable) ξ j variable is described by a linear combination of the manifest variable x jh :

Dominant environmental variables that mainly influence water quality in reservoir bays
Using redundancy analysis to perform multivariant regression should eliminate the influence of redundancy    Table 3. **p < 0.01, *p < 0.05; p-value represents the significance level, R-value represents the percentage of variance explained by the environment variable.

The sources and effects of nonpoint pollution in reservoir bays
The well-established results for nutrients limited study in inland hydrostatic water indicated that when the ratio of N:P concentration is higher than 23, the limiting nutrient referred to P, when the ratio of N:P concentration is lower than 9 that was tend to N limited, besides, the nutrients were N þ P limited (Paerl et al. ). According to this prior classify criteria, the nutrients limited level could be divided into N-limited, P-limited and N þ P limited ( Figure 7). Different nutrients limited types determine the kinds and amount of nutrients available to phytoplankton, which caused the difference in the biochemical process  between phytoplankton and water environmental factors.
Therefore, it is necessary to establish a path analysis model based on the nutrients limited classes from the sources of nitrogen and phosphorus.
The results of nutrients limited classification during both periods (Figure 7) showed that the most commonly distributed types were P-limited (35%-47%) and N þ P limited (35%-59%), while N-limited situations appeared quite rarely, accounted for less than 20%. In the storage period,  Table 5.
came from fertilizer, soil release and artificial discharge. N and P fertilizer mainly from dry land, paddy field and garden land uses. The soil release of N was related to the STN, SNH 4 , SNO 3 . While, the soil release of P was considered to STP, SAP. The artificial discharge of N and P was concerned with rural and urban land uses (Hua et al. ). PLS-SEM were constructed based on N limited, P limited, N þ P limited classes respectively . The total effect, direct effect and indirect effect of the results PLS-SEM were shown in Table 6.
The results of PLS-SEM ( Figure 9) showed that whatever the nutrients limited classes were, the higher effect on phytoplankton biomass was all phosphorus salt. This phenomenon was especially obvious when N and P joint limited (Effect of PS ¼ 0.62). While the effect of nitrogen salt was higher than the other nutrients limited types if it was N-limited.
The results of fertilizer, soil release, anthropogenic discharge effects on nitrogen salt, phosphorus salt and phytoplankton biomass were distinctive among three nutrients limited types (Figure 9). In N limited reservoir bays, nitrogen salt mainly came from soil release (total effect ¼ 0.6) and nitrogen fertilizer (total effect ¼ 0.43), of which the indirect effect from fertilizer to soil release was 0.3.
The sources of phosphorus salt showed a subtle difference that the effect of fertilizer (total effect ¼ 0.22) was a little  were that phosphorus always affected higher on phytoplankton biomass, whatever the nutrients limited types were. However, it was also necessary to take measures to control both sources of nutrients. The prevention of eutrophication should emphasize controlling fertilization and anthropogenic discharge first, then the transfer of the nutrients from the overland flow and infiltration to soil and water cannot be neglected also. This study hoped to propose a new solution to the research on the sources and potential risk warning of eutrophication in reservoirs and expect to provide scientific guidance for the controlling of non-point pollution.
PLS-SEM provides an effective solution to assess the coupled relationships between predictors and water quality characteristics. Nevertheless, for promoting the knowledge of the sources and routes of water nutrients from terrestrial exogenous pollutants that affecting water pollution, the PLS-SEM used in this study could be improved by considering more environmental factors and the sources of pollutants such as the pollution loads from the livestock production in driving water quality changes on different temporal and spatial scales. We expect that the methods presented inthis paper will be useful for hydroecologist wishing to apply PLS-SEM.