Abstract

The distribution of nutrients and chlorophyll-a (Chl-a) in reservoir could provide data for decision making. In-situ measurements were performed in April, June, August and October of 2013 in the Panjiakou, a channel reservoir located in Hebei Province of China. Sampling points of total phosphorus (TP) and total nitrogen (TN) were set at 0.5 m under water surface, 1/2 water depth and near the bottom, respectively, while Chl-a were set according to thermocline. The spatiotemporal variations of TN, TP and Chl-a were studied using Inverse Distance Weighted (IDW) method, and the influence of nutrients on Chl-a was examined using an empirical method. Generally, the peak values of both TN and TP concentrations appeared in October. The TN concentration in the upstream was higher than that in the downstream, while the TP concentration was opposite. High nutrients concentration or low nitrogen to phosphorus ratio (NPR) promoted the increase of Chl-a concentration. However, phosphorus was the limiting element to Chl-a as it had placed greater contribution to NPR than nitrogen. Therefore, limiting phosphorus input is important to improve reservoir water quality.

INTRODUCTION

The ratio of nitrogen and phosphorus provide necessary material base for the normal operation of the reservoir ecosystem (Akinbile et al. 2013; Meng et al. 2015). Research on nitrogen and phosphorus, especially in reservoir management, have shown the extensive concerns in the ecological community (Jacoby & Frazer 2009; Schindler & Heck 2009; Schelske 2009). It is necessary to study the nutrient concentrations and its relationship with the ecological indicators, which has a guiding significance to fisheries utilization and water environmental protection. Chl-a is a direct indicator used to evaluate the ecological state of water body, such as the algae blooms that degrade the water quality in lakes, reservoirs and estuaries (Devries et al. 2012; Park et al. 2015; Wang et al. 2016), e.g. Chl-a concentration over 65.0 μg/L can cause eutrophication (Chen et al. 2008).

Previous research have proved that the algae bloom is tightly related with nutrients loading of the water body (Zhang et al. 2011; Kiedrzyńska et al. 2014). It has been widely accepted that the phosphorus is the limiting element in most of the major lakes (Monbet et al. 2009; Xia et al. 2014). Phosphorus triggers eutrophication and threat the aquatic system (Yang et al. 2014; Santos et al. 2015) as it shows good agreement with phytoplankton concentration. Nitrogen, often profound in water body, could contaminate the environment and jeopardize the health of human beings as well (Okabe et al. 2002; Shin et al. 2004). To identify the surface water bodies and protect them from eutrophication, many countries have initiated their own guidelines to classify the nutrient ecoregions and water quality levels based on total phosphorus (TP) and total nitrogen (TN) concentrations (Cubas et al. 2014; Xu et al. 2014). For instance, the US guideline announced that nitrogen concentration should not exceed 0.1 mg/L in lakes and reservoirs, and phosphorus concentration should not exceed 0.02 mg/L, while China announced that the water body in class iii should have nitrogen and phosphorus concentration under 1.0 mg/L and 0.05 mg/L in lakes and reservoirs, respectively (CMEP 2002; USEPA 2002).

Panjiakou Reservoir, one of the water sources of Tianjin and Tangshan cities and the major fishery of Beijing, is facing severe nutrient loading from the upstream river basin. The water body is vulnerable to nitrogen and phosphorus pollution. However, few previous studies have studied the spatiotemporal variation in the reservoir domain (Song et al. 2012; Çelik 2013). Even fewer have conducted field investigation of the nutrients and chlorophyll-a (Chl-a) in a stratified reservoir (Komatsu et al. 2006; León et al. 2016). Historical measurement in the reservoir domain could provide direct support for decision making. In this study, monitoring was conducted in the Panjiakou reservoir. Longitudinal and vertical variation of nutrients and Chl-a were also studied based on field measurements. Moreover, the correlation of the nutrients and Chl-a concentration was examined by using the deviation rate method.

The objectives of this study were to: (i) identify the spatiotemporal variation of nutrients and Chl-a concentration in reservoir domain, and the factors influencing spatiotemporal distribution; (ii) examine the relationship between nutrients and Chl-a and identify the limiting elements of Chl-a.

MATERIALS AND METHODS

Study area

The Panjiakou Reservoir, located in Hebei Province of northern China, is a main part of the ‘Project to Divert Luanhe River to Tianjin’, which aims to solve water shortage in Tianjin and Tangshan cities. With this project, water supply to industry and residents are well secured. The catchment area of the reservoir is 33,700 km2, accounting for 75% of the Luanhe basin, which is part of the Haihe basin (the fourth largest basin in China) (Figure 1).

Figure 1

Location of Panjiakou Reservoir and sampling sites.

Figure 1

Location of Panjiakou Reservoir and sampling sites.

The reservoir, built in 1979, is a multi-year regulating storage reservoir. The primary purpose of Panjiakou reservoir is to provide industrial, agricultural and municipal water supply for Tianjin and Tangshan. However, there have been higher nutrient contents in the water body of the reservoir in recent years because of aquaculture (fish cages), leading to increasingly frequent algal bloom and fish death in some regions.

Sampling collection and analysis

Four in-situ measurements were performed in April, June, August and October of 2013, which represent spring, summer and autumn, respectively. Summer is a heavy rainy season, so two months were selected: June (without heavy rainfall) and August (after heavy rainfall). Winter is excluded for the reservoir is frozen from November to March. Because little pollution is from tributaries, water samples were collected from five sections in the trunk stream, which were set with the distances of 30 km, 26 km, 15 km, 6 km and 0.5 km to the dam, respectively (Figure 1). According to regulation for water environmental monitoring SL 219-2013 (Chinese), the location of samples are shown in Table 1.

Table 1

Location of sampling points

Monitoring indexTN & TPChl-a & WT
Location of sampling points 0.5 m under water surface A vertical intervals of 2 to 3 m, while interval was shortened to 1 to 2 m where water temperature fluctuates drastically 
1/2 water depth 
near the bottom of the reservoir 
Monitoring indexTN & TPChl-a & WT
Location of sampling points 0.5 m under water surface A vertical intervals of 2 to 3 m, while interval was shortened to 1 to 2 m where water temperature fluctuates drastically 
1/2 water depth 
near the bottom of the reservoir 

In the field measurements, the altitude and longitude of the sampling points were measured by GPS. The collected water samples were immediately stored, adding sulfuric acid with pH value between 1 and 2, and taken back to the laboratory for analysis at the same day. The ultraviolet spectrophotometry method was adopted to measure TN concentrations with 7501 ultraviolet spectrophotometer, while the ammonium molybdate spectrophotometric method was used to measure the TP with T6 Xinrui-vis spectrophotometer (CMEP 2009). Chl-a was tested on site with the 6600V2 portable water quality monitoring instrument (Storey et al. 2011). Sampling points were set according to water depths and the thermocline, located at the middle layer where water temperature (WT) fluctuates drastically, so the number of vertical water sampling points of Chl-a and WT at each section in different periods is diverse (Table 2).

Table 2

Number of sampling points at each section in different months

Sampling timePuhekou
Jiajiaan
Yanziyu
Panjiakou
Baqian
TN & TPChl-a & WTTN & TPChl-a & WTTN & TPChl-a & WTTN & TPChl-a & WTTN & TPChl-a & WT
April 2013 11 11 14 13 10 
June 2013 12 13 15 14 15 
August 2013 18 18 18 18 18 
October 2013 16 15 14 15 14 
Sampling timePuhekou
Jiajiaan
Yanziyu
Panjiakou
Baqian
TN & TPChl-a & WTTN & TPChl-a & WTTN & TPChl-a & WTTN & TPChl-a & WTTN & TPChl-a & WT
April 2013 11 11 14 13 10 
June 2013 12 13 15 14 15 
August 2013 18 18 18 18 18 
October 2013 16 15 14 15 14 

Spatial interpolation and deviation rate method

Inverse Distance Weighted (IDW) was applied to execute spatial interpolation. The equation is applied as:  
formula
(1)
where z0 is the values of interpolation points, zi means the values of sampling points, di stands for the distance between the sampling points and interpolation points (m), n means the number of sampling points.
To assess the impacts of nutrients on Chl-a, an empirical method was implemented. It can be calculated as:  
formula
(2)
where Si,j is deviation rate to annual average value of TN (TP or Chl-a), Ci,j refers to the average concentration of TN (TP or Chl-a) or the value of NPR (nitrogen to phosphorus ratio) at layer i and section j (Figure 2(a)), and represents the annual average concentration of TN (TP or Chl-a) or the value of NPR. The annual average concentration of TN and TP are 4.5 mg/L and 0.04 mg/L, and the annual average concentration of Chl-a is 12.93 μg/L (Wu et al. 2013).
Figure 2

(a) Schematic diagram of deviation rate to annual average value calculation; (b) statistical area of deviation rate to annual average value. Please refer to the online version of this paper to see the figure in colour: http://dx.doi.org/10.2166/ws.2017.189.

Figure 2

(a) Schematic diagram of deviation rate to annual average value calculation; (b) statistical area of deviation rate to annual average value. Please refer to the online version of this paper to see the figure in colour: http://dx.doi.org/10.2166/ws.2017.189.

To analyze the relationship between Chl-a and nutrients, statistical analysis of Si,j were conducted at each layer. Coordinates was divided into four parts by horizontal axis and vertical axis (Figure 2(b)). The value in area S1 (red points) is positive, which means the concentration is beyond the annual average. In this area, high TN (TP or NPR) concentration has promoted the increase of Chl-a concentration. In area S3 (red points), Chl-a concentration is lower than the annual average, which means that Chl-a concentration is at a low level if TN (TP or NPR) concentration is low. In area S2 (blue points), low TN (TP or NPR) concentration is good for the increase of Chl-a concentration, and high TN (TP or NPR) concentration in area S4 (blue points) has a limit to Chl-a concentration.

RESULTS AND DISCUSSION

Temperature stratification characteristics

The water temperature varied from 0.71 to 23.17 °C, and the mean temperature recorded was 10.04 °C. The maximum and minimum water temperature appeared in August 2013 at the upper layer of Jiajiaan section and, in April 2013, at the lower layer of Yanziyu section, respectively. The monitoring water temperature in each month were similar at each section within one layer. Water temperature showed little variation longitudinally.

However, vertical differences were significant based on the interpolation of water temperature in the reservoir domain (Figure 3). Results showed that, despite the differences in water depth, in every monitoring month, the vertical temperature is stratified at various levels. Therefore, we divided the reservoir into three layers top down on the basis of the location of thermocline (Figure 2). Taking an example of Puhekou section, the largest temperature difference between the upper layer and the lower layer reached 19.62 °C in August 2013. The interfaces between these three layers were at 14 m and 20 m below the water surface, respectively. The least difference was 8.12 °C in April 2013. The depths of interfaces were located at 10 m and 16 m at Puhekou section in April, respectively.

Figure 3

Vertical distribution of water temperature.

Figure 3

Vertical distribution of water temperature.

Spatiotemporal variation of nutrients and Chl-a and the reasons

Temporal variation of nutrients and Chl-a are shown in Table 3. The peak and bottom values of TN occurred in October at the lower layer of Puhekou section and the middle layer of Baqian section, respectively. The maximum and minimum value of TP were detected in October at lower layer of Baqian section and in June at lower layer of Puhekou section, respectively. Generally, the peak values of TN and TP concentrations both appeared in October. The reason may be that in October, the precipitation declined, resulting in less water supplement, so the outside disturbance was relatively small. Coupled with the poor flow ability of the water body, TN and TP concentration in October were generally higher than the other months. The concentrations of Chl-a were 1.60 to 54.63 μg /L, with an average level of 13.14 μg/L. Generally, the highest concentration of Chl-a appeared in April, for the reason that in early spring, water temperature in Panjiakou reservoir was low, with the range below 10 °C, which was not conducive to the growth of algae. With the increase of temperature, water temperature in April approached the optimum growth temperature of algae, which made Chl-a concentration maintain in a higher level.

Table 3

Statistics of nutrients and Chl-a during the monitoring period

VariablesMaximum
Minimum
Average
ValueTimeLocationValueTimeLocation
TNa 7.16 October 2013 lower layer, Puhekou section 3.31 October 2013 middle layer, Baqian section 5.33 
TPa 0.189 October 2013 lower layer, Baqian section 0.033 June 2013 lower layer, Puhekou section 0.079 
NPRa 176.09 August 2013 middle layer, Puhekou section 19.48 October 2013 lower layer, Baqian section 82.71 
Chl-aa 54.63 April 2013 upper layer, Puhekou section 1.60 June 2013 lower layer, Panjiakou section 13.14 
VariablesMaximum
Minimum
Average
ValueTimeLocationValueTimeLocation
TNa 7.16 October 2013 lower layer, Puhekou section 3.31 October 2013 middle layer, Baqian section 5.33 
TPa 0.189 October 2013 lower layer, Baqian section 0.033 June 2013 lower layer, Puhekou section 0.079 
NPRa 176.09 August 2013 middle layer, Puhekou section 19.48 October 2013 lower layer, Baqian section 82.71 
Chl-aa 54.63 April 2013 upper layer, Puhekou section 1.60 June 2013 lower layer, Panjiakou section 13.14 

aThe units of TN, TP, Chl-a are mg/L, mg/L, μg/L, respectively. NPR is a dimensionless index.

The spatial distribution characteristics of nutrients and Chl-a was significant (Figure 4). TN showed great variation between upstream and downstream of the reservoir, with the upstream higher than the downstream. No significant vertical variation was detected. Generally, high concentration of TN mainly appeared in the Puhekou section. Field survey indicated that cage culture was on the rise at this region in the late 1980s. A large amount of residual feed, organic fertilizer and fish waste were continuously deposited at the bottom of reservoir because they could not be decomposed in a timely manner. Low oxygen concentration at the bottom of the water body made sediment decompose under an anaerobic condition, producing large amounts of reducing substances. The process continuously releases nitrogen to water, increasing the TN concentration in the water body.

Figure 4

Spatial distribution of TN (a), TP (b), NPR (c) and Chl-a (d).

Figure 4

Spatial distribution of TN (a), TP (b), NPR (c) and Chl-a (d).

The concentration of TP appeared higher in downstream than that of upstream. Meanwhile, litter vertical variation were shown. The NPR gradually decreased from the upstream to downstream. Generally, high TP concentration were mainly concentrated in the downstream Baqian section, while low TP concentration was in the upstream. The main reason was that soil erosion was serious in the upstream, and the center of reservoir sedimentation gravity was from a distance of 48 km to 28 km away from the dam site between 1991 and 2005 (Jiang et al. 1997). Now the gravity was mainly concentrated between Yanziyu and Jiajiaan section. The adsorption of large amounts of sediment on phosphorus made TP concentration in the upstream at a low level.

Chl-a showed different pictures spatially. Significant vertical stratification was detected. Vertical stratification seemed to overweigh the longitudinal distribution. Generally, results showed that the Chl-a aggregated in the upper layer of the water body. For the reason that photosynthesis in the upper layer was obvious, and coupled with the great density of algae, the concentration of Chl-a was high. However, water body under the upper layer lacked direct sunlight, and the density of algae was small. Under the condition of shading, the speed of conversion from Chl-a to Chl-b accelerated, which declined the content of Chl-a. The reason for the low concentration of Chl-a in the upper layer in August was that concentration was measured after a heavy rainfall, making flow velocity and flow rate of Panjiakou reservoir significantly increase, and the interaction between water masses improved.

Possible influences of nutrients on Chl-a

Possible influences of nutrients on Chl-a were examined based on Equation (2). Given that the Chl-a shared good vertical stratification characteristics with water temperature, it is necessary to discuss the relationship of nutrients and Chl-a at various water temperature conditions (Figures 3 and 4). Additionally, since the phytoplankton usually aggregates just underneath or drift on the water surface, the upper layer contributed to the majority of the Chl-a than that of the middle and lower layer (Du et al. 2011a). Concentration variation rate of Chl-a between two adjacent sections was also calculated to illustrate the change of Chl-a concentration (Table 4). Results showed that in the middle and lower layers, variation rate of Chl-a changed from −33.9% to 35.5%. In contrast, the variation rate of Chl-a in the upper layer varied from −64.6% to 173.2%, which is greater than the other two layers. This may be because the upper layer received more sunlight and nitrogen stress than the other two layers (et al. 2015).

Table 4

Concentration variation rate of Chl-a between adjacent sections

Sampling timeLayersPuhekou-JiajiaanJiajiaan-YanziyuYanziyu-PanjiakouPanjiakou-Baqian
April 2013 upper layer −64.6% 170.2% −23.0% 6.7% 
middle layer 35.5% 10.4% −33.6% −5.2% 
low layer −33.9% −13.2% −21.1% 10.8% 
June 2013 upper layer 173.2% −12.5% 6.8% 35.0% 
middle layer 14.7% −7.4% −11.1% 15.2% 
low layer 24.4% −14.2% −15.0% 3.7% 
August 2013 upper layer 2.3% −12.5% −17.2% −13.7% 
middle layer −2.8% 1.8% −4.9% −2.7% 
low layer 3.2% −0.5% 0.7% 0.3% 
October 2013 upper layer −55.8% −28.9% −4.1% 2.9% 
middle layer −26.2% −16.5% −8.2% −8.4% 
low layer 2.4% −25.4% −9.9% 8.1% 
Sampling timeLayersPuhekou-JiajiaanJiajiaan-YanziyuYanziyu-PanjiakouPanjiakou-Baqian
April 2013 upper layer −64.6% 170.2% −23.0% 6.7% 
middle layer 35.5% 10.4% −33.6% −5.2% 
low layer −33.9% −13.2% −21.1% 10.8% 
June 2013 upper layer 173.2% −12.5% 6.8% 35.0% 
middle layer 14.7% −7.4% −11.1% 15.2% 
low layer 24.4% −14.2% −15.0% 3.7% 
August 2013 upper layer 2.3% −12.5% −17.2% −13.7% 
middle layer −2.8% 1.8% −4.9% −2.7% 
low layer 3.2% −0.5% 0.7% 0.3% 
October 2013 upper layer −55.8% −28.9% −4.1% 2.9% 
middle layer −26.2% −16.5% −8.2% −8.4% 
low layer 2.4% −25.4% −9.9% 8.1% 

Therefore, the relationship of the deviation rates was focused on the upper layer in this study. Statistical results have been summarized to illustrate the relationship of the deviation rates between nutrients and Chl-a (Figure 5). To get a better understanding of the meaning of each quadrant, a schematic was drawn in this study (Figure 5(a)). Taking an example of TN, area S1 represents that TN concentration exceeds the annual average value, while Chl-a concentration is also over the annual average value. In this area, the growth of TN concentration plays an important role in promoting the increasing of Chl-a concentration. Area S2 stands for TN concentration below the annual average value, while Chl-a concentration is over the annual average value. In this area, the decrease of TN concentration leads to an increase of Chl-a concentration. In contrast, in area S4 TN concentration is over the annual average value, while Chl-a concentration is below the annual average value, which represents that the increase of TN concentration causes a decrease of Chl-a concentration. S3 quadrant refers to the Chl-a concentration at a low level in the condition of low TN concentration. Therefore, it can be deduced that low TN concentration would result in the decrease of Chl-a concentration.

Figure 5

Relationship between TN, TP, NPR and Chl-a in the upper layer. Please refer to the online version of this paper to see the figure in colour: http://dx.doi.org/10.2166/ws.2017.189.

Figure 5

Relationship between TN, TP, NPR and Chl-a in the upper layer. Please refer to the online version of this paper to see the figure in colour: http://dx.doi.org/10.2166/ws.2017.189.

The percentage of points falling at each area division in the upper layer was counted to study the relationship of nutrients and Chl-a (Table 5). Results showed that more than 50% of the points fell into the region S1. This indicated that Chl-a concentration is more likely to increase with the increase of TN concentration in the upper layer; those 62.50% of all the points fell into the region S1, which showed that TP also presented fertilizing effects on Chl-a. Besides, other points falling into the area S4 in the graph of TP and Chl-a implied that negative correlation existed between Chl-a and TP concentrations in this range. However, these points just accounted for 37.5%, which was a minor proportion of the total. It can also be discovered that there were no points falling into areas S2 and S3, showing TP concentration was too large. This may be due to the recession flow from irrigation and aquaculture this year; the plot of NPR and Chl-a showed that 56.25% of the total points fell into the region S2, indicating that Chl-a concentration was at a high level in the condition of low NPR concentration. This indicated that the phytoplankton tended to grow at a low NPR condition. If the concentration of TN and TP were larger than the average value, increasing TP concentration and reducing TN concentration could trigger the algae growth. In addition, the increase of TN concentration could lead to the increase of Chl-a and TP concentrations. To reduce the value of NPR and increase Chl-a concentration, TP concentration needs to increase more quickly than the growth rate of TN concentration. Therefore, we deduce that phosphorus may be significantly profound than the average level. The phosphorus tends to be the limiting elements as it places greater contribution to NPR comparing with nitrogen.

Table 5

Comparison of the percentage of points falling at each region in the upper layer

RelationshipsUpper layer
S1S3S1 & S3S2S4S2 & S4
Chl-a∼TN 50.00% 18.75% 68.75% 12.50% 18.75% 31.25% 
Chl-a∼TP 62.50% 0.00% 62.50% 0.00% 37.50% 37.50% 
Chl-a∼NPR 6.25% 37.50% 43.75% 56.25% 0.00% 56.25% 
RelationshipsUpper layer
S1S3S1 & S3S2S4S2 & S4
Chl-a∼TN 50.00% 18.75% 68.75% 12.50% 18.75% 31.25% 
Chl-a∼TP 62.50% 0.00% 62.50% 0.00% 37.50% 37.50% 
Chl-a∼NPR 6.25% 37.50% 43.75% 56.25% 0.00% 56.25% 

CONCLUSIONS

In this study, significant spatiotemporal variation have been detected. Generally, the peak values of TN and TP both appeared in October. The maximum Chl-a concentration was seen in April, while the minimum was in June. Spatially, the upstream showed large value of both TN and NPR than that of the downstream, while the value of TP showed larger concentration at the downstream than that of the upstream. Both the nutrients and the NPR did not show significant stratification characteristics vertically. However, vertical stratification were detected in Chl-a. We deduced that the vertical distribution of Chl-a was significantly affected by water temperature. The upper layer aggregated the majority of the phytoplankton, leading to higher value in this layer than the beneath layers.

An empirical method based on deviation rate to annual average value was implemented to study the impacts of nutrients on Chl-a in the upper layer. Both the nitrogen and phosphorus showed fertilizing effects on Chl-a. However, the phosphorus tends to be the restrained elements as it places greater contribution to NPR comparing with nitrogen. Some interesting findings can also prove this conclusion. For instance, in Figure 5(c), 62.50% of the total points (red points) falling into area S1 indicated that the growth of TP concentration plays an important role in promoting the increasing of Chl-a concentration. By coincidence, 56.25% of them (blue points) fell into area S2 in the graph of NPR and Chl-a (Figure 5(d)). In this quadrant (S2), the decrease of NPR value led to an increase of Chl-a concentration, which implied that the growth of phosphorus made great contributions to the decrease of NPR value. The phosphorus was regarded as the main restrictive factor of controlling the growth of algae. To control the Chl-a concentration in reservoir, it is of vital importance to increase the NPR in the upper layer by limiting the phosphorus input, which is an effective measure to improve water quality.

However, there exist some deficiencies in this study, which requires more research into this field. In the further study, it should be considered that reducing how much phosphorus could improve water quality in reservoir using sufficient data. Maybe one good way to do that is to establish graphs between phosphorus concentration (or NPR value) and Chl-a concentration. These graphs can be established to analyze the NPR threshold value of algae in water quality control, by determining the critical value of Chl-a concentration.

ACKNOWLEDGEMENTS

This work was supported by the National Natural Science Foundation of China (40830637 and 51009150), the National Water Pollution Control and Management of Major Special Topics Technology of China (2012ZX07601001 and 2008ZX07207).

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