Combining hydrological investigations and radium isotopes to understand the environmental effect of groundwater discharge to a typical urbanized estuary in China

Science of the Total Environment 695 (2019) 133872

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Science of the Total Environment journal homepage: www.elsevier.com/locate/scitotenv

Combining hydrological investigations and radium isotopes to understand the environmental effect of groundwater discharge to a typical urbanized estuary in China Kai Xiao a,1, Gang Li b,c,1, Hailong Li a,⁎, Yan Zhang d, Xuejing Wang a, Wenli Hu a, Chengcheng Zhang e a State Environmental Protection Key Laboratory of Integrated Surface Water-Groundwater Pollution Control, School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen 518055, PR China b China Institute of Geo-Environment Monitoring, Beijing 100081, PR China c Hebei Key Laboratory of Geological Resources and Environment Monitoring and Protection，Shijiazhuang 050021, PR China d School of Water Resources and Environmental Science, China University of Geosciences, Beijing 100083, PR China e Northwest Institute of Nuclear Technology, Xian 710024, PR China

H I G H L I G H T S

G R A P H I C A L

A B S T R A C T

• Riverine groundwater discharge can reach 58% of upstream river input. • Riverine groundwater discharge contributed 19%~44% DIN, 16%~39% DIP, and 31%~60% DSi to Dan'ao River. • A major form of DIN transported by groundwater is anaerobic ammonium.

a r t i c l e

i n f o

Article history: Received 28 June 2019 Received in revised form 8 August 2019 Accepted 9 August 2019 Available online 11 August 2019 Editor: José Virgílio Cruz Keywords: Radium isotopes Water pollution Water residence time Estuary Eutrophication

⁎ Corresponding author. E-mail address: [email protected] (H. Li). 1 Contributed equally to this work.

https://doi.org/10.1016/j.scitotenv.2019.133872 0048-9697/© 2019 Elsevier B.V. All rights reserved.

a b s t r a c t Pollution of urbanized rivers with excess nutrients due to groundwater discharge is an increasing environmental concern worldwide. Dan'ao river, a typical urbanized river in the Guangdong-Hong Kong-Macao Greater Bay Area, is experiencing heavy water pollution. However, the groundwater-derived nutrient loads had not yet been thoroughly quantified. In order to quantify the contribution of groundwater-derived nutrient inputs, we combined the methods of hydrological investigations and radium isotopes. Groundwater and river water samples were collected from the river upstream to the estuary for the analyses of radium quartets and nutrients including DIN, DIP and DSi. The results showed that the radium activities in both surface water and groundwater decreased from the estuary to the upstream. The groundwater discharge rate was estimated by the radium mass balance model using short-lived radium isotopes (223Ra and 224Ra). The estimated groundwater discharge rate ranged from 1.99 × 105 to 6.67 × 105 m3 d−1, comparable to the upstream river discharge rate of 4.23 × 105 m3 d−1. The groundwater-derived nutrient fluxes were 165.66–554.98 mmol m−2 d−1 for DIN, 2.47–8.26 mmol m−2 d−1 for DIP and 63.73–213.49 mmol m−2 d−1 for DSi, respectively. They contributed 19% ~44% DIN, 16%~39% DIP, and 31%~60% DSi of all the nutrient inputs into the Dan'ao River, respectively. In addition, the nutrient inputs by groundwater discharge has an average DIN:DIP ratio of as high as 190, which is able to

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K. Xiao et al. / Science of the Total Environment 695 (2019) 133872

potentially affect the riverine and marine nutrient structures. These findings may provide useful information for designing control strategies for reducing massive nutrient inputs to Dan'ao River in the future. © 2019 Elsevier B.V. All rights reserved.

1. Introduction Estuary is one of the most productive natural habitats in the world, and acts as a transition zone between terrestrial environments and marine environments (McLusky and Elliott, 2004). The synthetic interactions between marine and terrestrial processes can provide high levels of material transports, making estuaries to be significant sources of dissolved nutrients to the coastal ocean (Valiela et al., 1990; Kelly and Moran, 2002; Santos and Eyre, 2011). However, with the rapid development of urbanization, the excess nutrient inputs can lead to the frequent occurrences of eutrophication in urbanized rivers, thereby reducing the water quality and upsetting biodiversity equilibrium (Bricker et al., 1999; Bowen and Valiela, 2001). The material transports controlled by terrestrial processes include upstream river input and groundwater discharge (Eyre, 1988). The latter is typical of complexity and concealment but has important environmental implication (Hinton et al., 1998). As shown in the Graphic Abstract, groundwater discharge to a river can be classified into water that entered the aquifer from some distance away from the estuary (i.e., lateral groundwater discharge) and water that originated within the river itself and that entered the aquifer for a period of time before returning to the river (i.e., the hyporheic flow) (Alley et al., 2002). Groundwater discharge as a potential pathway for non-point nutrient transport can produce important environmental impacts on water quality of surface water. Nitrogen (N) and phosphorus (P) concentrations are often elevated in groundwater relative to surface water, and the stoichiometry of N:P in groundwater most often diverges drastically from the Redfield ratio (16,1) (Capone and Bautista, 1985; Weiskel and Howes, 1992; LaRoche et al., 1997; Corbett et al., 1999; Santos et al., 2013; Gao et al., 2018). Since early suggestions that groundwater may be a major source of nutrients to the ocean (Johannes, 1980), the groundwater discharge has well been documented to be a significant contributor of nutrients to the surface water (Burnett et al., 2003; Moore et al., 2011; Santos et al., 2010; Robinson et al., 2018). In some research areas, nutrient fluxes via groundwater discharge were shown to rival those from surface waters (Kim et al., 2005; Swarzenski et al., 2007; Wang et al., 2015). However, the nutrient input via groundwater discharge in the Yellow River Estuary was at least five times of that via the Yellow River (Xu et al., 2013a). The groundwater often has much higher proportions of bioavailable ammonium than the less available dissolved organic nitrogen that dominates nitrogen inputs to the coastal water (Santos et al., 2014). Recent studies by Wang et al. (2018) reported that groundwater with high N:P ratio of 37.0 can change nutrient structure and primary productivity in coastal water in Daya Bay, China. These studies provided deep insights into the groundwater-derived nutrient loadings into the surface water. However, the potential adverse environmental impacts of groundwater-derived nutrients on river water quality were still poorly understood (Brodie et al., 2007; Ouyang, 2012). Naturally occurring radium isotopes (223Ra, 224Ra, 226Ra and 228Ra) are effective tracers of groundwater discharge because they behave conservatively and are highly enriched in groundwater relative to surface waters (Moore et al., 2006). They have well been used for quantifying groundwater discharge to rivers as their half-lives have a wide range from 3.8 days to 1600 years, allowing tracing processes from small to large scales (Charette et al., 2001; Swarzenski et al., 2006; Moore and Shaw, 2008; Charette et al., 2013; Xu et al., 2013b). Dan'ao River is a typical urbanized and industrialized river in the Guangdong-Hong Kong-Macao Greater Bay Area, China. For the last

several years, a series of water quality problems, including point and non-point source pollutants such as nutrients, pesticides, and heavy metals have been reported by the Guangdong Environmental Protection Bureau (http://www.gdep.gov.cn/swrfz/). Although the government was aware of the severity of deteriorated water quality conditions, there were only few research papers about Dan'ao River (Ke et al., 2017; Li et al., 2018a, 2018b). In addition, the treatment process of limiting the upstream input of pollutants by management was not very effective. This may be because the pollutants transported by groundwater has long been largely overlooked in this region. Recent studies by Li et al. (2018a) highlighted that groundwater in the Dan'ao estuary can transport 23.5%~78.7% nutrients of those by river discharge. However, these results may be difficult to upscale due to the hydrogeological complexity such as the spatial variability of aquifer heterogeneity (Calver, 2001; Kennedy et al., 2008). Thus, it is urgently needed to further quantify the contribution of groundwater discharge to water pollution in Dan'ao river by investigating the current hydrological conditions and using isotope techniques along the whole river from the downstream estuary to the upstream. Thus, the aim of this work is to enhance our knowledge of the complexity of hydrological conditions and current water quality condition. Time series of physical-chemical data (e.g., water level, salinity and water temperature) and river fluxes will be obtained. The spatial distribution of radium isotopes will be analyzed for the residence time of estuarine water, groundwater discharge rate and groundwater-derived nutrient loads. The nutrients include the dissolved inorganic nitrogen Dissolved (DIN), dissolved inorganic phosphorous (DIP) and reactive silicate (DSi). The ultimate aim would be to achieve a comprehensive understanding of groundwater discharge behavior, to be applied for future water pollution controlling strategies in the similar urbanized river systems. 2. Materials and methods 2.1. Site descriptions Dan'ao river is the largest river discharging into the Daya Bay, a semi-enclosed bay in the Guangdong-Hong Kong-Macao Greater Bay Area, China (Fig. 1). With a rapid economic development and urbanization, the Dan'ao river has been dredged as the flood way of the Danshui River since 1993 (Huang et al., 2000). Its discharge rate to the Daya Bay was about 2.62–7.18 m3 s−1 (Ren et al., 2013; Wang et al., 2017). The catchment of the Dan'ao River (~110 km2) is characterized by a subtropical and monsoonal climate, with an average annual temperature of 22 °C and precipitation of 1700 mm, respectively. About 80% of precipitation events occur from April to September. The strong northeast monsoon prevails from October to April, and the southwest monsoon predominates from May to September. An overflow dam exists in the river upstream. The upstream banks are surrounded by heavily developed urbanized areas (e.g., road embankment, residential areas) and the slopes are steeper than the downstream ones, where mangrove wetlands grew. Tidal current in the Dan'ao River estuary is dominated by a semidiurnal irregular tide with a mean and maximum tidal range of 1.03 m and 2.60 m, respectively. 2.2. Field sampling In this study, groundwater and surface water were collected along Dan'ao River, extended from seaward of estuary mouth, where the

K. Xiao et al. / Science of the Total Environment 695 (2019) 133872

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Fig. 1. The location of study sites and field setting: (a) The relative location of Daya Bay to China; (b) The relative location of Dan'ao River to Daya Bay; (c) The spatial distribution of sampling sites along the Dan'ao River (the yellow filled triangles: river water and groundwater; the yellow filled squares: estuarine seawater). The red filled circle indicates the location of longterm water quality monitoring point operated by the Department of ecology and environment of Guangdong Province. The red segments indicate the measurement transects of Acoustic Doppler Current Profiler. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

salinity of surface water was N27 ppt, to the upstream, where the salinity of surface water was b1.0 ppt. We collected nine river water samples, seven nearshore groundwater samples and five estuarine seawater samples along Dan'ao River (supporting information Table S1). Surface water samples were directly pumped by a peristaltic pump on a small boat. In order to obtain the representative samples of outside seawater, samples were collected at the estuary mouth at high tides, just prior to the slack water. Groundwater samples were sampled near the river bank at a depth of about 0.5 m by a shallow porewater stainless-steel sampler, PushPoint. These samples represent the real chemical components of groundwater immediately before it discharges into the river from the aquifer. The dissolved radium was extracted from 3 to 25 L of groundwater and 25–60 L of surface water through Mn-fibers (~25 g) according to the method proposed by Moore (2010). The flow rate was b1 L min−1 to ensure complete Ra adsorption on the Mn-fiber. Two serial cartridges were used sporadically to evaluate the Ra extraction efficiency onto the MnO2 fiber (typically N96%). After the water collection, the samples for nutrient analysis were immediately filtered through pre-cleaned 0.45 μm pore cellulose acetate filters, sampled in 50 mL bottles and kept in mobile refrigerators stored under 4 °C until lab measurements for nutrients. The in-situ

physicochemical parameters including salinity, temperature and pH were simultaneously measured by a handheld HI9829 Model probe (Hanna Instruments, Inc). 2.3. Hydrological investigations For better understanding the inherent hydrological complexity, the calibrated electrical loggers (LTC diver, Solinist) and an Acoustic Doppler Current Profiler (ADCP, RiverSurveyor-M9, Sontek product, Xylem Inc) were used to investigate the hydrological conditions along the river. The time series of water level, temperature and electrical conductivity at each sampling site were recorded at 10 min intervals from December 20th to December 27th, 2016. All the loggers were placed at the bottom of river water sampling sites where surface water flooded them even at spring low tides. Electrical conductivity was converted to salinity according to the UNESCO/ICES/SCOR/IAPSO Joint Panel on Oceanographic Tables and Standards (Cox et al., 1967; Ma et al., 2014). Three bank-perpendicular transects (T1, T3 and T6, Fig. 1) were established to measure upstream, middle and downstream hydrogeologic characteristics such as current velocities, river crosssection areas and fluxes by ADCP cruises. In particular, the upstream T6 and middle T3 transects were measured 8 times during a tidal

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K. Xiao et al. / Science of the Total Environment 695 (2019) 133872

cycle. The downstream T1 transect was continuously measured 26 times during a tidal cycle. The detailed descriptions about the methods of measurement and error analysis for correcting fluxes were referred to our recent studies (Xiao et al., 2019a). The elevation of the upstream overflow dam base at T6 transect is much higher than the high tide level, which means T6 transect is almost unaffected by the tidal effects. Therefore, the measured runoff flux at T6 transect at low tides could be regarded as the net discharge of the river upstream. Similarly, the difference between the river runoff and tidal fluxes through the estuarine T1 transect could be regarded as the net recharge of outside seawater to the river.

2.4.3. Groundwater discharge rate The groundwater discharge rate was calculated using the radium mass balance model (Eq. (2)). As a natural hydrogeological unit, the radium mass balance in Dan'ao River was controlled by the contributions from multi-individual sources (upstream riverine inputs Mup, diffusion from bottom sediments Mdif, desorption from suspended particles Mdes and groundwater discharge MGD) and sinks (radium decay Mdec and downstream tidal exchange or net export/discharge Mdown). The total gain or loss of radium should be balanced for a certain period of time. The radium mass balance model used in this study is as follows: Mup þ M GD þ M dif þ M des ¼ M dec þ Mdown

ð2Þ

2.4. Analytical methods Solving Eq. (2) for QGD, one has: 2.4.1. Laboratory measurements Mn-fibers were washed with radium-free water thoroughly to remove all particles and salts in the laboratory. The activities of 223Ra, 224 Ra and 228Ra were analyzed using a widely used RaDeCC (Radium Delayed Coincidence Counting) system (Moore and Arnold, 1996). Samples were recounted after ~4 weeks to correct for 228Th-supported 224 Ra (Garcia-Solsona et al., 2008; Moore et al., 2011). Counting uncertainties were estimated as described in Garcia-Solsona et al. (2008). The long-lived radium isotope, 226Ra, was determined by a radon-in-air monitor (RAD7, Durridge Co.) as proposed by Kim et al. (2001). The water samples for nutrient analysis were analyzed by a spectrophotometer in the National Research Center for Geo-analysis, Chinese Academy of Geological Sciences. The specific methods for nutrient measurements are as follows: nessler's reagent colorimetry for NH+ 4 , diazamine coincidence spectrophotometry for NO− 2 , cadmium column reduction method for NO− 3 , molybdenum blue spectrophotometry for dissolved inorganic phosphate (DIP), and silicon molybdenum yellow spectrophotometry for dissolved silicon (DSi). The detection limits of − − NH+ 4 , NO2 , NO3 , DIP, and DSi were 0.04, 0.002, 0.01, 0.005 and −1 0.02 mg L , respectively. The concentration of dissolved inorganic ni− + trogen (DIN) refers to the sum of those of NO− 3 , NO2 and NH4 . 2.4.2. Water residence time The water residence time (Tf) is an important parameter, which can provide the timescale available for components to accumulate in the water column (Moore, 2006). Two common methods such as the tidal prism method and the radium isotope method were often used to estimate Tf. The short-lived Ra isotopes, 223Ra (half-life = 11.4 days) and 224 Ra (half-life = 3.7 days) are especially useful in studies for estimating short residence times such as estuarine water systems (Moore, 2000a, 2000b; Xu et al., 2013b). In this study, both of above two methods were used to calculate Tf with the following equations (Sanford et al., 1992; Moore et al., 2006): T V T f ¼ tide river P tide ð1−bÞ

Tf ¼

"
#  F 224 Ra=223 Ra
 −1 λ224 I 224 Ra=223 Ra 1

ð1bÞ

where Vriver is the river volume, defined as the total water volume from the upstream T6 transect to the downstream T1 transect at the mean water level; Ttide is the tidal period (0.51 days); Ptide denotes the tidal prism, which is assessed as the product of the average river surface area and mean tidal range during the field monitoring period; b is the return flow factor, which is assumed to be equal to the seawater fraction estimated by a three end-member mixing model (Moore, 2006). For the radium model, F(224Ra/223Ra) is 224Ra/223Ra activity ratio of the inputs into the system and I(224Ra/223Ra) is the 224Ra/223Ra activity ratio of the river water samples. The decay constant for 224Ra is represented as λ224. Here, the most of the radium entering the system is assumed that from groundwater discharge (Moore et al., 2006).

Q GD ¼

M GD Ra22i gw

¼

M dec þ Mdown −M up −M dif −M des Ra22i gw

ð3Þ

22i Ra activwhere QGD and Ra22i gw are the groundwater discharge rate and ity at the groundwater sampling sites from estuarine D1 to upstream D6, respectively. i equals 3 or 4; By measuring the river flux at the transects T1 and T6, we can easily get the upstream influx and downstream efflux of radium as follows:

Mup ¼ Q up Ra22i up

Mdown ¼ Q down Ra22i ð4bÞ down 22i where Qup and Ra22i Ra concentration at the up are the upstream flux and upstream site D6, respectively; Qdown and Ra22i down are the average downstream flux rate during the falling tides and 22iRa concentration at the downstream site D1, respectively. The decay of the radium inventory could be obtained by the following equation: Mdec ¼ I22i λ22i ¼ V river Ra22i river λ22i

ð5Þ

where I22i is the inventory of 22iRa in Dan'ao River, equaling the product of average radium concentration Ra22i river in surface water and river water volume Vriver; λ22i is the disintegration coefficient, 0.189 d−1 for 224Ra and 0.061 d−1 for 223Ra (Li and Cai, 2011). The river surface water volume Vriver could be calculated by the following equation: 1 V river ¼ ðST1 þ ST3 þ ST6 Þ  L 3

ð6Þ

where ST1, ST3 and ST6 are the average area of three measurement transects at T1, T3 and T6 (Fig. 1). L denotes the distance between the upstream T6 and downstream T1 transects. The theoretical flux of 22iRa from sediments due to diffusion, bioirrigation, and sediment mixing (both physical and biological) can be calculated using the approach of Nozaki et al. (1990): Mdif ¼ F 22i sed  Sriver ¼ P  φ 

pffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi λ22i  ðDt þ K  Dmx Þ=ð1 þ K Þ

ð7Þ

22i Ra from sediments; Sriver is the estuwhere F22i sed is the diffusive flux of ary surface area (m2); P (dpm per liter sediment) is the production rate of radium isotopes in sediment with porosity (φ). Dt (cm2 s−1) is the dispersion coefficient for water movement through the sediments due to physical forcing and bioirrigation. Dmx (cm2 s−1) is the sediment mixing coefficient of water in the sediments. Dt and Dmx have a value of 2 × 10−5 and 6 × 10−6 for typical marine mud sediment, respectively (Zlotnik et al., 2010; Moore et al., 2011; Luo and Jiao, 2016). K is the adsorption coefficient for sediment bulk. K and P can be estimated with the sediment leaching experiment (Moore et al., 2011).

K. Xiao et al. / Science of the Total Environment 695 (2019) 133872

Mdes ¼ F 22i des  Q avg ¼ C p  Dc  Q avg

ð8Þ

−3 ) is the flux of 22iRa desorbed from suspended parwhere F22i des (dpm m ticles in unit volume water; Qavg is the average river runoff, equaling the mean value of Qup and Qdown. The concentration of suspended particles (Cp) in Dan'ao River was measured to be 29.75 ± 0.03 g m−3 (Wang et al., 2018). A maximum desorption (Dc) of 22iRa from suspended particles was assumed to be 2 dpm g−1 for 224Ra and 0.1 dpm g−1 for 223Ra (Moore and Shaw, 2008; Moore et al., 2011). By applying upstream flux, downstream estuarine flux and calculated Ra-derived groundwater discharge rate, the nutrient inputs from upstream, seawater and groundwater to Dan'ao River can be calculated by the following equations:

F rw ¼ Q up  C rw

ð9Þ

F sw ¼ b  Q down  C sw

ð10Þ

F GD ¼ Q GD  C gw

ð11Þ

where Frw, Fsw and FGD mean nutrient fluxes by upstream river runoff, tidal seawater input and groundwater discharge, respectively; Crw, Csw and Cgw are the mean concentrations of the considered nutrient in upstream river water, estuarine seawater and groundwater, respectively.

(a)

8.0

3. Results 3.1. Current pollution condition in Dan'ao river In order to estimate the current pollution condition in Dan'ao River, the data of water quality parameters were obtained from the government monitoring system (http://www.gdep.gov.cn/swrfz/). The water quality standards of surface water were referenced (National Standard of the People's Republic of China, GB 3838, 2002). The higher the level, the worse water quality. As shown in Fig. 2, the water quality parameters at the monitoring points varied greatly from October 2016 to March 2017. For example, pH ranged from 6.28 to 7.84, with an average value of 7.17 (Fig. 2a). The electrical conductivity ranged from 989 to 14,000 μs cm−1, with an average value of 3874 μs cm−1 (Fig. 2b). The number of fecal coliforms ranged from 7900 to 340,000 per liter, with an average value of 200,000 per liter. It is worth noting that the average number of fecal coliforms was almost five times higher than the upper limit of the fifth level water quality standard (the worst water quality level, 40,000 per liter), indicating Dan'ao River was seriously affected by human waste (Fig. 2c). Chemical Oxygen Demand (COD) ranged from 4.15 to 6.98 mg L−1, with an average value of 5.9 mg L−1, which was higher than the value of fourth level water quality standard (Fig. 2d). The concentrations of nutrients such as dissolved nitrogen and phosphorus indicated that Dan'ao River was heavily polluted. For example, the average concentration of dissolved nitrogen was nearly three times larger than the value of fifth level water quality standard (Fig. 2e). This may be caused by excessive ammonia nitrogen due to

(e)

0.6

TN (mmol/L)

The flux of 22iRa desorbed from suspended particles is calculated as:

0.5

pH

pH

7.5 7.0 6.5 6.0

1e+4 1e+3 1e+2

Fecal coliform group

1e+5

V

IV

(d)

45 40

0.3 0.2

V

0.1 0.35 0.30 0.25 0.20 0.15 0.10 0.05

IV

NH4-N

V

IV

(g)

1e+6

COD (mg/L)

FCG (num/L)

(c)

Total dissolved nitrogen

0.4

COD

V

35

IV

30 25

NO3-N (mmol/L)

EC (µs/cm)

Electrical conductivity

NH4-N (mmol/L)

(f)

1e+5

0.16

(h)

0.035 0.030 0.025 0.020 0.015 0.010

TP (mmol/L)

(b)

5

NO3-N

V

0.12

IV

0.08 0.04 0.00 Total dissolved phosphorus

V

IV

20 1 1 1 1 1 1 /10/0 016/11/0 016/12/0 017/01/0 017/02/0 017/03/0 2016 2 2 2 2 2

Date

1 1 1 1 1 1 /10/0 016/11/0 016/12/0 017/01/0 017/02/0 017/03/0 2 2016 2 2 2 2

Date

Fig. 2. The temporal variations of monitored water quality parameters, including (a) pH, (b) electrical conductivity, (c) fecal coliform group (FCG), (d) chemical oxygen demand (COD), (e) total dissolved nitrogen (TN), (f) ammonia nitrogen (NH4-N), (g) nitrate nitrogen (NO3-N) and (h) total dissolved phosphorus (TP). Data were obtained from the Department of ecology and environment of Guangdong Province (http://www.gdep.gov.cn/swrfz/). The black dashed line indicates the average value. The red and purple dashed lines indicate the fifth and fourth level water quality standards, referring to the National Water Quality Standards for surface water (National Standard of The People's Republic of China, GB 3838, 2002). (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

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K. Xiao et al. / Science of the Total Environment 695 (2019) 133872

the anaerobic water environment with high value of COD. Therefore, nitrification may be inhibited, leading to excessive ammonium (Fig. 2f). Similarly, total dissolved phosphorus was also shown to be significantly excessive. The average concentration of total dissolved phosphorus was 1.5 times higher than the value of fifth level water quality standard. Overall, the current water quality in Dan'ao River was extremely deteriorated. Therefore, the potential reasons of water pollution need to be explored for effective environmental improvement. 3.2. Riverine hydrological conditions The time series of daily precipitation recorded in a meteorological station of Daya Bay showed no large rainfall occurred during the sampling period (supporting information Fig. S1). Therefore, the variation of the magnitude of upstream river runoff and nutrient concentrations in surface water and groundwater could be ignored. The results of observed tidal levels (i.e., the riverine water depth) and temperature showed no significant relationship (supporting information Fig. S2). However, salinity was very sensitive to the variation of tidal level and the distance to the sea. For example, the salinity

fluctuations at D5 and D6 were almost consistent with the tidal fluctuations as this way: the salinity was almost zero at the lowest tides and increased gradually with the rise of tidal level; At high tides, the salinity can reach the maximum (~20 ppt). However, there was nearly no any response for the salinity from E2 to D3 to the variations of tidal level. This may be explained by the coupled effects of the tidal effect and upstream freshwater input. That is to say, salinity was well mixed downstream and change little with tidal fluctuations. In view of the spatial variations, the terrain elevation decreased primarily and then gradually rose from the E2 to D6 (Fig. 3a). Accordingly, the average water depth at the monitoring points varied adversely with elevation (Fig. 3b). In addition, as the distance goes farther from the tidal source toward the upstream, the variation range of water depth (i.e., the tidal amplitude) gradually decreased. The average values of temperature at different monitoring points were similar but the varied ranges from D4 to D6 were significantly larger than those from E2 to D3 (Fig. 3c). This may indicate that the upstream input of fresh water has greater influence on the temperature variations. Similarly, salinity variations were conservative from E2 to D3 but changed dramatically from D4 to D6 (Fig. 3d).

Fig. 3. The spatial variations of (a) elevation, (b) water depth, (c) temperature and (d) salinity at the sampling sites. The error bars indicate the variation range during the monitoring period.

K. Xiao et al. / Science of the Total Environment 695 (2019) 133872

As shown in Fig. 4, the flow velocities at T1 and T3 stations showed a significant layering phenomenon at the mid-rising tide. The flow velocity in the surface layer reached the maximum (~0.6 m s−1) and gradually decreased with the water depth. At the bottom, the water was nearly constant. In contrast, there were no significant layering phenomena for the flow velocity at T6 transect. In terms of spatial variability, the flow velocity at T1 was larger than that at other transects. This is because the estuarine T1 transect is closest to the tidal source and there is nearly no input of fresh water from the upstream due to the existence of overflow dam. Further, in terms of temporal variability, the flow velocity was investigated during a spring-neap tidal cycle at estuarine T1 transect. The results showed that the average flow velocity reached the maximum in the middle of rising and/or ebbing tide (supporting information Fig. S3). In addition, the results also showed a good linear correlation between the average flow velocity and flux. These results are similar to our recent field investigation results at the mouth of Jiaozhou Bay (Xiao et al., 2019a).

3.3. Salinity and radium isotope activities Salinity is a good indicator, which can reflect the physical mixing processes at estuary. The spatial distribution pattern showed that the salinity and short half-life radium isotope activities (223Ra and 224Ra) in both surface water and groundwater gradually increased from the upstream to the estuary (Fig. 5 and supporting information Fig. S4). However, the spatial distributions of the long half-life 228Ra and 226Ra did not show similar variation trends. For example, 228Ra activity was relatively low at estuary but peaked in the middle of the river. The possible reasons for the inconsistence may be that the long half-life of 228Ra has the low production rate and was diluted by the tidal mixing. Generally, the average activity of radium in groundwater was one order of magnitude higher than those in river water and estuarine seawater (supporting information Table S1).

7

Correlation analysis of four radium isotopes showed that there were good linear relationships among them (supporting information Fig. S5). In particular, the linear correlations between the salinity and the short half-life 223Ra (r2 = 0.77) and 224Ra (r2 = 0.76) were much better than those of long half-life 226Ra (r2 = 0.56) and 228Ra (r2 = 0.08) (Fig. 6). In order to show the spatial distribution of radium isotopes more clearly in Dan'ao River, we conducted a statistical analysis by dividing the water samples into three kinds according to the sampling locations: estuarine seawater, river water and groundwater (Fig. 7). Results showed that the general rank of average radium activities in three kinds of water was that: Groundwater N Estuarine seawater N River water. Meanwhile, the statistical results also showed that the rank of variation ranges of average radium activity was that Groundwater N River water N Estuarine seawater. 3.4. Water residence time According to Eqs. (1a) and (1b), two methods were used to calculate the residence time of estuarine water. For the first, tidal prism method, the estuary volume Vriver, defined as the frustum of the upstream and downstream cross-sections at the mean water level, was calculated to be 1.16 × 106 m3. The tidal period T equals 0.51 days. Therefore, the tidal prism Ptide was assessed as the product of the estuary surface area and observed mean tidal range, equaling to 1.25 × 106 m3. Following the mixing model in Moore et al. (2006), the return flow factor b was assumed to be equal to seawater fraction, which was calculated to be 0.29 for 223Ra and 0.65 for 224Ra. Then, the calculated residence time of estuarine water in Dan'ao River ranged from 0.5 to 0.91 days. For the second method, the application of this model requires precise knowledge of the 224Ra/223Ra activity ration of input to calculate the water residence time. In this case, F(224Ra/223Ra) = 67 and I (224Ra/223Ra) = 55. The decay constant for 224Ra (λ224) equals 0.189 d−1. Therefore, the calculated water residence time equals 1.15 days. As this model is quite sensitive to the variation of selected for the

Fig. 4. The spatial distributions of water flow velocity at (a) T1, (b) T3 and (c) T6 transects during the rising-mid tides.

30 25 20 15 10 5 0

(b) D6

D5 D4

D3

D1

223

(a)

Ra (dpm/100L)

K. Xiao et al. / Science of the Total Environment 695 (2019) 133872 Salinity (ppt)

8

E1 E3

60 50 40 30 20 10 0

D6

(d)

5000 4000 3000 2000 1000 0

D6

224Ra

D5 D4

D3

D1

E1 E3

226

D3

D1

E1 E3

(dpm/100L)

600 500 400 300 200 100 0

D6

228Ra

(dpm/100L)

(e)

228 Ra (dpm/100L)

223Ra

Ra (dpm/100L)

224

(c)

Ra (dpm/100L)

Salinity (ppt)

D5 D4

D5 D4

D3

D1

E1 E3

(dpm/100L)

120 100 80 60 40 20 0

D6

226Ra

D5 D4

D3

D1

E1 E3

(dpm/100L)

Fig. 5. The spatial distributions of (a) salinity, (b) 223Ra, (c) 224Ra, (d) 228Ra and (e) 226Ra in the surface water (colour contour plots) and groundwater (the above black histograms).

activity ratio (Moore et al., 2006), a change of considerable 10% error of the activity ratio resulted in ±0.64 days. Therefore, the estimated residence time of estuarine water varied from 0.51 to 1.8 days. Although the values of water residence time calculated by two methods were different, they were actually in the same order of magnitude, indicating that the residence time of estuarine water in Dan'ao River was very short. 3.5. Groundwater-derived nutrient fluxes The parameter values used in the equations for estimating groundwater discharge rate were summarized in supporting information Table S2. For example, the fluxes of upstream (Qup) and downstream (Qdown) used in the Eqs. (4a) and (4b) were measured to be 4.23 × 105 m3 d−1 at D6 and 1.84 × 106 m3 d−1 at D1, respectively. Thus, the average river runoff (Qavg) was 1.13 × 106 m3 d−1, equaling the mean value of Qup and Qdown. The river water volume Vriver was calculated to be 7.97 × 105 m3, according to the average area of the upstream and downstream cross-sections, which can be directly obtained by the measurement of ADCP. Substituting these parameters into the radium mass balance model (Eq. 3), the radium fluxes from groundwater can be easily converted to groundwater discharge fluxes. The average radium activity levels, 1134.03 dpm 100 L−1 for 224Ra and 16.19 dpm 100 L−1 for 223Ra, were used in the model as the groundwater radium end-members. Finally, groundwater discharge rate was estimated to be 6.67 × 105 m3 d−1 (76.2 cm d−1) by 224Ra and 1.99 × 105 m3 d−1 (22.7 cm d−1) by 223Ra. Therefore, the average value of groundwater discharge rate into Dan'ao River was 2.46 × 105 m3 d−1 (28.1 cm

d−1). Compared with the upstream river discharge rate 4.23 × 105 m3 d−1, the average groundwater discharge rate reaches up to 58% of the former one. As shown in Fig. 8a and supporting information Table S3, the main form of inorganic nitrogen in groundwater and river water was ammonia nitrogen, which indicated that the river water was in a severe anoxic reducing environment. In addition, the DIN concentrations at estuary were lower than those at middle and upstream transects. It was worth pointing out that the average DIN concentration during the sampling period was much higher than the fifth level water quality standard. This was consistent with the long-term monitoring results, both of which belong to the serious excess of nitrogen input. The average concentration of DIP was slightly lower than the fifth level water quality standard, but it was still higher than the fourth level water quality standard, belonging to the category of phosphorus pollution (Fig. 8b). In view of the spatial distribution, the DIP concentration of groundwater was lowest at estuary. This result was similar to the finding at Delaware Estuary, a heavily urbanized estuary in the USA (Lebo and Sharp, 1993). The estuarine groundwater may carry lower concentration DIP than other sites. Another possible reason could be that the concentration of dissolved oxygen in estuarine seawater may be higher than that in groundwater and river water, resulting in less release of phosphorus by desorption reactions (Furumai and Ohgaki, 1989). There was no specific water quality standard for the DSi, but one can clearly see that the DSi in groundwater was higher than that in river water and estuarine seawater (Fig. 8c). In particular, the approximate linear relationships between the short half-life radium isotope activities and nutrients (except DIP) were found, indicating groundwater could

K. Xiao et al. / Science of the Total Environment 695 (2019) 133872

9

Fig. 6. Correlations between radium isotope activities, including (a) 224Ra, (b) 223Ra, (c) 228Ra and (d) 226Ra, and salinity. The gray filled circles and white squares indicate the surface water (refer to left axis) and groundwater (refer to right axis), respectively.

be an important nutrient source for river water (supporting information Fig. S6). Therefore, nutrient inputs by the river upstream were 694.8 mmol m−2d−1 for DIN, 9.71 mmol m−2 d−1 for DIP and 105.64 mmol m−2 d−1 for DSi. Similarly, the fluxes induced by tides were 17.6 mmol m−2 d−1 for DIN, 3.45 mmol m−2 d−1 for DIP and

38.26 mmol m−2 d−1 for DSi into Dan'ao River. The input of DIN, DIP and DSi from groundwater to Dan'ao River was calculated according to the mean nutrient concentrations collected along Dan'ao River. Multiplying concentrations by groundwater discharge rates yielded daily DIN, DIP and DSi fluxes into the river, ranging from 165.66 to 554.98, 2.47–8.26 and 63.73–213.49 mmol m−2 d−1, respectively. We assumed

Fig. 7. Box plots for showing the statistically significant differences in the activities of (a) 224Ra, (b) 223Ra, (c) 228Ra and (d) 226Ra among the river water, groundwater and estuarine seawater. The symbols of “×” indicate the locations of mean values. The small circles indicate the outliers.

10

K. Xiao et al. / Science of the Total Environment 695 (2019) 133872

Riverwater

Groundwater (a)

DIN (mmol/L)

4 3 2

Estuarine seawater

NO3--N + NH4 -N NO2 -N

1

(b)

0.04

DIP (mmol/L)

0

0.03

V

DIP

0.02

V 0.01 0.00

DSi (mmol/L)

(c)

1.2 1.0

DSi

0.8 0.6 0.4 0.2 0.0

W W W W W W W W W W W -SW W W -G 3-G 1-G 3-G 4-G 5-G 6-G 0-R 2-R 2-R 3-R 4-R 6-R d d E2 D D D D E E1 D D D D D

Water samples Fig. 8. The spatial distributions of nutrient concentrations in estuarine seawater (SW), river water (RW) and groundwater (GW), including (a) DIN, (b) DIP and (c) DSi. The three different colour bands from the left to the right indicate the groundwater, river water and estuarine seawater, respectively. The black dashed line indicates the average value. The red and purple dashed lines indicate the fifth and fourth level water quality standards, referring to the National Water Quality Standards for surface water (National Standard of The People's Republic of China, GB 3838, 2002). (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

that the dissolved nutrients in Dan'ao River were mainly derived from three components, including the upstream freshwater, groundwater discharge and estuarine seawater. As a result, we can derive the contribution percentage of each component (Fig. 9). One can see that the river upstream dominated the nutrient inputs into Dan'ao River (Tables 1 and 2). For example, the river upstream can contribute 76% DIN, 60% DIP and 47% DSi on average. However, groundwater is another important nutrient source, which can contribute 19%~44% DIN (22% on average), 16% ~39% DIP (19% on average) and 31%~60% DSi (36% on average). Last, the estuarine seawater contributed less nutrients than river upstream and groundwater, with average contribution percentages of 2% DIN, 21% DIP and 17% DSi, respectively.

4. Discussions 4.1. Uncertainty analyses Defining the groundwater end-member concentration is a crucial step in groundwater tracer studies and has been recognized as a major source of inherent uncertainties (Burnett et al., 2007). Most previous studies have used the average radium concentration as the groundwater end-member (Lee et al., 2012; Kwon et al., 2014; Sadat-Noori et al., 2015; Tait et al., 2017) while some have considered the maximum

radium activity to avoid overestimation (Moore, 1996; Stewart et al., 2015). In order to evaluate the uncertainty caused by the groundwater endmember in this study, the mean value was changed by a standard deviation, which can cause variations of the groundwater discharge flux by 12.5% for 224Ra and 16.8% for 223Ra. In this case, the groundwater discharge fluxes were (6.67 ± 0.83) × 105 m3 d−1 for the 224Ra mass balance model and (1.99 ± 0.33) × 105 m3 d−1 for the 223Ra mass balance model. Similarly, the measurement uncertainty of 10% at downstream D1 site can lead to variations of the groundwater discharge flux by 10% and 11.6% for 224Ra and 223Ra models, respectively. Another source of uncertainty could be caused by the asynchronization of sampling work at the nine sampling stations taking place over multiple days. Here, despite sampling went over multiple days, little difference was observed between the maximum tidal ranges (0.58–0.61 m) at each site (Fig. S2) and there was little change in atmospheric conditions and minimal rainfall over the course of the study (Fig. S1). Therefore, we assume that similar rates of porewater exchange occurred at the riverbed during the sampling period. In addition, this study has only traced the effects of groundwaterderived nutrients and their contribution percentage. There are large portions of unaccounted groundwater-derived nutrient inputs from the other tributaries from the desorption of resuspended particles (Rodellas et al., 2015). In particular, for the highly polluted estuary,

K. Xiao et al. / Science of the Total Environment 695 (2019) 133872

11

Fig. 9. The average contribution percentages of upstream fresh water (F_up), downstream estuarine seawater (F_down) and groundwater (F_GW) to the inputs of (a) DIN, (b) DIP, (c) DSi and (d) NH+ 4 into Dan'ao River.

there is a great need to consider the nutrient loadings derived from sedimentary processes (e.g., diffusion, bioirrigation and bioturbation), which will mount great influences on the nutrient diagenesis and removal (Hu et al., 2001; Cai et al., 2015; Hong et al., 2017). Overall, these unaccounted factors have a large potential to cause unforeseen uncertainties, which may warrant further investigation by future studies. 4.2. Comparisons with other studies The comparative results of residence time, groundwater discharge rate and groundwater-derived nutrient fluxes into tidal estuaries with some of the previous studies were summarized in Table 3. Generally, our results fell within the results of other studies in different countries. Among these studies, if normalizing to per square meter of area, the groundwater discharge rate ranged from 0.1 cm/d in the Okatee Estuary, USA (Moore et al., 2006) to 328 cm/d in the Richmond River Estuary, Australia (de Weys et al., 2011; Santos et al., 2013). Similarly, groundwater-derived DIN loadings ranged from 0.06 (Swarzenski et al., 2006) to 239.7 mmol m−2 d−1 (Moore et al., 2006), groundwater-derived DIP loadings ranged from 0.01 (Kelly and Moran, 2002) to 49.3 mmol m−2 d−1 (Moore et al., 2006) and groundwater-derived DSi loadings ranged from 1.0 (Li et al., 2018a) to 220 mmol m−2 d−1 (Rengarajan and Sarma, 2015). Recently, the groundwater discharge rates at the estuary of Dan'ao River were estimated using so-called “pair-wells” methods through building two intertidal transects at D1 and E1 perpendicular to the

river bank (Li et al., 2018a). Based on the generalized Darcy's Law, the estimated groundwater discharge rates at intertidal transects ranged from 1.6 to 39.1 cm d−1, which was close to the half of this study but had the same order of magnitude (Table 3). Similarly, the groundwater-derived nutrient fluxes except DIP were significantly lower than those in this study. Therefore, the point measurement could be difficult to extend the whole river, but both of them indicate groundwater discharge was an important nutrient source to Dan'ao River. 4.3. Environmental implication The joint analysis of hydrological dynamics and isotopic results described in the above section, together with the background information available from previous works (Li et al., 2018a, 2018b), has provided deeper insights into the environmental role of groundwater discharge in Dan'ao River. The combined treatment of the hydrogeological information advances our understanding of the hydrodynamic complexity. The wide range of reported groundwater-derived nutrient fluxes in Table 3 reflects the importance of hydrogeologic controls, as well as the potential anthropogenic perturbations. These perturbations can change the quality of groundwater and river water, and affect the stability of the coastal ecosystem (Swarzenski et al., 2006; Destouni et al., 2008). For example, during the last ten years, a large petrochemical industrial zone appeared around Dan'ao River. As ammonia concentration is usually high in the petrochemical wastewater (Ma et al., 2009; Shavisi et al., 2014), the DIN concentration (mainly NH+ 4 -N) was very high in

Table 1 Nutrient fluxes transported by groundwater discharge, upstream fresh water and downstream seawater inflow and their contribution percentages to Dan'ao River. Source

Groundwater discharge Upstream fresh water Downstream seawater a

Discharge (m3/d)

Nutrient fluxes (mmol m−2 d−1)

Contribution percentage (%)

DIN

DIP

Dsi

DIN

DIP

DSi

2.46 × 105 (1.99 × 105–6.67 × 105)a

204.5 (165.66–554.98)

3.04 (2.47–8.26)

78.7 (63.73–213.49)

4.23 × 105

694.8

9.71

105.64

6

17.60

3.45

38.26

22 (19–44) 76 (79–55) 2 (2–1)

19 (16–39) 60 (62–45) 21 (22–16)

36 (31–60) 47 (51–30) 17 (18–10)

1.84 × 10

Numbers in parentheses indicate the variation range.

12

K. Xiao et al. / Science of the Total Environment 695 (2019) 133872

Table 2 DIN fluxes transported by groundwater discharge, upstream fresh water and estuarine seawater and their contribution percentages to Dan'ao River.

Groundwater discharge

Contribution percentage (%)

NH+ 4 -N

NO− 2 -N

NO− 3 -N

NH+ 4 -N

NO− 2 -N

NO− 3 -N

2.46 × 105 (1.99 × 105–6.67 × 105)a

193.1 (156.43–524.03)

2.17 (1.76–5.9)

9.23 (7.48–25.05)

4.23 × 105

575.2

21.0

98.5

25 (21–48) 75 (79–52)

0.0

4.1

13.5

0

8 (7–19) 77 (78–68) 15 (15–13)

8 (7–18) 81 (82–72) 11 (11–10)

Upstream fresh water Downstream seawater a

DIN fluxes (mmol m−2 d−1)

Discharge (m3/d)

Source

1.84 × 10

6

Number in parentheses indicate the variation range.

Dan'ao River, with the maximum NH+ 4 -N concentrations reaching N3 mmol L−1 at D2. Similarly, recent research by Ke et al. (2017) also found high NH+ 4 -N concentration at Dan'ao estuary and they speculated that NH+ 4 -N mainly originate from industrial wastewater, which has a

strong influence on the water quality. However, they may have ignored the effect of groundwater discharge, which can also deliver large amounts of nutrients to the river, such as nitrogen (especially NH+ 4 -N) and phosphorus (Fig. 9).

Table 3 Comparisons of groundwater discharge rate, groundwater-derived nutrient fluxes and water residence time with other studies. Study site

DIP

DSi

Tf

Tracers

References

Groundwater discharge rate

DIN

m3 d−1

cm d−1

mmol m−2 d−1

0.9

0.55

–

–

9.4

0.2–2

0.17–0.49

0.01–0.04

–

8±4

224/228/226

2.1

4.5 ± 4.6

0.16 ± 0.17

–

5.9–20

224/223/228/226

(Charette and Buesseler, 2004)

2.6 × 10 (1.0–3.8) × 105

23.6

26

0.11

26.0

~7

224/223/226

(Hwang et al., 2005)

2.0–7.4

0.06–1.06

0.07–0.38

–

0.8–1.0

8.6 × 104

0.1–1.2

25.2–239.7

5.2–49.3

–

1.6–5

70–77

4.7–19.5

0.36–1.48

–

–

6.0–10.6

–

–

–

0.44

37.1–58.9

–

–

–

0.21

2.8–328

38.6

0.5

–

0.2–2.3

0.31 ± 0.34

0.05 ± 0.06

–

d 224/223/228/226

Waquoit Bay estuary, MA, USA Pettaquamscutt estuary, Narragansett Bay Elizabeth river estuary, Chesapeake Bay, USA Yeoja Bay, Korea Loxahatchee river estuary, FL, USA Okatee estuary, SC, USA

3.7 × 10

4

– 1.0 × 106 7

– (0.8–1.4) × 104 Richmond river estuary, (4.8–7.7) × NSW, Australia Wet 104 Richmond river estuary, NSW, – Australia 8.5 × Caloosahatchee river estuary, FL, 104–1.3 × USA 106 Gautami Godavari estuary, India 5.0 × 106 (2.0–4.3) × Vasishta Godavari estuary, India 107 Kakinada bay, India 3.0 × 108 (1.7–1.8) × Jiulong river estuary, China 108 (0.3–1.4) × Jiulong river estuary, China 107 (8.6 ± 2.6) Wet × 104 Korogoro Creek estuary, NSW, Australia (1.7 ± 1.7) Dry × 104 Shark River Slough estuary, FL, 65–297 USA (6.1–7. 8) × 104 Coffs Creek estuary, NSW, (2.6–4.3) × Australia 104 Pamet river estuary, MA, USA

Dry

Six mangrove creeks, Australia

–

Knysna estuary, South Africa

1.8 × 10

Daya Bay, China

6.8 × 106 (6.3 ± 2.4) × 106 – (1.99–6.67) × 105

Daya Bay, China Dan'ao estuary, Daya Bay, China Dan'ao river, Daya Bay, China a b c

TDN. TDP. NO3-N.

Ra

(Charette et al., 2001) (Kelly and Moran, 2002)

Ra

Ra + Si 224/223/228/226 Ra + 222 Rn 224/223/228/226 Ra + Salinity 224/223/228/226 Ra

(Swarzenski et al., 2006) (Moore et al., 2006) (Charette, 2007)

222

Rn

(Santos and Eyre, 2011)

–

222

Rn

(de Weys et al., 2011; Santos et al., 2013)

13.5–19

224/223/228/226

30.3

1–19

0.6–2.6

5–40

2.6–4.8

–

19–40

2.6–5.5

200

–

–

120–140

10.0

220

–

2.3

71.7

–

Ra

(Charette et al., 2013)

224/223/228/226

170.5–189 47.6

Ra +

Salinity+Si 224/226

Ra

(Rengarajan and Sarma, 2015)

(Guo et al., 2011)

224/223/228/226

3.7–20.3 74.4 ± 22.3 14.9 ± 14.9

12.4–67.8

0.01–0.03

20.4–111.5

~2

8.1 ± 3.9

0.45 ± 0.74

–

–

Ra +

Salinity 224/223/226 222

1.6 ± 0.4

0.10 ± 0.02

–

–

–

–

–

0.5–2

Ra +

Rn

(Wang et al., 2015) (Sadat-Noori et al., 2015; Sadat-Noori et al., 2016)

224/223/226

0.7–3.0

222

Ra + Rn + Salinity

27.8 ± 5.3 –

–

–

5–9.2

223

13.6 ± 2.1 –

–

–

–

224

0.95 ± 0.40b

–

–

224/223

3.3 ± 0.3 3.2

224/223

Ra + 222Rn + Salinity 222 Rn 224

Ra Ra

(Smith et al., 2016)

(Sadat-Noori et al., 2017)

1.5–30.9 5

Ra +

Salinity

2.39 ± 1.30a

1.5

0.14–0.98

–

–

28.2 1.18 ± 0.43 1.6–39.1

13.7c

0.2

37.4

0.2–0.37c

0.008–0.023 –

16

2.2–201.9

0.24–18.9

–

22.7–76.2

165.66–554.98 2.47–8.26

1.0–45.7

63.73–213.49 0.5–1.8

Ra

Ra

(Tait et al., 2017) (Petermann et al., 2018) (Wang et al., 2017) (Wang et al., 2018)

Darcy's Law

(Li et al., 2018a)

224/223

This study

Ra

K. Xiao et al. / Science of the Total Environment 695 (2019) 133872

Our analysis of the results put forth here leads us to characterize that even the volume of groundwater discharge is not dominant in water budget, it still can determine the nutrient structure in river water. The typical marine organic matter has an average stoichiometry of approximately (CH20)106(NH3)16(H3PO4) (Redfield, 1934), providing C:N:P mole ratios of 106:16:1. However, the average DIN:DIP ratio reached up to 190 in groundwater, which was nearly twelve and two times higher than those of the Redfield ratio and river water, respectively. This indicates that massive nutrient loadings transported by groundwater may potentially change nutrient structures in Dan'ao River. The major form of DIN carried by groundwater was ammonia nitrogen, which belongs to highly labile forms of nitrogen and can be rapidly consumed within the surface water by primary producers such as macroand microalgae (Charette et al., 2013). However, they were not consumed because of the severe oxygen deficiency in the water body, which made it difficult for phytoplankton to survive. The degradation of water quality due to nitrogen and other nutrients can alter species composition and decrease overall health of aquatic communities (Ouyang, 2012). High levels of these constituents in surface water bodies have contributed to conditions of elevated bacterial levels and increased chemical oxygen demand (Fig. 2). While the residence time of estuarine water in Dan'ao River was short, the continuous nutrient transport by upstream freshwater and groundwater kept the high pollution level of Dan'ao River water. Therefore, future environmental control measures should control not only upstream input but also groundwater discharge from both sides of the river. Lastly, the growth of mangrove plants may affect the activities of radium isotopes and nutrient concentrations. For example, Wang and Du (2016) found the relatively high radium activities (224Ra ranged from 281 to 581 dpm 100 L−1, 223Ra from 8.14 to 18.9 dpm 100 L−1) in the mangrove area. In this study, much higher activities of 224Ra (1424–4388 dpm 100 L−1) and 223Ra (30–53 dpm 100 L−1) in groundwater were also found at the downstream area, where mangroves grew well (Fig. 5 and supporting information Table S1). Similarly, Sadat-Noori et al. (2017) also reported that radium activities increased in parts of the estuary surrounded by mangroves based on the radium isotope spatial survey. The previous research revealed that the freshwater availability and sediment stratification (i.e., the surface mud layer overlying the bottom sand layer) may be the main hydrogeological factors critical to the mangrove development (Xia and Li, 2012). The bald mudflat is most probably due to the lack of enough terrigenous freshwater for generating a brackish soil condition essential to mangrove growth. The recent research by Xiao et al. (2019b) also emphasized that the bottom sand layer plays an important pathway for terrigenous freshwater transport. Therefore, in the mangrove wetlands, the fresh groundwater discharge can consequently decrease the groundwater salinity to more comfortable levels for the release of radium isotope from the particles. Further, our recent studies reported that the mangrove wetland is a hot region for nitrogen removal by microbial denitrification due to the existence of anoxic environment and abundant organic matters (Xiao et al., 2018). Therefore, planting mangroves along Dan'ao River, especially at the estuary area, could be an effective method to improve the water quality of river water and decrease nutrient inputs into the coastal water. 5. Conclusion A double-criteria approach combining hydrological investigations and isotopic tools has proven useful to investigate the role of groundwater discharge in Dan'ao River, and may be useful in similar settings worldwide. The qualitative and statistical analyses of the time series of physical-chemical data and spatial distribution of naturally occurring radium isotopes, together with the information derived from the current monitoring system in Dan'ao River, contributed to a comprehensive knowledge of average water residence time (~1.15 days) and groundwater discharge rate (2.46 × 105 m3 d−1), comparable to the

13

upstream river discharge rate. The conclusion derived from the above joint analysis is that groundwater discharge in Dan'ao River acts as an invisible but important nutrient source, continually carrying nutrients to river water and sustaining pollution state. The nutrient inputs with an average DIN:DIP ratio of as high as 190 from groundwater can potentially affect the riverine and marine nutrient structures. The source of nutrients in groundwater was speculated originating from the discharge of human and industrial wastewater along Dan'ao River. In overall, these investigations would allow environmental managers to assess the magnitude of groundwater discharge and its nutrient contributions into the Dan'ao River and highlighted the significance of groundwaterderived nutrients. Still, additional scientific efforts are needed to acquire in-depth knowledge about nutrient budgets in riverine and estuarine system. There are still large room for unaccounted portions in calculating the contributions of groundwater-derived nutrients such as the desorption of resuspended particles in highly polluted river, as well as the nutrient loadings derived from sedimentary processes. Moreover, the long-term investigations make it possible to grasp the variation trend of water pollution degree and define specific actions for a correct management of the water resources.

Acknowledgments This research was supported by the Key Program of National Natural Science Foundation of China (Grant No. 41430641), the China Postdoctoral Science Foundation (Grant No. 2018M640730) and the National Basic Research Program of China (“973” Program, Grant No. 2015CB452902). The fieldwork and Laboratory experiment were completed with the assistance of two project teams, including China University of Geosciences (Beijing) (Wenjing Qu, Meng Zhang, Xueqian Guo, Ping Yuan and Xiaobo Feng) and Southern University of Science and Technology (Manhua Luo and Xiaolang Zhang). The instrument and firm names used in this paper are just for descriptive purposes and do not imply a commercial purpose or get endorsed by the authors or their employers. Appendix A. Supplementary data Supplementary data to this article can be found online at https://doi. org/10.1016/j.scitotenv.2019.133872.

References Alley, W.M., Healy, R.W., LaBaugh, J.W., Reilly, T.E., 2002. Flow and storage in groundwater systems. Science, 296(5575): 1985–1990. https://doi.org/https://doi.org/10.1126/ science.1067123. Bowen, J.L., Valiela, I., 2001. The ecological effects of urbanization of coastal watersheds: historical increases in nitrogen loads and eutrophication of Waquoit Bay estuaries. Can. J. Fish. Aquat. Sci. 58, 1489–1500. https://doi.org/10.1139/f01-094. Bricker, S.B., Clement, C.G., Pirhalla, D.E., Orlando, S.P., Farrow, D.R.G., 1999. National Estuarine Eutrophication Assessment: Effects of Nutrient Enrichment in the Nation's Estuaries. NOAA, National Ocean Service, Special Projects Office and the National Centers for Coastal Ocean Science, Silver Spring, MD (71 pp). Brodie, R., Sundaram, B., Tottenham, R., Hostetler, S., Ransley, T., 2007. An Overview of Tools for Assessing Groundwater–Surface Water Connectivity. Bureau of Rural Sciences, Canberra, p. 133. http://www.brs.gov.au. Burnett, W.C., Bokuniewicz, H., Huettel, M., Moore, W.S., Taniguchi, M., 2003. Groundwater and porewater inputs to the coastal zone. Biogeochemistry 66, 3–33. https://doi. org/10.1023/B:BIOG.0000006066.21240.53. Burnett, W.C., Santos, I.R., Weinstein, Y., Swarzenski, P.W., Herut, B., 2007. Remaining uncertainties in the use of Rn-222 as a quantitative tracer of submarine groundwater discharge. A New Focus on Groundwater-Seawater Interactions (Perugia, Italy). Cai, P., Shi, X., Hong, Q., Li, Q., Liu, L., Guo, X., Dai, M., 2015. Using 224Ra/228Th disequilibrium to quantify benthic fluxes of dissolved inorganic carbon and nutrients into the Pearl River Estuary. Geochim. Cosmochim. Acta 170, 188–203. https://doi.org/ 10.1016/j.gca.2015.08.015. Calver, A., 2001. Riverbed permeabilities: information from pooled data. Ground Water 39 (4), 546-533. https://doi.org/10.1111/j.1745-6584.2001.tb02343.x. Capone, D.G., Bautista, M.F., 1985. A groundwater source of nitrate in nearshore marine sediments. Nature 313, 214–216. https://doi.org/10.1038/313214a0.

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