Estimating submarine groundwater discharge and associated nutrient inputs into Daya Bay during spring using radium isotopes

Jing-yan Gao,Xue-jing Wang,Yan Zhang,Hai-long Lib,,*

aSchool of Environment,Harbin Institute of Technology,Harbin 150001,China

bSchool of Environmental Science and Engineering,Southern University of Science and Technology,Shenzhen 518055,China

cSchool of Water Resources and Hydropower Engineering,Wuhan University,Wuhan 430072,China

dState Key Laboratory of Biogeology and Environmental Geology,China University of Geosciences,Beijing 100083,China

Abstract Daya Bay,a semi-enclosed bay in the South China Sea,is well known for its aquaculture,agriculture,and tourism.In recent years,many environmental problems have emerged,such as the frequent(almost yearly)occurrence of harmful algal blooms and red tides.Therefore,investigations of submarine groundwater discharge(SGD)and associated nutrient inputs to this bay have important theoretical and practical significance to the protection of the ecological system.Such a study was conducted using short-lived radium isotopes223Ra and224Ra.The estimated SGD fluxes were 2.89×107m3/d and 3.05×107m3/d based on223Ra and224Ra,respectively.The average SGD flux was about 35 times greater than that of all the local rivers.The SGD-associated dissolved inorganic nitrogen(DIN)and dissolved inorganic phosphorus(DIP)fluxes ranged from 1.95×106to 2.06×106mol/d and from 5.72×104to 6.04×104mol/d,respectively.The average ratio of DIN to DIP fluxes in SGD was 34,much higher than that in local rivers(about 6.46),and about twice as large as the Red field ratio(16).Our results indicate that SGD is a significant source of nutrients to the bay and may cause frequent occurrence of harmful algal blooms.This study provides baseline data for evaluating potential environmental effects due to urbanization and economic growth in this region.

Keywords:Submarine groundwater discharge(SGD);Radium isotopes;Radium mass balance model;SGD-associated nutrient fluxes;Daya Bay

1.Introduction

Coastal zones with increasingly dense human occupation are at the complex and dynamic interface between the land and the ocean.As an important process of land-ocean interaction and a component of the hydrological cycle,submarine groundwater discharge(SGD)has been widely recognized as a significant source of water(Wang et al.,2015)and an important pathway for dissolved material(e.g.,nutrients,metals,and carbon)transport from land to the ocean(Taniguchi et al.,2002;Peterson et al.,2009;Knee et al.,2016;Moran et al.,2014).Owing to spatial and temporal variations,SGD is very difficult to measure and evaluate.Nonetheless,SGD and associated nutrient fluxes,in some regions,have been shown to rival those from local surface waters(Swarzenski et al.,2007;Hwang et al.,2010;Knee et al.,2016;Zhou and Boyd,2015).Thus,SGD is very important to the marine geochemical cycle of elements such as nutrients and metals,and it can lead to various environmental problems in coastal zones(Moore,1997,2006;Beck et al.,2007;Wudtisin and Boyd,2005).Numerous studies have shown that the nutrient inputs to coastal water through SGD maytriggerharmfulalgalblooms,whichhave negative impacts on the marine environment and economy(Lee and Kim,2007;Lee et al.,2009;Waska and Kim,2011).

The definition of SGD,from Burnett et al.(2003),is flow of water on continental margins from the seabed to the coastal ocean,regardless of fluid composition or driving force.Driven by both terrestrial and marine forcing components,SGD comprises terrestrial fresh groundwater and circulated seawater.The composition of SGD,however,differs from simple mixing of terrestrial fresh groundwater and circulated seawater,since biogeochemical reactions in the aquifer modify its chemistry(Moore,2010).The terrestrial driving force of SGD consists of the inland hydraulic gradients,which result from the difference in water level between terrestrial groundwater and seawater.The marine driving forces are complicated and include density gradients(Santosa et al.,2012;Gonneea and Charette,2014),waves(Li and Barry,2000;Xin et al.,2010),tidal pumping(Li et al.,1999,2008;Li and Jiao,2003;Li et al.,2008;Li and Jiao,2013),geothermal heating(Moore,2010),storms(Moore and Wilson,2005;Wilson et al.,2011),and seabed topography(Konikow et al.,2013).Although driven by a combination of these spatially and temporally terrestrial and marine forces,SGD at large scales can be evaluated quantitatively using natural geochemical tracers such as radon(Burnett and Dulaiova,2003;Tse and Jiao,2008;Wang et al.,2017;Charette et al.,2013)and radium isotopes(Moore and Arnold,1996;Moore et al.,2008;Kim et al.,2005;Lee and Kim,2007;Lee et al.,2012;Peterson et al.,2013;Stewart et al.,2018).The nutrient inputs from aquaculture,urbanization,and anthropogenic discharge have increased in recent decades in Daya Bay,a semi-enclosed bay located in the northwestern part of the South China Sea,which is confronted with severe environmental pollution problems(Wang et al.,2008).In particular,it has experienced a high frequency of algal blooms and red tides over the past few decades(Wang et al.,2017).Thus,the sustainable management of the coastal environment in Daya Bay is a major challenge due to accelerating anthropogenic pressures in the area.However,few studies have investigated SGD fluxes and associated material inputs at large scales around Daya Bay(Wang et al.,2017).More importantly,SGD has long been ignored in the evaluation of the ecological environment in this region.

In this study,we used the short-lived radium isotopes223Ra(with a half life of 11.6 d)and224Ra(with a half life of 3.66 d)to estimate the fluxes of SGD and the associated nutrient inputs to Daya Bay.We obtained the spatial distribution patterns of223Ra and224Ra in the bay.The water mass age of coastal water was calculated with a water mass age model of radium.The fluxes of SGD into the bay were estimated using a radium mass balance model with the derived water mass age.The fluxes of nutrients into the bay through SGD were determined by combining the nutrient concentration levels in groundwater.Their environmental and ecological effects and implications are discussed below.

2.Methodology

2.1.Study area

DayaBay,asemi-enclosedbay,isoneofthelargestandmost important gulfs of the South China Sea.It is located from 22°31′43′′Nto22°49′48′′N,andfrom114°30′Eto114°49′48′′E,in the eastern part of Guangdong Province,China(Fig.1).The bay covers an area of 556 km2,with a coastline of about 51 km and an average width of 20.7 km.About 60%of the area in the bay is less than 10 m deep(Wang et al.,2006).

Daya Bay is tropical,but close to the temperate zone.It has a subtropical monsoon and monsoon humid climate with an average annual temperature of 22°C.The seasonal variation of wind direction and wind speed is significant,especially at the mouth of the bay.The northeast winds are the main winds in spring and winter,with the southwest winds prevailing in summer and the easterly winds in autumn,with an average annual wind speed of 2.7 to 2.8 m/s.According to data from the European Center for Medium-Range Weather Forecasts(ECMWF),the average annual precipitation in this area is between 1800 and 2000 mm,and most of the precipitation occurs in summer.The evaporation capacity is stronger in summer than in winter,with an average annual evaporation of 665.6 mm.

Daya Bay faces the South China Sea and the tidal wave intrusion in the South China Sea is greatly in fluenced by the topography.The tidal current in this region is dominated by irregular semidiurnal tides and the mean and maximum tidal ranges are 1.03 m and 2.60 m,respectively.The average tidal range during the sampling period(March 26 through 29,2016)was 1.44 m.There is no large river running into the bay,but only some small seasonal rivers discharging into the bay along the northern coast.The Dan'ao River,with a mean flux of 6.20×105m3/d,is the largest one in the northwestern part of the bay.

Fig.1.Study area and sampling stations.

Table 1 223Ra activity(A223),224Ra activity(A224),and salinity(S)in seawater.

Table 1(continued)

2.2.Sampling and chemical analysis

The field work was conducted on March 26 to 29,2016.We collected 16 coastal groundwater samples at ten stations and four river water samples at four stations along the shoreline from March 26 through 27,2016,as well as 64 seawater samples with different depths at 27 stations from March 26 through 29,2016.According to the different water depths at each station,the seawater was divided into one to five layers for radium sampling.The sampling depths of each station are listed in Table 1.

The seawater samples were pumped through a 0.45-μm filter to remove suspended particulates.Then,the radium was extracted from the filtered water by passing the water through columns filled with about 25 g of manganese-coated acrylic fiber,which were produced according to Moore(1976),with a flow rate below 1 L/min in order to ensure complete radium adsorption(Moore et al.,2008).Then,Mn- fibers were flushed with radium-free double deionized water to remove salts and were sent back to the laboratory for analysis.Groundwater samples(5-15 L)were collected with pushpoint samplers inserted into sediments at depths of about 0.5-1.5 m and processed like river samples(Moore,2006).In order to test the extraction efficiency of Mn- fiber,a groundwater sample was selected and passed through two Mn- fibers connected in series.For groundwater and river water,500-mL samples were filtered through a 0.45-μm membrane filter and collected for nutrient analysis.These samples were stored at 4°C until the measurements were made.

The physical and chemical properties of water samples(e.g.,salinity and temperature)were measured in situ using a hand-held HANA multi-parameter measuring instrument.Nutrients(,,,and)of groundwater/river water samples were analyzed with a spectrophotometer at the National Research Center for geoanalysis.The sum of,,andconcentrations was defined as dissolved inorganic nitrogen(DIN)and the concentration ofwas regarded as dissolved inorganic phosphorus(DIP).The shortlived radium isotopes,223Ra and224Ra,were measured with radium-delayed coincidence counters(RaDeCC)(Moore and Arnold,1996).The measurement of224Ra was completed within four days of the sampling to avoid significant decay.Then,223Ra measurements were performed after two224Ra half-lives after the sampling to avoid interference from224Ra;an attempt was made to complete the measurements within ten days.After a month or so,a second224Ra measurement was taken in order to correct the224Ra produced by the228Th(with a half life of 1.9 years)decay and obtain the initial excess224Ra activity.The uncertainties in the detection of223Ra and224Ra were 7%and 12%,respectively(Moore and Arnold,1996;Moore and Cai,2013;Garcia-Solsona et al.,2008).

2.3.Radium mass balance model

In order to quantify the fluxes of SGD into Daya Bay,a radium mass balance model was developed for this system.Under steady-state conditions,the inputs of radium to the bay should be balanced by losses.The major sources of the radium isotopes include riverine input(Ir),submarine sediment diffusion(Ised),desorption from suspended particulate matter(SPM)(ISPM),atmospheric dust input(Idust),and SGD input(ISGD).The sinks include loss from tidal mixing with the opensea water(Imix)and radioactive decay(Idec).The mass balance equation of radium isotopes can be described as follows:

2.4.Water mass age model

Water mass age is an important physical parameter for evaluation of the exchange characteristics of water.This parameter is essential to assessing land-coastal area nutrient budgets as well as the sensitivity of the coastal ecosystem to pollutant loadings(Brooks et al.,1999).One can estimate water mass age using the radioactive decay equation derived by Moore(2000):

where the subscript“obs”means the observed value at each observation station;the subscript “i” means the initial A224/A223value(endmember of groundwater samples);and λ223and λ224are the decay constants in d-1of223Ra and224Ra,respectively.Solving Eq.(2)for water mass age(τ)yields the following:

The equations above are based on the following assumptions:(1)the radium source is mainly groundwater and it has a stable A224/A223value over spatial and temporal scales in the study area;(2)the inputs from rivers and bottom sediments can be neglected;and(3)the short-lived radium activity in the open sea is relatively low and negligible.

3.Results

3.1.Radium activities and salinity in all samples

Theactivities of223Ra and224Ra togetherwithsalinity forall the seawater,coastal groundwater,and river water samples are listed in Table 1,Table 2,and Table 3,respectively.The activities of223Ra range from 0.59 to 7.17 dpm per 100 L with an average of 1.77 dpm per 100 L(n=63,where n represents the number of seawater samples obtained)in seawater,from 2.69 to 139.09 dpm per 100 L with an average of 25.88 dpm per 100 L(n=15)in coastal groundwater,and from 0.42 to 1.52 dpm per 100 L with an average of 0.86 dpm per 100 L(n=4)in river water.The corresponding values for224Ra range from 13.09 to 140.10 dpm per 100 L with an average of 35.78 dpm per 100 L(n=64)in seawater,from 5.53 to 7882.97 dpm per 100 L with an average of 1319.05 dpm per 100 L(n=16)in groundwater,and from 6.13 to 64.13 dpm per 100 L with an average of 29.49 dpm per 100 L(n=4)in river water.

Salinity in coastal groundwater ranges from 0.008%in fresh water to 2.942%in saline groundwater(Table 2).High223Ra and224Ra activities in saline groundwater may be due to a large supply from parent isotopes(228Th and227Ac)in solids and desorption from the adsorbed matters(Kiro et al.,2012;Sturchio et al.,2001).The relationships between223Ra and224Ra activities and salinity in all samples are shown in Fig.2.Higher223Ra and224Ra activities were observed in the coastal groundwater than in seawater and river water.

Table 2 223Ra and224Ra activities and salinity in coastal groundwater.

Table 3 223Ra and224Ra activities and salinity in river water.

Fig.2.Plots of223Ra and224Ra activities versus salinity in all samples.

3.2.Nutrients in coastal groundwater,river water,and seawater

The concentrations of nutrients in coastal groundwater,river water,and seawater samples are given in Table 4.Also,the proportion ofis greater in the DIN of the river water.Coastalgroundwatersampleshave DIN concentrations ranging from 0.35 to 182.14 μmol/L,and DIP concentrations ranging from 0.41 to 5.29 μmol/L;river water samples have DIN concentrations ranging from 122.36 to 143.82 μmol/L,and DIP concentrations ranging from 0.70 to 59.35 μmol/L;and seawater samples have DIN concentrations ranging from 3.57 to 29.60 μmol/L,and DIP concentrations ranging from 0.28 to 1.66 μmol/L(Table 4).The results show thataccounts for the largest proportion of DIN in both coastal groundwater and river water.The DIN and DIP concentrations in coastal groundwater are much higher than in river water and seawater,which suggests that the coastal groundwater is a significant source of nutrients in Daya Bay.Moreover,the three types of water are ranked in the following descending order according to the average ratio of DIN to DIP fluxes:coastal groundwater(with a ratio of 34:1),seawater(with a ratio of 22:1),and river water(with a ratio of 6.5:1).

4.Discussion

4.1.Spatial distribution of radium isotopes and salinity

The223Ra and224Ra activity levels are higher in coastal groundwater than in seawater and river water(Fig.2),which suggests that the groundwater discharge will contain large quantities of223Ra and224Ra.In addition,a significant trend can be observed,which is that both223Ra and224Ra activities increase as the salinity increases for coastal groundwater and river water.This is mainly due to the fact that223Ra and224Ra are adsorbed on particles(e.g.,suspendedparticulate matter in river water and sediments)in fresh water,but they can desorb from particles in saline water.That is,the radium isotopes show low desorption from the absorbed phase in low salinity environments and easily desorb when salinity increases(Luo et al.,2000,2014;Sturchio et al.,2001;Kiro et al.,2012;Gonneea et al.,2008).Such characteristics of radium isotopes make them good tracers for investigation of SGD.

Table 4 Nutrient concentrations in coastal groundwater,river water,and seawater samples.

Figs.3-5 show the spatial distributions of223Ra and224Ra activities and salinity in the surface and bottom water of Daya Bay.It can be seen that in the surface and bottom water,both223Ra and224Ra have relatively higher activity levels in the nearshore area than at the mouth of the bay.In the gulf,the highest activity occurs in the northeast,and there is a trend of decreasing activity from the northeast to the southwest.However,regardless of whether at the surface or bottom,the activity gradient of224Ra is significantly greater than that of223Ra.This may be related to the half-life and/or the diffusion coefficient of water.

The salinity of seawater can affect the marine physics phenomena such as water mass,thermocline,and current(Liu et al.,2003).The fluctuation of salinity also in fluences the stability of the ecosystem,and directly affects the growth and reproduction of animals and plants.The distribution of salinity(Fig.5)is generally contrary to the distribution of radium activities.The data show a low salinity near the shore,a high salinity at the mouth of the bay,and a gradual increase from north to south.

4.2.Water mass age estimation

Fig.3.Distributions of A223in surface and bottom water of Daya Bay.

Fig.4.Distributions of A224in surface and bottom water of Daya Bay.

Fig.5.Distributions of salinity in surface and bottom water of Daya Bay.

Fig.6.Activity ratio of224Ra to223Ra in coastal groundwater.

Fig.6 shows the relationship between224Ra and223Ra activities in coastal groundwater.Since the223Ra activity was not determined for the GW1 sample,this sample was excluded from the 16 coastal groundwater samples in radium analysis.The coastal groundwater samples have a stable A224/A223value over spatial and temporal scales.In Eq.(1),we assume that the radium isotopes are mainly from groundwater discharge and other sources can be neglected.Thus,to avoid underestimating water mass age and to obtain conservative SGD estimates,the maximum slope of the fitted curve 78.2(the red line in Fig.6)was used as the A224/A223value in coastal groundwater for the calculation of the water mass age.The uncertainty of the initial A224/A223value determined by standard error propagation was 34%,which could lead to an average A224/A223value of 78.2±26.6.Using the water mass age model,we then calculated the water mass age to be 10.47±2.74 d.The stated uncertainty(changing one standard deviation)is based on calculation of statistics.

4.3.Riverine input

The radium flux from riverine input to the coastal zones included the dissolved radium isotopes in river water and the desorbed radium isotopes on riverine suspended particles.The suspended particles included the dust particles from atmospheric deposition.The desorbed radium on suspended particles,however,could be ignored in this system due to the low discharge rates with low particle concentration.Thus,the total radium flux from local rivers could be calculated by the following equation:

where Qr，i(m3/d)is the ith river discharge,and Ar，i(dpm per 100 L)is the activity of radium isotopes in the ith river.The activities of223Ra and224Ra and discharge rates of the four local rivers are listed in Tables 3 and 5,respectively.Based on Eq.(4),the total fluxes of223Ra and224Ra from local rivers can be estimated to be 1.08×107dpm/d and 4.36×108dpm/d,respectively(Table 5).

4.4.Radium desorption from SPM and atmospheric dust

The radium isotope inputs from SPM are associated with the concentration of SPM in seawater,the parent isotope concentrations in SPM,the decay constants,and the fraction of radium released in SPM.The concentration of SPM in seawater was approximated by the data from Mirs Bay,which is located about 4 km southwest of Daya Bay.The concentration of SPM in Mirs Bay was 3.8 mg/L,as obtained from the EnvironmentalProtection Department(EPD,2016),Hong Kong.The concentrations of the parent isotopes227Ac and228Th in SPM were assumed to be 0.01 dpm/g and 2 dpm/g,respectively(Moore et al.,2011).Because of high mobility in the saline environment and the quite small portion of SPM-released radium(Luo et al.,2000),it was reasonable to assume that the223Ra and224Ra produced by the decay of parent isotopes from SPM were completely released from the particles(Moore et al.,2011).The223Ra and224Ra fluxes from SPM desorption could be calculated to be 6.69×106dpm/d and 3.58×107dpm/d,respectively.

Radium can be desorbed from the atmospheric dust when it is deposited in the ocean.The atmospheric dust input to all ofDaya Bay in spring was estimated to be 1.22×107g/d(Du et al.,1994).Using the maximum desorption rates of223Ra and224Ra from dusts reported by Moore et al.(2011),i.e.,0.01 dpm/g for223Ra and 2 dpm/g for224Ra,the atmospheric inputs of223Ra and224Ra to the entire bay were estimated to be 1.22×105dpm/d and 2.44×107dpm/d,respectively,which are two to three orders of magnitude lower than those from local rivers.

Table 5 Parameters and values used in steady state mass balance model for223Ra and224Ra.

4.5.Mixing and decay losses

The main sinks are mixing loss and decay loss in this system.Using the water mass ages estimated in section 4.1 and the activity difference between embayment water and open-sea water,the mixing loss can be obtained.The flushing time refers to the time required for all the water in the bay to be refreshed once.This is the ratio of the volume of the bay to the rate of flushing,which is an important factor in describing the characteristics of embayment water exchange.In this study,water mass age was used instead of the flushing time.The mixing loss can be determined by the following equation:

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The average activity of four low-activity seawater stations(S13,S14,S26,and S27)at the bay mouth was chosen as the background value(Table 5).Based on the approach of Peterson et al.(2008),this value already included the contribution of sediment diffusion,so we did not consider the diffusive inputs of radium from sediments in Eqs.(2)and(3).

In order to obtain the water volume and radium inventory of Daya Bay,we added 51 points along the coastline(C1 through C51 in Fig.7)where the water depth was zero.Daya Bay was divided into 93 small triangles(Fig.7).Using the longitude and latitude of each triangle vertex,the area of each triangle was calculated.Then,the seawater volume within each triangle was calculated as the product of the triangle area and the average depth of its three vertices.Thus,the area and volume of seawater could be obtained.

The radium inventory in the study area was obtained by summing up the 93 triangle data,each of which was obtained by multiplying the average radium activity at the three vertexes of a triangle with the volume of the triangle.The radium activity at each vertex is the average of values at different sampling depths at this point.Using the value of 10.47 d for the water mass age,the mixing loss could be based on Eq.(5).The mixing losses of223Ra and224Ra were 2.42×109dpm/d and 7.29×1010dpm/d,respectively.The parameters used to calculate SGD are listed in Table 5.The decay loss of radium could be obtained by the product of the inventory of radium isotopes in the bay and its decay constant.

Fig.7.Triangle elements for calculation of radium inventory in Daya Bay.

4.6.SGD estimation with radium mass balance model

Table 5 shows values of all the sources and sinks of radium used in the radium mass balance model.Substituting these parameters into the radium mass balance model(Eqs.(1),(4),and(5)),the radium fluxes from SGD can be easily converted to SGD fluxes through division by the radium activity in the groundwater endmember.The average radium activity levels,25.88 dpm per 100 L for223Ra and 1319.05 dpm per 100 L for224Ra,were used in the model as the groundwater radium endmembers.The calculated SGD fluxes were 2.89×107to 3.05×107m3/d based on223Ra and224Ra,which are much larger than the local river flux.There are some inherent uncertainties in this model,mainly originating from the selection of the groundwater endmember,background Ra activity,and water mass age.In order to evaluate the uncertainty caused by the groundwater endmember,the endmember value was transformed by a standard deviation,which led to a 38%variation of the SGD flux.In this case,the SGD results were(2.89±1.10)×107m3/d for the223Ra mass balance model and(3.05±1.16)×107m3/d for the224Ra mass balance model.If a longer water mass age(13.21 d)was used,the SGD fluxes decreased by 4%and 7%for the223Ra and224Ra models,respectively.Using a shorter water mass age(7.73 d),the SGD fluxes increased by 7%and 12%for the223Ra and224Ra models,respectively.In order to evaluate the uncertainty caused by open sea water endmembers,the background activity values were changed by 20%,which could lead to 1%and 11%variations of the SGD flux based on223Ra and224Ra,respectively.

4.7.Nutrient fluxes

Surface water discharges have long been regarded as the most significant sources of pollution in Daya Bay(Wang et al.,2017).However,with the increasing knowledge of SGD,many studies have shown that SGD can transport large fluxes of nutrients from land to the ocean because SGD often contains higher concentrations of nutrients compared to surface water(Moore et al.,2006;Lee and Kim,2007;Chen et al.,2007;Xu et al.,2013).Thus,the large volume of SGD flowing into Daya Bay confirms its importance in delivering nutrients to the bay.If one wants to understand how the coastal ocean functions and how it responds to anthropogenic or natural perturbations,accurate insight into the magnitude of nitrogen and phosphorus fluxes associated with SGD is needed(Mackenzie et al.,2002;Rabouille et al.,2001).In this study,the analysis ofnutrientconcentrations in coastalgroundwater suggested that SGD is a significant source of the nutrients in Daya Bay.The most common approach for estimating SGD-associated nutrient fluxes is to multiply SGD flux by nutrient concentrations in the groundwater endmember,which is the average concentration of nutrients in all groundwater samples(Table 6).The SGD-associated nutrient fluxes were calculated and are shown in Table 6.

For comparison,nutrient fluxes from local rivers were also determined by multiplying the river discharge and by concentrations in river waters.The results are also shown in Table 6.It is clear that SGD-associated nutrient fluxes in Daya Bay are significantly higher than those from local rivers.The nutrients in the coastal waters are closely related to human activities,including artificial fertilization,as well as industrial and agricultural wastewater discharge.These human activities change the quality of groundwater and river water,and affect the stability of the coastal ecosystem(Destouni et al.,2008).The average ratio of DIN to DIP fluxes in groundwater was determined to be about 34,which was about twice the Red field ratio(16),indicating that SGD makes Daya Bay a phosphatelimited environment.

We can compare the nutrient fluxes in Daya Bay to those in other regions in China.Luo et al.(2014)employed short-lived radium isotopes(223Ra and224Ra)to evaluate the SGD and associated nutrient fluxes in Tolo Harbor.They determined the nutrient fluxes via SGD to be 0.94-2.19 mmol/(m2·d)for DIN and 0.007-0.039 mmol/(m2·d)for DIP.Zhang(2016)used the radon isotope(222Rn)to estimate the SGD and associated nutrient fluxes into Laizhou Bay.The nutrient fluxes from SGD were 13.17 mmol/(m2·d)for DIN and 1.30 mmol/(m2·d)for DIP.If using the same unit,the SGD-associated nutrient fluxes in our study were 3.52-3.71 mmol/(m2·d)for DIN and 0.10-0.11 mmol/(m2·d)for DIP.Both DIN and DIP fluxes from SGD in Daya Bay are greater than in Tolo Habor,but an order of magnitude lower than in Laizhou Bay.This indicates that coastal groundwater pollution may be more serious in Laizhou Bay.

Although these data and calculation processes have some limitations,this study provides some important and preliminary evaluations of SGD-associated nutrient fluxes and potential environmental effects.The SGD-associated nutrient inputs into Daya Bay cannot be neglected in future environment protection and management measures and initiatives.

5.Conclusions

In this study,we used a steady state mass balance model of short-lived radium isotopes(223Ra and224Ra)to evaluate theSGD flux and SGD-associated nutrient fluxes based on a field investigation in March 2016 in Daya Bay.The following conclusions can be drawn:

Table 6 Nutrient fluxes driven by SGD and river into Daya Bay.

(1)Both223Ra and224Ra had relatively higher activity levels in the nearshore area than at the mouth of the bay.The highest levels of activity occurred in the northeastern part of the bay,and the bay showed a trend of decreasing activity from the northeast to the southwest.The distribution of salinity was generally contrary to the distribution of radium activity,i.e.,there was low salinity near the shore and high salinity at the mouth of the bay with a gradual increase from north to south.

(2)TheaverageDINconcentrationwas0.35-182.14μmol/L for groundwater samples,and 122.36-143.82 μmol/L for river water samples.The average DIP concentration was 0.41-5.29 μmol/L for coastal groundwater samples,and 0.70-59.35 μmol/L for river water samples.Nitrate made up the largest proportion of DIN in both coastal groundwater and river water samples.

(3)The average water mass age was estimated to be 10.47 d based on the radioactive decay equation.

(4)The mass balance models of223Ra and224Ra in a steady state were established to calculate the SGD flux.The estimated SGD fluxes were 2.89×107to 3.05×107m3/d based on the223Ra and224Ra,respectively.The average SGD flux was about 35 times greater than that of all the local rivers.

(5)The SGD-associated DIN and DIP fluxes were estimated to be 1.95×106to 2.06×106mol/d and 5.72×104to 6.04×104mol/d,respectively.Both are higher than those of all the local rivers.The ratio of DIN to DIP fluxes in SGD was about 34,about twice as large as the Red field ratio(16),indicating a phosphate-limited environment.This may cause the frequent occurrence of harmful algal blooms.

In short,the in fluences of SGD and SGD-associated nutrient inputs on coastal ecological environments cannot be neglected.Our results show that SGD may cause the frequent occurrence of harmful algal blooms.The findings from this study must be considered in management and protection of coastal environments in Daya Bay.