Continental Shelf Research 53 (2013) 63–76

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Continental Shelf Research

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n Corr

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Research papers

Submarine groundwater discharge in the Sarasota Bay system: Itsassessment and implications for the nearshore coastal environment

B.M. Mwashote a,n, M. Murray a, W.C. Burnett a, J. Chanton a, S. Kruse b, A. Forde b,1

a Oceanography Program, Department of Earth, Ocean and Atmospheric Science, Florida State University, 117 N. Woodward Avenue – 323OSB, P.O. Box 3064320,

Tallahassee, FL 32306, USAb Department of Geology, University of South Florida, 4202 E. Fowler Ave, Tampa, FL 33620, USA

a r t i c l e i n f o

Article history:

Received 30 December 2011

Received in revised form

7 December 2012

Accepted 8 December 2012Available online 20 December 2012

Keywords:

Groundwater discharge

Seepage meters222Rn and CH4 geochemical tracers

Subseafloor resistivity

Nutrient flux

Sarasota Bay Florida

43/$ - see front matter & 2012 Elsevier Ltd. A

x.doi.org/10.1016/j.csr.2012.12.002

esponding author. Tel.: þ1 850 644 6700; fax

ail addresses: mwashote@ocean.fsu.edu, mwa

washote), skruse@usf.edu (S. Kruse), aforde@

ow at United States Geological Survey, St. Pe

Center, 600 4th St. South, St. Petersburg, FL

a b s t r a c t

A study was conducted from July 2002 through June 2006 in order to assess the significance of

submarine groundwater discharge (SGD) to Sarasota Bay (SB), Florida. The assessment approaches used

in this study included manual seepage meters, geochemical tracers (radon, 222Rn and methane, CH4),

and subseafloor resistivity measurements. The estimated SGD advection rates in the SB system were

found to range from 0.7 to 24.0 cm/day, except for some isolated hot spot occurrences where higher

rates were observed. In general, SGD estimates were relatively higher (5.9–24.0 cm/day) in the middle

and south regions of the bay compared to the north region (0.7–5.9 cm/day). Average dissolved

inorganic nutrient concentrations within the SB water column ranged: 0.1–11 mM (NO2þNO3), 0.1–

9.1 mM (NH4) and 0.2–1.4 mM (PO4). The average N/P ratio was higher in the north compared to the

middle and south regions of the bay. On average, we conservatively estimate that about 27% of the total

N in the SB system was derived via SGD. The prevalence of shallow embayed areas in the SB system and

the presence of numerous septic tanks in the surrounding settlements enhanced the potential effects of

nutrient rich seepages. Statistical comparison of the quantitative approaches revealed a good

agreement between SGD estimates from manual seepage meters and those derived from the 222Rn

model (p¼0.67; a¼0.05; n¼18). CH4 was found to be useful for qualitative SGD assessments. CH4 and222Rn were correlated (r2¼0.31; a¼0.05; n¼54). Large scale resistivity surveys showed spatial

variability that correlates more clearly with lithology than with SGD patterns.

& 2012 Elsevier Ltd. All rights reserved.

1. Introduction

Sarasota Bay is a barrier island enclosed lagoon located on thesouthwest coast of Florida (United States), surrounded by the cityof Sarasota. Over the last five decades, due to increased anthro-pogenic pressure, Sarasota Bay has experienced a slow but steadydecline of its ecosystem’s general health. It has had problems ofwater and sediment quality, increased nitrogen and poor clarity,loss of seagrasses, wetlands and coastal habitats, overuse; andadverse effects on marine biota. The Sarasota city population hasgrown, with more residential, commercial and industrial devel-opment, creating pollution (Sarasota Bay Estuary Program, SBEP,2006).

The bay and beaches are the center of a multimillion dollartourism industry, the main industry in Sarasota. Due to population

ll rights reserved.

: þ1 850 644 2581.

shote@fo-pu.org

usgs.gov (A. Forde).

tersburg Coastal and Marine

33701, USA.

growth, seagrass and mangrove habitats have been altered toprovide for waterfront development, resulting in the loss of marinehabitat and pollution. Miles of shoreline have been replaced byseawalls and residential and commercial development, includingnumerous fill projects and dredging. Areas of the bay were dredgedto create navigable waterways and home sites. These processesresulted in increased storm water, wastewater, sediment andchemical contaminants being discharged into the bay.

At the time of this study, a large numbers of septic tanks in thearea resulted in elevated N loading, especially in Roberts Bay,Phillipi Creek, Blackburn Bay and Little Sarasota Bay. At the time,septic tanks were a major environmental health issue andsignificant source of N. Additionally, storm water runoff at thetime was estimated to contribute 56% of N load with 60% comingfrom residential areas (FGS, 1985; USGS, 2007).

Over 1400 different native species of plants and animals andabout 500,000 people are resident in Sarasota Bay area (SBEP,2006). Early efforts for rehabilitation of the Sarasota Bay environ-ment were focused on treating wastewater and storm water,which are the major nitrogen sources. The base flow (ground-water flow into tributaries) was then estimated to contribute

Fig. 1. Study area showing sampling sites within the Sarasota Bay system. For

purposes of the study, the area was divided into three regions: North Region (NR,

water volumeE80%), Middle Region (MR, water volumeE12%) and South Region

(SR, water volumeE8%). The assumed 200 m SGD regime area within the SB

system is�7.8 km2 (� 8% of the total SB area). The North Bay region lies on

latitudesZ27.34441N. Middle Bay (MB) is found within latitudes 27.3047–

27.34441N, while the South Bay region lies within latitudes 27.1250–27.30471N.

Table 1Estimates of physical characteristics of the Sarasota Bay system (SBEP, 2006; FGS

open file report 10 Geology of Sarasota Co., 1985).

Regionwithin SBsystem

Totalpassespresent

Averagelength(km)

Averagewidth(km)

Averagedepth(m)

Area(km2)

Estimatedresidencea

time (days)

North 2 19 5 2.5 75.1 5–12

Middle 2 4 3 2.5 11.1 5–12

South 1 6 2 1.5 10.5 3–7

a Estimates were made using a modified simple tidal prism model approach

described in Dyer (1973) and Dyer and Taylor (1973).

B.M. Mwashote et al. / Continental Shelf Research 53 (2013) 63–7664

8% of the nitrogen to the bay (SBEP, 2006). However, the resultsreported here will show that this is an underestimate given thatSGD was shown to contribute about 27% of N. Our estimates arebased on the regional nutrient concentrations in groundwater,associated with SGD flux determinations made via independentapproaches that were described in this study.

Several previous studies have documented the importance ofSGD in the supply of nutrients and other dissolved components tomany coastal environments (Valiela et al., 1990; Capone andSlater, 1990; Mwashote et al., 2010). However, actual mechan-isms driving the discharge can be quite varied (Bokuniewicz andPavlik, 1990). For instance, Lapointe et al., (1990) found signifi-cant inputs of nitrogen and dissolved organic phosphorous dis-charged to canals and surface waters in the Florida Keys, whichmay have been an important factor for initiating phytoplanktonblooms in the area. It was also suspected that nitrogen richgroundwater may have been responsible for nourishing algalmats in Bermuda (Lapointe and OConnell, 1989) as well as baysand reefs in Jamaica (D’Elia et al., 1981). SGD is particularlyimportant in these cases because shallow groundwaters areenriched in nitrogen species, often due to contamination fromseptic tanks (Corbett et al., 1999). Perhaps of even greatersignificance and historical importance is that groundwater con-taminated by bacterial pathogens from sewage and septic sys-tems was responsible for 63% of all water borne illness in the USduring the 1970s (Porter, 1985). More recently, Peeler et al.(2006) showed a correlation of elevated nitrate and caffeine levelsbeing linked to population centers and their associated waste-water treatment plants. Elsewhere, Paul et al. (1995) directlytraced sewage effluent from a septic tank into surface water inless than 12 h in Key Largo Florida, while Dillon et al. (2000) alsodocumented impacts on surface waters from sewage disposal.

While the potential for contaminated groundwater to havean impact on surface waters is greatest in coastal areas andrestricted bodies of water, the impact of groundwater into acoastal system is dependent on several variables. These includethe amount and type of nutrient enrichment in the groundwater,circulation, tidal flushing, porosity and permeability of the under-lying strata, hydraulic head and the corresponding groundwaterflow. Due to variability in many of these parameters, the exactlocation of discharge into coastal regions may be difficult todetermine by only monitoring the standard water quality con-stituents, such as nutrient concentrations or turbidity, or by theexclusive use of any one particular method.

1.1. Significance and objectives of study

As efforts to reduce surface water pollution continue and aresuccessful, possible SGD pathways of contamination will alsoneed to be understood. The main purpose of this study wastherefore to assess SGD in the Sarasota Bay system and determineif it plays a significant role in the water and nutrient budgets ofthe bay system with respect to other sources. In this work, threeindependent approaches were employed: manual seepage meters,natural tracers (222Rn, CH4), and subseafloor resistivity measure-ments. Together, these approaches were used in order to locate,characterize and quantify SGD rates within the bay system.

1.2. Study area: description of the Sarasota bay system

The Sarasota Bay system (SB system) extends from the north,Anna Maria Sound, to the south, Venice Inlet. The bay liesbetween barrier islands called keys that separate the body ofwater from the Gulf of Mexico. Longboat Key, Lido Key, Siesta Key,and Casey Key are the major keys that delineate the main baysystem and its smaller portions. Sarasota Bay has a watershed of

417 km2 of which 65% is uplands and 35% is wetlands. The SBsystem is about 26 km long and 6.1 km wide at the widest pointand has a surface area of about 97 km2 (SBEP, 2006; USGS, 2007).The two major portions are Sarasota Bay and Little Sarasota Bay,but there are many smaller creeks, embayments and bays. Fresh-water enters the bay system through small tidal bays and creeks,whose input includes storm water runoff and SGD. Major tribu-taries to the bay system are Whitaker Bay, Hudson Bay andPhillipi Creek. The highest concentration of septic tanks (approxi-mately 35,000) is found within Phillipi Creek catchment area(Lipp et al., 2001). Whitaker Bay receives advanced treatedwastewater effluent from the city of Sarasota municipal treat-ment plant (Dillon and Chanton, 2005). Numerous other bays andcanals are also found within the bay system. For reference, thestudy site (Fig. 1) was divided into three general bay regions:North, Middle and South.

The South Bay region comprises Roberts Bay (RB) and LittleSarasota Bay (LSB). The bay regions are generally all shallow,particularly the South Bay, less than 2 m, except for within theIntracoastal Waterway (Table 1). The North Bay is somewhatdeeper, up to 4 m in some areas. Passes are open at the North andMiddle Bay (NB and MB). The South Bay has only one pass (withinRB). Phillipi Creek is a tidal creek within the South Bay (withinRB). The land adjacent to Phillipi Creek had a high septic tankpopulation at one time (mostly currently replaced) that wasblamed in part, for the degradation experienced within RB.

B.M. Mwashote et al. / Continental Shelf Research 53 (2013) 63–76 65

The mean annual rainfall of the area is about 140 cm, primarilyfrom mid June to mid October. Only about 30–35% contributes tosurface water runoff, 5% is recharged into the groundwater and65–70% is lost through evapotranspiration (USGS, 2007). Most ofthe rain water enters the bay system as storm water runoff viacreeks and bays. Inlets provide for water exchange to Gulf ofMexico at Anna Maria Sound, Longboat Pass, New Pass, Big Passand Venice Inlet. The land around the bays is mostly flat andpoorly drained, with swamps, marshes and ponds throughout thearea. The water table is near the land surface in most areasnearby, and some areas are characterized by artesian flow (mainlyin the North region). Extensive natural drainage systems havebeen channelized. The surficial aquifer generally flows west andsouth. Below the sandy/shelly area is sandy limestone with acarbonate mud matrix, with varying amounts of clay, phosphaticsediments, dolomites and limestone (FGS, 1985).

2. Materials and methods

2.1. General approach

Previous research in the SB system identified areas of potentialgroundwater contamination in the southern bay (FGS, 1985;SBEP, 2006). Samples for radon and methane were collected fromthese areas in addition to other areas within the system. Radonsamples were analyzed within 4 days (about one half life) whilemethane samples were held in ice or refrigerated and analyzedwithin 2 weeks. Manual seepage meters were also deployedwithin the SB system in order to directly determine seepagerates, and resistivity surveys were conducted to assess areaswithin the SB system with freshwater in the shallow subsurface.

2.2. Radon measurements

The method for measuring 222Rn in grab samples of seawaterwas first developed by Broecker (1965) and modified by Key et al.(1979) and Mathieu et al. (1988). More recently a continuousradon monitor (CRM) approach was developed (Burnett et al.,2001, 2006). Both bottle sampling and the CRM approach wereused in this study.

2.2.1. 222Rn bottle technique

Radon samples were collected at several sampling sites peri-odically in (helium) evacuated 6 L high density polyethylenebottles on various occasions (a minimum of bimonthly interval)from July 2002 through to June 2006. There were 125 individualsamples and approximately 20% of these were duplicates. 222Rnsamples were collected about 0.3 m above the bottom using aperistaltic pump and Tygon tubing fitted into helium filled 6 lbottles. The tubing was flushed twice with ambient water beforefilling the bottles about 2/3 full and clamping off the intakeand vent hoses. Additional details on laboratory sampling andanalysis are as described in Burnett and Dulaiova (2003) andBurnett et al. (2006).

2.2.2. Continuous 222Rn mode (CRM) surveys

Data were also collected using a continuous radon monitor(CRM) for two survey transects during May 2003 and August 2004and two time series at a fixed sites: New College, Caples (NC), NRand Roberts Bay (RB), SR (Fig. 1). For the case of CRM surveys, theCRM system (consisting of Rad 7 radon monitor from DurridgeInc.) analyzes 222Rn from a constant stream of water passingthrough an air–water exchanger that distributes radon from arunning flow of water to a closed air loop. The air stream is fed toa commercial radon in air monitor which determines the

concentration of 222Rn by collection and measurement of thealpha emitting daughters, 214Po and 218Po. Since the distributionof radon at equilibrium between the air and water phases isgoverned by a well known temperature dependence, the radonconcentration in the water is easily calculated (Burnett et al.,2001; Burnett and Dulaiova, 2003).

2.2.3. Sediment equilibration experiments

Sediment samples were collected at 27 sites to estimate radonin pore waters. A grab sampler (Petite Ponar) was used to collectsediment samples which were placed into polythene samplingbags. The site number, date and time were recorded on thesample bag until analyzed. These samples were used for ‘‘sedi-ment equilibration’’ experiments to assess pore water 222Rnvalues and in deriving diffusive 222Rn flux estimations (Martensand Klump, 1980; Cable et al., 1996). Sediment subsamples ofapproximately 70 g were weighed and placed in a 250 mLErlenmeyer flask with 120 mL of radium free DI water. A stopperwith two clamped tubes was placed in the neck and the stopperwas sealed with marine sealant. The flasks were placed on ashaker table in a water bath for at least 30 days. Radon was thenmeasured using the extraction procedure described above. Degas-sing time was set at 60 min.

2.2.4. 222Rn and 226Ra calculations

Total 222Rn activities in water samples were calculated by thefollowing equation:

A222 ¼ R=ð3ELÞ � 1=e�lt1 xlt2= 1�e�lt2

� �ð2:1Þ

where

A222 activity of total 222Rn (dpm/L),R the net sample count rate per minute (cpm),E the total efficiency of the system (including stripping,

trapping, transferring, and cell counting efficienciesexpressed as a fraction). The factor of three accountsfor the two alpha emitting daughters as well as 222Rn,

L sample volume (L),l the radioactive decay constant for 222Rn (1.235 � 10�4/

min),t1 time from the beginning of sample degassing to begin-

ning of counting (min),t2 counting time (min).

The calculation of the radium activity is similar to that used for222Rn except that a correction was added for the radon ingrowthperiod as shown in the following equation:

A226 ¼ R=ð3ELÞx1= 1�e�lt1� �

e�lt2� �

Þxlt3= 1�e�lt3� ��

ð2:2Þ

where

A226 activity of 226Ra (dpm/L),t1 radon ingrowth time (the time from the end of the

initial degassing of the sample to the start of sampledeemanation, min),

t2 time from end of sample flushing to time counting isinitiated (min),

t3 counting time (min).

All other variables in the 226Ra equation are the same as thosediscussed for the initial 222Rn calculation. After both total 222Rn atthe time of sample analysis and 226Ra are determined, any‘‘excess’’ 222Rn present in the sample (222Rnex¼

222Rnt�226Ra)

may be corrected back to the time of sample collection by use of a

B.M. Mwashote et al. / Continental Shelf Research 53 (2013) 63–7666

standard decay equation, At¼Aoe-lt where t in this case representsthe time interval in between sample collection and analysis, i.e:

222Rno ¼222Rnt=e�lt ð2:3Þ

Fig. 2. Lee-type, manual seepmeter (Lee, 1977; Taniguchi et al., 2003). When

water seeps into the chamber it displaces water that is forced into a plastic bag

attached to a tube in the top of the drum. The change in volume over a measured

time interval provides the seepage rate.

2.2.5. Estimation of 222Rn from diffusion

Diffusive fluxes (Fdiff) from pore water profiles were estimatedaccording to two approaches. With Fick’s First Law adapted fromBerner (1980):

Fdiff ¼ ~Ds dC=dZ� �

ð2:4Þ

and also from the depth independent estimation model inMartens and Klump (1980):

Fdiff ¼ lDsð Þ1=2 Ceq2Co

� �ð2:5Þ

where

~¼sediment porosity,Ds¼effective wet sediment diffusion coefficient,dC/dZ¼gradient of 222Rn concentration at the sediment waterinterface,l¼decay constant for 222Rn,Ceq¼

222Rn in wet sediment at equilibrium with radium in thesediment (measured via sediment equilibration),Co¼

222Rn in the overlying water at sediment water interfacemultiplied by the sediment porosity to obtain a value corre-sponding to the 222Rn concentration in wet sediment.

For the estimation of Ds, we used the approximation from Penget al. (1974):

logDo ¼ 980=T� �

þ1:59 ð2:6Þ

where

Do¼molecular diffusion of radon through water,T¼temperature (in Kelvin, K),

Sediment tortuosity is then corrected for in order to obtain theeffective diffusion coefficient, DsE~Do (Ullman and Aller, 1982).

2.2.6. SGD estimates from 222Rn

When the CRM was used in a time series mode, generally theconcentration results (and thus inventory) were analyzed overshort time periods, for instance each hour or two. With integra-tion times this short, loss of radon by decay and inputs viadiffusion can usually be ignored. The flux of radon out of thewater column by atmospheric evasion was calculated using wellknown relationships of radon emanation to wind speed, tempera-ture, and concentration gradients (MacIntyre et al., 1995). Adjust-ments to inventories as a consequence of tidal variations wereeasily performed with measurements or estimates of the tidalstage and radon concentrations of incoming and outgoing waters.Radon inventories were generally normalized to mean tidalheight so this effect was discounted.

In order to convert to water fluxes (o, cm/day), the estimatedtotal 222Rn fluxes (dpm/cm2 day), Ftotal, is divided by the concen-tration of excess 222Rn (ex 222Rnpw, dpm/cm3) in the fluidsentering the system according to the mass balance ‘‘box model’’equation (Burnett and Dulaiova, 2003):

o cm=day� �

¼ Ftotal=ex222Rnpw ð2:7Þ

The model is similar to those used in previous radon studies(e.g., Corbett et al., 1999) in that it describes various source andsink terms for radon in the system.

2.3. Methane measurements

Methane samples were collected in dissolved oxygen bottlesand stored in ice until analysis. The tubing from the peristalticpump was placed into the bottom of the bottle and the water wasallowed to gently overflow for approximately three bottlevolumes before sealing. Methane samples were then analyzed inthe laboratory by the headspace equilibration technique(McAulffe, 1971; Chanton et al., 1989).

2.4. Seepage meter measurements

Groundwater seepage rates into surface water bodies are oftenmade using manual seepage meters. Manual seepage meters areopen ended chambers placed over the bay floor with a vent tubeto which a plastic sample bag is attached to collect groundwaterseeping from the bay floor (Fig. 2).

In this study we deployed several manual seepage meters atthree sites between May and July 2004. Deployment sites wereselected because they were in areas of suspected seepage andcould be accessed from shore.

During the manual seepage meter deployments in the field,plastic bags were pre-filled with 1 L ambient seawater beforedeploying them on the drum chambers which had been left for aninitial�4 h to achieve equilibration at the deployed site. Thisserves as a precautionary measure aimed at addressing measure-ment artifacts that can readily arise from frictional resistance andhead loss along the internal boundary of meter, attachment tube,reservoir bags as well as short term influx of water after theplastic bags have been attached to the seepage meter (Shaw andPrepas, 1989, 1990a, b; Shinn et al., 2002). The SGD flow rate, incm/day, was computed by dividing the change in volume (cm3) ofwater collected in the seepage bag by the cross section area (cm2)of the benthic chamber and dividing the result of this by the timetaken (hours converted into days), for the volume of water tocollect. Thus, net measured water volumes (in cm3), collected inthe bag after every�1 h on a known area (2550 cm2), yielded theseepage rate (cm3/cm2 day¼cm/day).

2.5. Resistivity survey

Resistivity surveys are designed to detect lateral and verticalvariability in the resistivity of the subsurface. The resistivity is a

B.M. Mwashote et al. / Continental Shelf Research 53 (2013) 63–76 67

function of lithology, porosity, and pore water conductivity. Theapparent resistivity of the subsurface is determined by measuringthe potential difference between pairs of electrodes while intro-ducing current into the ground or surface water through anotherpair of electrodes (TIQ, 2006). Streaming and fixed cable marineresistivity methods offer potential as a reconnaissance surveyingmethod for detecting subsurface zones of freshwater (e.g.Swarzenski et al., 2007a, 2007b), because freshwater has a muchhigher resistivity than seawater. Thus zones of concentratedfreshwater discharging into the seafloor may be expected to havecorrespondingly higher terrain resistivities.

Resistivity data for regional comparisons with radon data werecollected in May 2003 and February 2004 using the AGI Super-Sting of Advanced Geosciences, Inc. The system continuallyrecords and stores data using a multichannel resistivity receiveras well as collection of position coordinates from a GPS receiver.The 100 m streaming resistivity cables used contain a currentelectrode pair and nine potential electrodes set up to be used in acustom AGI 100 m dipole array with a 10 m spacing (Greenwoodet al., 2006). The streamers were towed across the water’s surfaceat a speed of �3 to 5 knots. Data were inverted using theEarthImager software from Advanced Geosciences, Inc.

The formation factor, or ratio between terrain resistivity andpore water resistivity, was determined at three sites on Sarasota

Fig. 3. Scatter plots for 222Rn (CRM) survey transects conducted within the Sarasota Ba

different periods (A) 27–28 May 2003 and (B) 18–19 August 2004. In both periods, the p

levels in the South Region relative to the other regions.

Bay by sampling pore waters from depths resolved in coincidentresistivity surveys (Harrison, 2006).

2.6. Nutrient measurements

Nutrient samples of bay water and groundwater were filteredthrough glass fiber filters (0.70 mm) using acid (1 M HCl) washedequipment and sample bottles (polycarbonate), rinsed in ultrapurewater (millipore milli-Q), storing them in ice boxes in the field (at�4 1C), before transporting to the laboratory at the Florida Depart-ment of Environmental Protection (FDEP) for analysis within theshortest possible time. For storage that required waiting periodsbeyond two days, they were stored in a deep freezer (attemperaturesr�10 1C). In the laboratory, samples were analyzedfor dissolved inorganic nutrients (nitrateþnitrite, phosphate, andammonium) within a period of less than two weeks. Sodiumphenolate was added as a preservative to ammonium samplesbefore refrigeration. Whenever storage was necessary, the sampleswere stored in upright positions and thawed in the same mannerbefore analysis. Thawing was mainly done at room temperaturewithin a few hours with regular shaking of samples to ensurecomplete mixing before analysis. Analytical error assessment oneach individual sampling station was on the basis of standarddeviations on triplicate samples, which remained withinr7% for all

y system showing the general salinity versus 222Rn variations from N to S for two

lots clearly depict lowest salinities, coinciding with the highest 222Rn concentration

Table 2Average seawater 222Rn and CH4 concentrations in the Sarasota Bay system during

the period July 2002–July 2004 for bottle samples; 18–19 August 2003 for CRM

survey.

Region withinSB System

Average CH4 (nM)n¼19

Average 222Rn concentration(dpm/L) n¼214

Bottle Survey

North 56.9 15.7 20.2

(41.5) (14.1) (2.1)

Middle 34.6 12.4 24.7

B.M. Mwashote et al. / Continental Shelf Research 53 (2013) 63–7668

the nutrient samples. Analyses were conducted using a Latchat autoanalyzer according to manufacturer’s guidelines and standardmethods described in Parsons et al. (1984) and Grasshoff et al.(1999). Measurements of DOC were made using a Shimadzu TOC Vseries total carbon analyzer according to the method of Benner andStrom (1993).

While we directly measured all the water column nutrientconcentration data within the SB system, groundwater nutrientdata was obtained from the FDEP database. All nutrient measure-ments were conducted using the described standard (qualitycontrolled) nutrient analytical methods.

(6.3) (11.3) (2.5)

South 50.6 25.6 42.3

(12.7) (16.0) (4.2)

Figures shown in parentheses indicate standard deviations (1s).

2.7. SB system flushing (residence) time estimations

The approximate flushing (residence) times of the differentregions in the SB water system were estimated by using a modifiedsimple tidal prism model (Dyer, 1973; Dyer and Taylor, 1973). Inthe model, the residence time, t, was estimated by taking intoconsideration the flooding and ebbing cycles during both the neapand spring tides in the SB region. The model represents the bayregion as a box with low tide (or flood tide) volume V and intertidal(or average) volume P. The empirical equation for calculatingresidence time, t, measured in days, is

t¼ P= 9P�V9=T� �

ð2:8Þ

where T is tidal cycle period in days. The simple tidal prismmodel assumes that the bay water is well mixed. Estimates weremade for both semi-diurnal and diurnal tidal range scenarios, asthe SB system experiences both. Residence times estimated in thismanner are the minimum estimates possible.

3. Results

3.1. Radon determinations

3.1.1. Grab samples

During every sampling session within the SB system (Fig. 1),grab samples were collected in as many regions as possible in anorth to south direction. The radon measurements were all madeduring the interval July 2002 to July 2004. The distributions of the222Rn concentrations within the three regions of the SB systemthrough this period are shown in Fig. 3. These measurementsreveal that the 222Rn levels relatively were very high for surfacewaters (4 20 dpm/L) and were generally highest in the southregion. There was no significant difference between concentrationlevels that were observed in the north the middle areas (t test:t¼�0.15; p¼0.88; n¼145).

3.1.2. Continuous 222Rn mode (CRM) surveys

The two CRM surveys that were conducted on 27–28 May 2003and 18–19 August 2004 revealed a trend consistent with the grabsamples in the distribution of 222Rn within the SB system. Althoughthese CRM surveys were conducted at different times, their trendremained markedly consistent along the north–south direction withinthe SB system, as revealed in the scatter plots (Fig. 3). The two 2 daysurveys each confirmed the average variation trend that wasobserved throughout the nearly two year grab sampling period(Table 2). There was however, more scatter for the 222Rn concentra-tions that were observed during May 2003 compared to the results inAugust 2004. It is also to be noted that the former measurementswere conducted during a period of relatively less rainfall than thelatter.

3.1.3. Continuous 222Rn mode (CRM) fixed station estimates

The time series continuous radon measurements were conductedat two fixed stations within the SB system: (1) New College, NC(within the North Bay) and (2) Roberts Bay, RB (within the MiddleBay). These measurements were conducted during the same periodof time (Fig. 4). The variations at NC and RB showed similar trendsthroughout the measurement period with high concentrations in thesame range as the southern region of the bay shown earlier (Fig. 3).The internal consistency of these results is somewhat remarkablesince these two sites were separated by approximately 14 km. Therelative mean of 222Rn concentration at RB (39.477.3 dpm/L) wasessentially the same as that at NC (38.977.2 dpm/L). The close trendsimilarities between these two regional sites may suggest a common222Rn source for the two regions.

3.1.4. 222Rn end member estimates and diffusive fluxes

In an attempt to establish the most reasonable end member forgroundwater 222Rn concentrations, a number of sediment equili-bration experiments were conducted on nearshore sediments thatwere collected from within the SB system. The choice of locationsfor collection of sediment samples were mainly two fold easyaccess and the fact that the areas were within the vicinity of coastalsites that were suspected to have considerable seepage, mainly dueto karstic, highly transmissive carbonate zone within the area(Fretwell and Stewart, 1981; USGS, 2007). In addition to pore water222Rn, estimated diffusive fluxes can be compared with the derivedSGD advective fluxes determined from the 222Rn model andseepage meter measurements. These experiments produced esti-mated pore water values ranging from 170 to 800 dpm/L, with amean value of 3907180 dpm/L (Table 3; n¼27).

In addition to the near surface sediment equilibration experi-ments, regional estimations for groundwater 222Rn end memberconcentrations and diffusive fluxes were also estimated via porewater sampling. These samples were collected with a piezometerand the results displayed as 222Rn concentration versus depthprofiles (Fig. 5). These profiles generally show concentrations nearthe surface close to those estimated from the sediment equilibra-tion experiments (mean�3907180 dpm/L).

3.2. Methane (CH4)

The temporal and spatial variations in CH4 concentrationswere observed to show some relationship with that of 222Rn. Anapproximate relationship between CH4 and 222Rn concentrationsin all the regions of the SB regional system was observed for allconcurrent samples assessed within the SB system despite thefact that CH4 is non-conservative gas relative the radioactive gas222Rn.

20

25

30

35

40

45

50

55

222 R

n C

once

ntra

tion

(dpm

/L)

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

Wat

er le

vel (

m)

Rn ConcWater Level

20

25

30

35

40

45

50

55

01/08/2003 12:00:00 01/09/2003 12:00:00 01/10/2003 12:00:00 01/11/2003 12:00:00 01/12/2003 12:00:00Time

222 R

n C

once

ntra

tion

(dpm

/L)

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

Wat

er le

vel (

m)

Fig. 4. Variations over time of seawater 222Rn concentrations (dpm/L) and water level at two fixed stations: (A) Roberts Bay, RB – Middle Bay (Mean

concentration¼39.477.3 dpm/L) and (B) at the New College, NC – North Bay (Mean concentration¼38.977.2 dpm/L), within the Sarasota Bay system during a time

series monitoring, 8–12 January 2003.

Table 3Results of sediment equilibration experiments from the Sarasora Bay system, May 2003–March 2004.

Latitude(1N)

Longitude(1W)

Site name Wet sediment 222Rnconcn. (C0), dpm/L

Pore water 222RnConcn. (Ceq), dpm/L

Estimated diffusive 222Rnflux (¼Fdiff), dpm/m2/d

Diffusive 222Rn Flux (SGDequivalent, cm/d)

Regionwithin SBsystem

27.409 82.575 Bowlees Creek

(Whtfld Est)

72 193 168 0.043

27.386 82.567 New College 224 419 269 0.07 North27.384 82.585 Mid Sar Bay 67 197 179 0.046

27.383 82.565 New College 154 184 42 0.011

27.358 82.557 Whitaker

Bayou (Ind Bch)

230 643 571 0.148

27.357 82.605 Longboat Key 52 183 180 0.047

27.355 82.547 Whit Bayou 185 330 199 0.052

27.353 82.553 Whit Mouth 141 475 460 0.119 Middle27.329 82.542 Anchorage 184 269 118 0.03

27.325 82.531 Hudson Bayou 275 635 498 0.129

27.311 82.546 Siesta Key

Brdge (Bascule)

175 465 400 0.103

27.3 82.548 Roberts Bay 132 169 52 0.013

27.293 82.547 Bascule Bridge

(south)

165 379 295 0.076

27.289 82.556 Siesta Key

Canal

98 251 210 0.054

27.285 82.545 Roberts Bay 156 384 315 0.081

27.277 82.55 Philippi Creek

(across)

129 248 164 0.042

27.276 82.529 PC small bridge 242 290 66 0.017

27.276 82.525 Phil Cr 285 803 715 0.185

27.263 82.542 Stickney Bridge

(north)

168 252 116 0.03 South

27.253 82.532 Stickney Bridge 230 685 627 0.162

27.249 82.518 Canal 156 430 377 0.097

27.239 82.518 Marina 285 762 659 0.17

27.239 82.51 Hidd Harb

(Mouth)

191 415 309 0.08

27.236 82.516 Little SB 173 358 255 0.066

27.228 82.516 Siesta Key 219 358 191 0.049

27.228 82.505 Vamo 169 316 203 0.052

27.213 82.505 Bird Keys,

Vamo

110 342 319 0.082

Means 173 386 295 0.076Stdev 63 180 188 0.049

B.M. Mwashote et al. / Continental Shelf Research 53 (2013) 63–76 69

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

0 2000 4000 6000 8000

Dep

th (m

)

12.4±11.3 dpm/L

A 0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

5.0

5.5

6.0

6.5

7.0

0 200 400 600 800 1000 1200

222Rn Concentration (dpm/L)

222Rn Concentration (dpm/L)

Dep

th (m

)

15.7±14.1 dpm/L

Fig. 5. Depth 222Rn concentration profiles (based on piezometer sampling) from

the Sarasota Bay System: (A) North Bay region (NC site) and (B) Mid Bay region

(RB site). Values shown by arrows are mean bottom water 222Rn concentrations.

The shaded band indicate the margin for the equivalent equilibrium concentration

zone (3907180 dpm/L).

B.M. Mwashote et al. / Continental Shelf Research 53 (2013) 63–7670

3.3. Resistivity surveys

The formation factors determined at 1–3 m depth at three sitesin Sarasota Bay ranged from 4.4 to 5.4 (Harrison, 2006). This rangeis limited enough to suggest that resistivity could be a usefulqualitative indicator of pore water conductivity.

The 222Rn concentration observations indicate higher SGD inthe southern portion of the SB system (Fig. 3). However, forresistivity data sets collected during the same day (with similarantecedent rainfall) we do not see consistently higher subseafloorresistivities in the southern portion of the bay. The dominantsignature in the resistivity response appears to be associated withthe conductive clays in the Peace River Formation, which arefound only in the southern portion of the bay (Harrison, 2006).Fig. 6 compares representative same-day resistivity profiles froma northern site and southern site in SB. The northern site shows

slightly higher resistivities, while the southern site shows a morepronounced low-resistivity layer that coincides with the depths ofthe clay-rich layer. Thus on the regional scale across Sarasota Bayresistivity variations associated with lithology appear to outweighthose driven by SGD.

3.4. Seepage meter measurements

Direct SGD measurements obtained through manual seepagemeters are shown together with the corresponding 222Rn SGDadvection determinations (Table 4). Although the absolute SGDvalues between the two approaches did not coincide, they werenot widely different from each other. Of the three sites consid-ered, the highest seepage meter SGD rates were found at Caples(middle region) while the lowest were observed at Island Park,which is also found within the middle region. The north region(NC) showed medium SGD rates. Since seepage meter determina-tions are directly dependent on the local seepages at the site,reliable results can only be obtained through several repeatmeasurements of an area.

3.5. Nutrient concentrations

Nutrient measurements of bay waters were conducted inJanuary and March 2004, in order to get a general sense ofconcentration levels within the SB system. The results are shownin Table 5.

4. Discussion

4.1. SGD, water volumes and residence times

The magnitude of SGD in the SB system was evident fromthe independent measurements that were carried out (Tables 4and 7). The average regional SGD estimates were obtained byaveraging the individual estimated regional SGD rates (in m/day,cm/day¼10�2 m/day) derived from the two 222Rn modelapproaches (bottle and CRM). The residence times of the watersof the SB system, estimated via a modified tidal wedge approach(Dyer, 1973) ranged from 3 to 11 days. As shown in Table 1, thenorth and middle regions of the SB system had similar residencetimes which were slightly higher than for the south region of thebay. Extended residence times may result in enhanced primaryproductivity of the system if elevated nutrient levels develop. Thismight have been the case in areas within the south and middleregions of the SB system, partly due to the existence of numerousseptic tank systems in the surrounding area. Indeed previousstudies within the SB bay system revealed considerable transportof contaminated waters into the bay with effluent from shallowseptic systems (Lipp and Griffin, 2004).

The north region showed lower nutrient concentrations per-haps because of a relatively larger seawater volume compared tothe other regions. In relation to the other regions of the SB system(Table 6), the north region accounts for about 80% of the totalvolume of seawater present, while the middle and south regionsonly account for about 12% and 8% respectively.

4.2. SGD estimates

The bulk of SGD estimations in the SB system was carried outusing the ‘‘grab sampling’’ (bottle) method. The measurementscovered included various periods between July 2002 and August2004. The overall estimated groundwater advection (SGD) in thethree main regions within the SB system, during the study periodranged from 0.7 to 24 cm/day. In the north region of the SB

Fig. 6. Representative samples from resistivity profiles collected on the same day.

Top: Profile in northern section of the SB system near Bowlees Creek. Line is centered at 82.584019 W, 27.407342 N. Here Holocene deposits overlie the Arcadia Limestone.

The top of limestone lies 1–5 m below seafloor (Locker et al., 2001a). Black line indicates seafloor. The low resistivity zone at 800–900 m corresponds to a thickened zone of

Holocene deposits.

Bottom: Profile in southern section of the SB system in Little Sarasota Bay. Line is centered at 82.524692 W, 27.247786 N. Here �2 to 3 m of Holocene deposits overlie

5–8 m of the clay-rich Peace River Formation, which in turn overlies the Arcadia Limestone (Locker et al., 2001b). Overall resistivities in the southern profile are slightly

lower than in the northern profile, note difference in scale between top and bottom figures. The Peace River Formation correlates with a distinct zone of lower resistivities.

Table 4Quantitative estimations of SGD and nutrient fluxes within the different regions of the Sarasota Bay system.

Region in theSB System

Total SurfaceArea (�106 m2)

Estimated TotalVolume (�106 m3)

Estimated SGD rates(cm/day� ��10�2 m/day)

Combined averageSGD (�10�2 m/day)

SGD nutrient fluxes in the SB system(mmol/m2 day)

Bottle Survey Seepmeters NO2þNO3 PO4 NH4 N/P(222Rn) (222Rn) (Manual)n¼214 n¼214 n¼18

North Bay 75.1 150.2 5.8 5.6 16.7 5.7 7.9 0.4 0.4 21

(0.8) (0.7) (8.5) (0.8)

Middle Bay 11.1 22.2 4.5 7.8 3.3 6.2 5.4 2.5 2.3 3

(0.6) (1.0) (2.3) (0.8)

South Bay 10.5 15.8 6.5 10.8 – 8.7 0.1 0.6 2.0 4

(0.9) (1.4) (1.2)

Figures shown in parentheses indicate standard deviations (1s) and n is the number of representative SGD rate measurements in each region used in the estimations.

B.M. Mwashote et al. / Continental Shelf Research 53 (2013) 63–76 71

system the range was from 0.7 to 5.9 cm/day, while in themiddle and south portions of the bay the range was from 5.9 to24 cm/day.

On average, SGD estimates in the SB system that were made bythe 222Rn bottle technique were relatively lower compared tothose made using seepage meters and the continuous mode 222Rntechniques (Table 6). This was not unexpected however becausein the former method (based on grab sampling), the radon mixinglosses in the estimations are neglected since these are instanta-neous samples, while this aspect is accounted for in the case ofCRM estimates made by a non steady state mass balanceapproach. The average salinity within the SB system during theinvestigation period was 26.074.2 ppt (the variation indicatedrepresent the standard deviation and not actual error in indivi-dual measurements). Since the scope of the study did not allowprecise detailed calculations of expected freshwater inputs withregard to the salinity changes observed, salinity variations were

only explained in terms of the observed general SGD inputswithin the different SB regions.

The relatively unusually high 222Rn concentration levels(4 20 dpm/L) measured through the entire SB system couldimply one of the three possibilities, either; the SB waters havehigh SGD prevalence, or the presence of minerals associated with222Rn (i.e. 226Ra) in the underlying rocks, or the SGD into the baycontain very high concentrations of 222Rn per volume discharged.However, looking at other independent evidence such as the highCH4 concentrations whose variation trend generally follows thatof 222Rn (Fig. 3), and the generally low salinities within the SBsystem (Fig. 3), it is more probable that the high 222Rn areassociated with the SGD prevalence rather than the other twopossible factors. This is further augmented by the manual seepagemeter SGD values which averaged about 1075.4 cm/day(Table 4) for NR and MR combined, where the seepage meterswere deployed. The relative agreement of the observed SGD

Table 5Seawater nutrient concentration levels in the Sarasota Bay system. Sampling

conducted on 04 January and 04 March 2004 for all the SB system regions (North,

Middle and South).

Region DOC (lM) NO2þNO3 (lM) PO4 (lM) NH4 (lM) N/P

North Bay (n¼4) 181 1.46 0.23 0.56 9

830 11.2 0.72 0.10 16

400 4.06 0.44 6.11 23

369 0.35 0.18 0.29 4

Mean 445 4.26 0.39 1.77 15(Stdev) 275 4.86 0.25 2.91

Middle Bay (n¼4) 1032 0.75 0.90 1.59 3

480 0.17 0.29 0.95 4

484 0.33 0.81 9.14 12

380 1.36 1.08 7.99 9

Mean 594 0.65 0.77 4.92 7(Stdev) 295 0.53 0.34 4.25

South (n¼10) 535 0.13 0.27 0.67 3

567 0.19 0.37 0.94 3

565 0.21 0.34 0.94 4

244 0.24 0.39 1.06 2

243 0.27 0.37 3.87 11

186 0.34 0.41 1.63 5

1082 0.71 1.22 0.00 0

724 2.01 1.05 5.63 7

635 1.96 1.15 9.06 10

1041 1.25 1.35 0.00 0

Mean 582 0.73 0.69 2.34 5(Stdev) 311 0.74 0.44 2.97

Table 6Average groundwater nutrient concentrations in wells found within the vicinity

of the SB system.

Region NO2þNO3 (lM) Total dissolved P (lM) NH4 (lM) N/P

North 1387215 6.979.1 7.876.2 21

(n¼3) (n¼9) (n¼9)

Middle 44.2785 28.3741 28.4727.1 3

(n¼4) (n¼5) (n¼7)

South 1.270.7 7.178.5 23.4712.1 4

(n¼6) (n¼17) (n¼30)

Groundwater raw nutrient data source: Watershed Monitoring Section of the

Florida Department of Environmental Protection, FDEP. (Standard deviations are

indicative of measurement variations at a given site taken at different seasons.

However, median measurements were used for flux estimation calculations.)

B.M. Mwashote et al. / Continental Shelf Research 53 (2013) 63–7672

trends using both seepage meters and 222Rn has been reported inearlier studies. Burnett et al. (2008), for example, found a similarSGD pattern with seepage meters as well as 222Rn concentrationsin Flamengo Bay, Ubatuba, Brazil. Some other studies in variousnearshore environments have also found similar observations (i.e.Sholkovitz et al., 2003; Burnett et al., 2006). It is thus suggestedthat these independent SGD estimation techniques complementrather than substitute for each other. Therefore a better under-standing of SGD in an area is more probable when more than oneof these approaches are applied in a complementary manner.

The two CRM surveys that were conducted in May 2003 andAugust 2004 revealed a relatively consistent trend in the dis-tribution of the radon concentration estimates, within the entireSB system (Fig. 3). It was evident from the observed trends thatrelatively high SGD rates were likely present in the south regionand the lowest levels in the middle region of the bay. While theobserved trend of SGD estimates is likely attributable to the localhydraulic gradients, and to a great extent on the surroundingregional catchment areas, it is also important to consider theprevailing sediment properties and structure within the differentregions. Hydrological conductivity of sediments and the topogra-phy of an area are integral factors that could directly determinethe net SGD rates (Hornberger et al., 1998).

The trends in groundwater advection estimates performedusing the CRM survey and those that were done by the bottlemethod at the different sampled sites within the SB system werelargely in agreement in magnitude.

The continuous SGD measurements at two fixed stationswithin the SB system, at NC and RB sites were synchronizedand conducted within the same period of time.

These two time series sites were ‘‘hot spots’’ identified in thesurvey, so their SGD estimates were relatively high as expected. Inspite of the fact that these two sites were about 14 km apart theirradon concentrations and SGD estimates were very similar(Table 7). A statistical analysis revealed no significance differencebetween the measurements (p¼0.62; a¼0.05; n¼78), and therelative estimated SGD mean at RB (46721 cm/day) was essen-tially the same as at NC (43720 cm/day). The representative porewater end member radon concentration used in the CRM advec-tion model estimations was 3907180 dpm/L. This was theaverage value derived from several sediment equilibration experi-ments that were conducted on nearshore sediment cores col-lected throughout the SB system (Table 3). It should be noted thatthe ‘‘7 ’’ associated with these estimated fluxes refer to realstandard deviations (1s) and are not uncertainty values.

The similarities between these two fixed CRM regional sitesmay indicate a common SGD supply source for the two regions,perhaps a regional aquifer that discharges in both regions. In bothplots, the general sinusoidal SGD variation pattern at the two sitesclosely related to the way the tidal wave varied. In each case, thehighest SGD peak occurred a few hours after the lowest tide waterlevel was reached. A similar phase difference has also beenobserved elsewhere. For instance, in their correlation analysesbetween SGD and sea level in Osaka Bay, Japan, Taniguchi andIwakawa (2004) found that SGD changes were delayed by 4 hafter sea level changes.

There were differences in SGD estimates via CRM and seepagemeters within the same bay regions (average difference of�33%).It should be noted that the SGD measurements at NC and RB siteswere made at distances close to the shoreline within areas that weregenerally known to have substantial submarine seepage (thesesubstantial diffuse SGD were evident through measurements takenusing manual seepage meters within the area). It is therefore likelythat the relatively higher overall CRM SGD estimations in the twotime series sites compared to the observed seepage meter valueswere probably due to the karstic, high transmissive nature of the

carbonate zone predominant in areas around where NC and RBsampling sites were located (Fretwell and Stewart, 1981; USGS, 2007).

The SGD values derived from estimated diffusive fluxesobtained from equilibration experiments on sediment cores ofthe SB system were negligible compared to SGD advectionestimations (Tables 3 and 7). The estimated 222Rn diffusive fluxeswere at least two orders of magnitude lower compared tocalculated fluxes estimates derived from the 222Rn model withinthe same sites (Table 7). It is interesting to observe a markeddifference in 222Rn concentrations in piezometer samples from NCand RB sites (Fig. 5). While the surface 222Rn concentrationsfrom both areas were similar, there was a sharp differenceobserved in terms of their depth concentration profiles. The NCsediment 222Rn concentrations profile increased gradually andremained fairly constant beyond the 2 m depth level at a value of�390 dpm/L, which is essentially the same as the pore water endmember based on the sediment equilibration experiments. Unlikethe NC profile however, the RB site 222Rn pore water concentra-tion profile revealed an irregular variation with depth (Fig. 5).While the average 222Rn concentrations above 2.5 m depth level

Table 7SGD – advection and diffusive flux estimations using different approximation approaches within the Sarasota Bay system.

SB SystemRegion

Temperature

(1C)

Porosity Equilibration

sediment222Rn concn.

(�102 dpm/L)

Depth

(m)

222Rn depth profile

(�102 dpm/L)

D0

(m2/day)

Ds

(m2/day)

222Rn flux (¼J)

Diffusion

(dpm/m2/day)

Bay Area

(�104 m2)

SGD estimates

(a,b,c¼Flux/ex

222Rnpw d¼manual

seepmeters) (cm/day)

North 31.2 0.684 3.86 0 1.89 1.54E�05 1.06E�05 273 75.1 0.071a

(NC site) 0.2 6.03 15 0.004b

16.7d

6.8c

Middle 19.9 0 1.25 1.16E-05 7.93E-06 314 5.5 0.081a

(RB site) 3 0.001b

a J¼Dsnl1/2(Ceq�Co), diffusive flux.

b J¼�~nDsndC/dZ, diffusive flux.

c Radon model advection (SGD) estimates, overall average for SB system (� 2 to 3 orders of magnitude higher than diffusive SGD flux).d Manual seepmeter measurements, average for the NC site (� 2 to 3 orders of magnitude higher than diffusive SGD flux).

B.M. Mwashote et al. / Continental Shelf Research 53 (2013) 63–76 73

wereo250 dpm/L, a prominent peak was found at around 3 m ofabout 7000 dpm/L. This peak is likely indicative of the presence ofa uranium enriched phosphatic sediment or freshwater lens atthis depth since the 222Rn concentration levels tapered off tolower concentrations at deeper levels, showing that the elevatedlevels were mainly localized at the 2.5–3.5 m depth range. Thelow salinity range (1.7–4.8 ppt) observed within this depth andthe higher values at shallower sediment depths (11.7–23.9 ppt)confirm the presence of a freshwater lens.

In contrast to 222Rn, CH4 is rarely used as a quantitative SGDtracer. A correlation analysis of the CH4 and 222Rn data revealed afairly strong relationship (r2

¼0.31; a¼0.05; n¼54) between thetwo data sets. In spite of CH4 not being a conservative SGD tracer,its marked qualitative potential in SGD estimations is owed to thefact that the relative concentrations of CH4 associated withadvecting groundwater compared to those in ambient seawater(CH4gw/CH4sw) is typically higher by some orders of magnitude. Inthe present study, this ratio was �16 (i.e. one order of magnitudehigher). In a previous study, Bugna et al. (1996) measured bothCH4 and 222Rn concentrations of up to three orders of magnitude(concentrations of up to about 3300 and 2100 times higherrespectively) in groundwater from an offshore spring comparedto the respective ambient seawater concentrations. While CH4

may be a good SGD indicator, its non-conservative nature pre-cludes it from being used as a quantitative assessment tool forSGD. In this respect, 222Rn is better suited for such use since it isboth an inert gas and like CH4 also available at relatively highconcentrations in groundwater environments compared to sur-face water. Nevertheless, CH4 is an important qualitative tool forSGD assessments (Bugna et al., 1996).

Seepage meters on the other hand are site specific and depen-dent on the specific local sediment environment where the benthicchamber is deployed. Reliability of the seepage meter SGD estima-tions is normally based upon a representative number of deploy-ments made within a given location. Although some individual SGDestimations obtained by direct manual seepage meter measure-ments at some sites within the SB system appeared to differ fromthose derived from the 222Rn approach (Fig. 1), when pooled, theoverall data agreed more closely and no statistical difference wasfound among them (t test: p¼0.12; a¼0.05; n¼18). In their review,Burnett et al. (2006) found good agreement in patterns and over-lapping calculated advection rates on independent estimations byseepage meters and the radon model, during an intercomparisonSGD study which was conducted at the same location (West NeckBay, Shelter Island, New York).

The streaming resistivity surveys offered large scale usefulreconnaissance method for detecting zones of fresher groundwater(Fig. 6). However, on a regional (kilometers to tens of kilometers)

scale the relationship between marine resistivity and tracer basedSGD estimates did not generally follow the expected pattern ofhigher resistivities associated with higher SGD flux (Fig. 6). Thereappeared to be only subtle differences between resistivity structurein the northern and southern regions of the bay. These smalldifferences show an inverse relationship regionally between advec-tion rates and resistivity values in the north and south portions ofthe bay. The north region of the SB system was dominated by lowerflow rates ranging between 0.71 and 5.9 cm/day and higherresistivity values between 3.1 and 30.0 O m. The south regiondisplays generally higher flow rates ranging from 5.9 to 24.0 cm/day with lower resistivity values between 0.31 and 3.1 O m. Thisinverse relationship is the opposite of what would normally beexpected if fresh SGD were the dominant cause of resistivityvariability throughout the area. Seafloor resistivities instead maybe influenced by stratigraphy, particularly the presence of a claylayer at �10 to 15 m depth in the south region. In the south region,the general trend from the seafloor downward is of decreasingresistivity at the depths associated with the clay layer, andincreasing resistivity below clay depths. In the north region, wherelimestone is close to the bay floor, resistivity values are slightlyhigher, and the decrease in resistivity around ten meters depth isless pronounced.

4.3. Nutrient fluxes in the SB system

There were no trends in the variation of seawater nutrientsthat were measured in January and March 2004 within thedifferent regions of the SB system (Table 5), partially due tolimited water column nutrient data that was available. However,except for NO2þNO3, there were generally somewhat highernutrient levels observed within the middle and south regions(albeit not being statistically different), as compared to the northregion. Since the nutrient data were only from occasional grabsamples, it is difficult to expect these data to reveal a representa-tive nutrient distribution trend for the entire SB system. It ispossible that the apparent higher nutrient levels observed withinthe middle and south regions is due to factors related to thegeneral ocean water circulation, rather than to their actual source.Factors such as residence time, mean depth, number of passes andsediment characteristics could all be contributing to the regionalnutrient distribution. It is also expected that groundwater see-page into the SB system influences the nutrient concentrationssince the groundwater nutrient concentrations tend to be high(Table 6). Such an effect might be especially important in areasthat have longer residence times where the expected occurrenceof rapid tidal dilution effect to the open Gulf of Mexico (GOM) isimpeded. This is more likely to happen within the middle and

B.M. Mwashote et al. / Continental Shelf Research 53 (2013) 63–7674

south regions rather than in the north as there is a much largervolume of water involved (�80% of SB system water is foundwithin the north region alone). Because of the apparent complexinteractions of these factors, non-linear relationships are likely toresult between SGD nutrient supplies and the subsequent con-centrations. Our observations are consistent with an earlier workwithin the SB system by Tomasko et al. (1996), who noted thatthe water quality parameters did not clearly reflect differences inwatershed nutrient inputs. The relative elevation of nutrientlevels within the SB regions where relatively substantial SGDwas observed (such as in the south region) is in agreement withearlier studies that have associated SGD with dissolved nutrientsupply within coastal environments (USGS, 2007; Valiela et al.,1990; Capone and Slater, 1990).

For purposes of estimating nutrient fluxes of groundwaternutrient concentrations for each of the three regions (Table 6)were assumed to approximate the SGD or pore water concentra-tion levels in each region (Table 6). Groundwater nutrient con-centrations in wells for areas surrounding SB system wereobtained from the Florida Department of Environmental Protec-tion (FDEP) database. Nutrient fluxes for each region wereestimated by multiplying the regional estimated SGD rates withthe respective average groundwater nutrient concentrations inthat region (i.e., Flux¼SGD rate � nutrient concentration�m/day � mmol/m3

¼mmol/m2 day).From these estimates it seems clear that the earlier model

(WASP4) generated estimate of �10% for nitrogenous nutrientsbeing attributed to groundwater may be an underestimate (USGS,2007). As revealed in the present study, SGD is a significant sourceof nutrients in SB system, and assuming that the SGD seepageregime covers the 200 m coastal zone from the shoreline seaward(Burnett et al., 2006), then about 27% of total N is associated withSGD in the entire SB system (with base flow included as part ofSGD). This should however be considered as a crude estimategiven the large seasonal variability of the relatively limitedgroundwater nutrient data that was used in the study. A futurefurther detailed groundwater nutrient assessment is recom-mended for the SB system. The estimate is based on the medianend member groundwater (N) concentration value within theregion.

The estimation of % N due to SGD was arrived at consideringthe assumption that the SGD regime extends approximately200 m from the average shoreline. On this assumption andconsidering the shoreline of the SB system, it was estimated thatthe total SGD regime was about 8% of the total area of the SBsystem. Median nutrient estimations showed that N due to SGDwas in the order 81,373 kg/yr of the estimated 481,233 kg N totalinput load in the SB system in 2004 (USGS, 2007). This works outto approximately 17% of total N due to SGD. However, since thebaseflow which is approximated at 10% of the total N input isconsidered in this study as part of the N input due to SGD, thusthe total N due to SGD estimates to 27% (i.e. 17%þ10%¼27%) asreported in our study.

This value is comparable to atmospheric and rainfall inputswhich were also estimated at about 27% of total N in the region.Forty-six percent of the total N was attributed to surface runoff.Using the map scale provided for the SB system, the overall areaattributed to SGD worked out to approximately 8% of the totalarea of the SB system (Fig. 1; USGS, 2007).

The regional SGD (groundwater flux) N/P ratio was 21 in thenorth, three in the middle and four in the south regions,respectively (Tables 4 and 6). Except for the north region, it wasevident that all the others had N/P ratios that were less than thetheoretical Redfield ratio of 16 (Redfield et al., 1963). Therelatively elevated levels of DOC (Table 5) within the middleand south regions are consistent with higher SGD in these areas

since DOC has often been strongly associated with groundwater,and its inherent terrestrial nutrient loads as well as low pH levels(Goldharber et al., 1977; Santos et al., 2008). In general, there areseveral possible explanations for the low N/P ratios observed inboth the seawater and groundwater of the SB system. Among theprobable reasons for the observed low N/P ratio include the factthat, in our estimations we only considered the dissolved inor-ganic nitrogen (DIN) fraction, while assuming that the other labilenitrogen fractions such as the dissolved organic nitrogen (DON)were negligible. Other reasons that could be attributed to thisobservation may include the behavior of PO4 in groundwater. Forinstance, while reactive phosphorus in groundwater is mostlypresent as inorganic dissolved PO4, it is generally rapidly removedthrough sorption to feroxides or coprecipitated with Al and Ca inmineral phases through its flow path (hence raising the N/P ratio),though this removal becomes significantly inefficient in anoxicenvironments (Zanini et al., 1998). A case in point is a study inButtermilk Bay, Massachusetts, where the N/P ratio was observedto rapidly increase from 17 at the outlet of a septic system to 40one-meter downstream (Slomp and Van Cappellen, 2004). Theconverse of this may be explained by taking into considerationthe relative amount of P present or supplied, with respect to thatof N within a region.

A previous study of Sarasota Bay by Dillon and Chanton (2005,2008) had shown that storm water PO4 can be a significant sourceto the underlying groundwater aquifers. They showed that PO4

concentrations which ranged from 3.5 to 13.8 mmol/L were signifi-cantly higher than concentrations in rain water. While low N/Pratios are rather unusual for oxic groundwaters where dissolved PO4

is normally expected to be negligible and the coastal groundwaterN/P ratios are typically higher than 16, this is not totally surprisingespecially if the sorption capacity of an aquifer is overwhelmed dueto excessive terrestrial P inputs (Slomp and Van Cappellen, 2004).Indeed, values as low as three have also been reported in the NorthInlet, South Carolina, where P fluxes were found to average on thehigher level, �900 mmol/m2 day (Krest et al., 2000). In a similarstudy, Suzumura et al. (2000) reported high levels of dissolved PO4

in groundwater in Tokyo Bay, Japan, where values in excess of101 mM were measured.

The average nutrient fluxes obtained in this study ranged from2.1 to 8.3 mmol/m2 day for DIN (combined NH4 and NO2þNO3), andfrom 0.4 to 2.5 mmol/m2 day for total dissolved P (Table 6). Thesevalues were on average higher than those reported recently in a morepristine site in the northeastern Gulf of Mexico (Santos et al., 2008).The generally high nutrient fluxes observed are partially to beattributed to the reported high density of septic tank systemscommonly used in the increasingly populated coastal settlementsfound in the surrounding area of the SB system (SBEP, 2006; USGS,2007). Overall however, our SGD and nutrient flux values(Table 8(a) and (b)) were comparable to other studies done indifferent coastal environments.

5. Conclusions

In our assessments, 222Rn was shown to be an effective tracer forsubmarine groundwater discharge. SGD flow rates calculated fromthe radon box model are consistent in magnitude with thoseobtained using manual seepage meters. There is some regionalvariability in SGD rates within the different regions of the SarasotaBay system. SGD rates were shown to be relatively higher in themiddle and south regions (5.9–24.0 cm/day) compared to the northregion of the system (0.7–5.9 cm/day). The estimated advectionrates in the Sarasota Bay system were found to range from 0.7 to24.0 cm/day, except for isolated hot spot occurrences where higherrates were observed. Although much of it is likely recirculated

Table 8(a) Comparison of advection (SGD) rates between this study and other studies.

Study site Seepmetera (cm day�1) Manual meter (cm day�1) 222Rn model (cm day�1)

Turkey Point,b FL (FSUML) 13 11.5–18 12.2–18

Banana River Lagoon,c FL – 3.6–6.9 3.5

South Carmel Coast,d Israel 7.7 – –

Town Cove,e Cape Pod, MS – 2.4–7.2 –

Cockburn Sound,f N. Australia 13.7–16.3 – –

Turkey Point,g FL (FSUCML) 5 – –

Lynch Cove,h WA 7.6 – –

Turkey Point,i FL (FSUCML) 3.3–11.3 7–14 7.2–12.4

Present study (SB system) – 3.3–16.7 4.5–10.8

(b) Comparison of nutrient flux rates and N/P ratios between this study and other studies

Total dissolved P(mmol/m2 day)

DIN (¼NH4þNO2þNO3)(mmol/m2 day)

N/P Source

Tampa, Florida 0.1 0.9 7 Swarzenski et al. (2007a, 2007b)

Turkey Point, Florida (FSUCML) 0.470.3 8.271.2 6–813 Santos et al. (2008)

Florida Bay, Florida o0.03 0.4–1.5 – Corbett et al. (1999)

Waquoit Bay, Massachusetts – 0.55 – Charette et al. (2001)

Nauset Marsh Estuary, Massachusetts – 24 - 72 416 Portnoy et al. (1998)

Pettaquamscutt Estuary, Rhode Island 0.03 0.41 14 Kelly and Moron (2002)

Kaloko, Hawaii – 116 – Paytan et al. (2006)

North inlet, South Carolina 0.9 2.4 3 Krest et al. (2000)

Sarasota Bay, Florida (SB system) 0.4–2.5 2.1–8.3 3–21 Present study

a Seepmeter — is an automated version of a seepage meter as described in Mwashote et al. (2010).b Burnett et al. (2002).c Cable et al. (2004).d Weinstein et al. (2007).e Giblin and Gaines (1990).f Taniguchi et al. (2003).g Cable et al. (1997).h Swarzenski et al. (2007a, 2007b).i Mwashote et al. (2010).

B.M. Mwashote et al. / Continental Shelf Research 53 (2013) 63–76 75

seawater, the numerous possibly leaky septic tank systems foundwithin the middle and south relatively highly populated coastalsettlements play an important role in the observed SGD dissolvedinputs to the Sarasota Bay system as revealed through the regionalseawater nutrient concentration levels, nutrient fluxes and N/Pratios. The generally large variations in water column nutrient werelikely attributed to the relatively limited data that was available inthis study. Although nutrient concentrations did not reveal anyobvious trend, the average nutrient flux N/P ratio was higher in thenorth compared to the middle and south regions.

The importance of SGD in the Sarasota Bay system was evident inthat it conservatively contributes about 27% of the total dissolved N isassociated with SGD in the entire SB system. Since this only presenteda preliminary exploratory study, it is suggested that further detailedwork comprising a more diversified team (including hydrologists,hydrogeologists, environmental economists and marine biologists) beconducted in the SB system in order to elucidate in greater detail thenutrient and water circulation dynamics of the system.

Acknowledgments

The authors express special thanks to a number of people withoutwhose help, this project would not have been possible. Kelly Peeler,Christina Stringer, Rick Peterson, Henrieta Dulaiova, Claire LangfordAxel Schmidt, and Jason Greenwood assisted on this project both atthe field and in the laboratory. The watershed monitoring section ofthe Florida Department of Environmental Protection (FDEP) databaseis much appreciated for allowing use of their groundwater nutrientdata. This project was jointly funded through a Florida Sea Grant/EPAGrant and an IFP Ford Foundation PhD Fellowship. This financialsupport is gratefully acknowledged.

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