Saltwater intrusion model pompano fl

Case Study/

Effect of Sea-Level Rise on Salt Water Intrusionnear a Coastal Well Field in Southeastern Floridaby Christian D. Langevin1 and Michael Zygnerski2

AbstractA variable-density groundwater flow and dispersive solute transport model was developed for the shallow

coastal aquifer system near a municipal supply well field in southeastern Florida. The model was calibrated fora 105-year period (1900 to 2005). An analysis with the model suggests that well-field withdrawals were thedominant cause of salt water intrusion near the well field, and that historical sea-level rise, which is similar tolower-bound projections of future sea-level rise, exacerbated the extent of salt water intrusion. Average 2005hydrologic conditions were used for 100-year sensitivity simulations aimed at quantifying the effect of projectedrises in sea level on fresh coastal groundwater resources near the well field. Use of average 2005 hydrologicconditions and a constant sea level result in total dissolved solids (TDS) concentration of the well field exceedingdrinking water standards after 70 years. When sea-level rise is included in the simulations, drinking water standardsare exceeded 10 to 21 years earlier, depending on the specified rate of sea-level rise.

IntroductionThere is little dispute that global mean sea level has

been rising, and there is recent evidence to suggest thatthe rate of rise is accelerating. Recent satellite altimetrydata collected from 1993 to 2003 show an increasedrate of 3.1 ± 0.7 mm/year (Cazenave and Nerem 2004).This rate is almost twice the rate observed during the20th century (1.7 ± 0.5 mm/year; Bates et al. 2008), butowing to the relatively short period of time, it is possiblethat part of the increased rate could be due to naturalvariability. Predictions of future rates of sea-level risecontinue to improve as the science evolves, as new dataare collected, and as associated uncertainties are morefully addressed. In the Third Assessment Report (TAR),

1Corresponding author: U.S. Geological Survey, 411 NationalCenter, Reston, VA 20192; 703-648-4169; fax: 703-648-6693;[email protected]

2Broward County Environmental Protection and GrowthManagement Department, 115 South Andrews Avenue, FortLauderdale, FL 33301.

Received January 2012, accepted September 2012.Published 2012. This article is a U.S. Government work and is

in the public domain in the USA.doi: 10.1111/j.1745-6584.2012.01008.x

the Intergovernmental Panel on Climate Change (IPCC)reported possible increases for the 21st century that rangefrom 0.24 to 0.88 m, with a median value of about 0.48 m(Church et al. 2001). As part of the Fourth AssessmentReport (AR4) by the IPCC, Meehl et al. (2007) providean estimated range of 0.18 to 0.59 m for the expected risein sea level by the end of this century. Bates et al. (2008)provide insight into the apparent differences between the2001 and 2007 studies: “the upper values of the ranges(reported in Meehl et al. (2007)) are not to be consideredupper bounds for sea-level rise.” Meehl et al. (2007) notedthat dynamic ice flow processes are poorly understood.For this reason, they did not include Greenland andAntarctic ice sheet losses in their projections. By includingthe effect of land ice, Pfeffer et al. (2008) suggest thata 2.0 m rise in sea level by the end of the century ispossible if variables are quickly accelerated but that a0.8 m rise is more plausible. Improving these projectionshas been the subject of recent IPCC investigation on icesheet instabilities (IPCC 2010).

Several studies have attempted to quantify and char-acterize, in a generic way, the effect of sea-level riseon salt water intrusion into a coastal aquifer. Using asteady-state analysis with an analytical solution, Werner

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and Simmons (2009) identified the major hydrogeologiccontrols on the impact of sea-level rise on salt water intru-sion in unconfined coastal aquifers. They differentiatedbetween flux-controlled and head-controlled systems andshowed that sea-level rise is more problematic for head-controlled systems because inland water levels do not risewith rising sea level. Chang et al. (2011) also found thatfor flux-controlled confined aquifers, sea-level rise maynot have an impact on fresh water volumes. Werner et al.(2012) extended the analysis of Werner and Simmons(2009) to include unconfined and confined aquifers andproposed quantitative vulnerability indicators that can becalculated based on boundary condition type and hydro-geologic parameter values. Webb and Howard (2010) andWatson et al. (2010) investigated the migration aspect andresponse time of salt water movement. Webb and Howard(2010) focused solely on the head-controlled system asthe consequences are more severe for that case. Theirsimulation results indicated that in certain situations, sev-eral centuries may be required for the salt water interfaceto reach equilibrium with sea-level change. Watson et al.(2010) found markedly different response times dependingon the type of indicator. For example, the representativeresponse time for the vertical center-of-mass was muchshorter than the response time for the toe position, indicat-ing that care should be given to select indicators relevantto the study purpose. These studies generalize the effectof sea-level rise on salt water intrusion for hypotheticaland simplified conditions.

Several efforts have addressed the effect of sea-level rise on a specific coastal setting. Masterson andGarabedian (2007) predicted the response for the LowerCape Cod aquifer system and found that sea-level riseincreased groundwater discharge into streams causinga reduction in the total volume of fresh water. UsingWerner and Simmons (2009) terminology, the LowerCape Cod aquifer would be classified as a head-controlledsystem. In contrast, Rozell and Wong (2010) found thatShelter Island, New York, would act as a flux-controlledsystem and that the effects of sea-level rise on the freshwater volume would be relatively minor. Interestingly,they found that an increase in sea level might actuallyincrease the fresh water lens volume. They attributed thiscounterintuitive response to the presence of a marine claylayer that truncates the base of the fresh water lens; thus,the volume of fresh water in the aquifer is less if themarine clay layer were absent. As the prescribed sea levelrose in the model, there were no overlying head controlsand so fresh water accumulated in the unsaturated zone.Vulnerability of low-lying coastal areas to sea-level risehas been addressed by Lebbe et al. (2008) for the Belgiancoastal plain, by Oude Essink (1999) and van der Meijand Minnema (1999) for the Netherlands, by Feseker(2007) for northwestern Germany, and by Giambastianiet al. (2007) for an unconfined coastal aquifer nearRavenna, Italy. Fujinawa et al. (2009) evaluated theeffect of climate change (including sea-level rise) for theeastern Mediterranean coastal region of Turkey. Loaicigaet al. (2012) concluded for the seaside area sub-basin in

Monterey County, California, that groundwater extractionwould have a larger effect on sea water intrusion thansea-level rise. For northern Miami-Dade and southernBroward Counties, a sensitivity analysis by Guha andPanday (2012) suggests that water levels and chlorideconcentrations could increase by as much as 15 and 640%,respectively, for coastal parts of the Biscayne aquifer. Allof these studies used a mathematical modeling approach topredict the impact of sea-level rise on salt water intrusion.

This paper adds to our understanding of the impactof sea-level rise on salt water intrusion by quantifyinghistorical changes in fresh water resources and quantifyingprocess sensitivity for a low-lying coastal aquifer insoutheastern Florida subjected to municipal groundwaterwithdrawals. The shallow coastal aquifers of southernFlorida, which include the Biscayne aquifer, offer a uniqueopportunity to evaluate the effect of sea-level rise; thelimestone aquifer is highly permeable, and thus, effectson fresh water resources may be seen more quickly thanfor less permeable clastic aquifers. Southeastern Floridaalso generally fits into the head-controlled category ofWerner and Simmons (2009) because of an extensivecanal network that overlies the entire region; these canalshave been shown to be in direct hydraulic connection withthe underlying permeable aquifers and act as a stronghead control. Combined with a thin unsaturated zone,high propensity for damaging floods and high rates ofevapotranspiration, there is little volume available in thethin unsaturated zone for future rises in the water table.Southern Florida is also representative of many coastalareas because of its large population. The combined 2009population of the three counties comprising mainlandsoutheastern Florida (West Palm Beach, Broward, Miami-Dade Counties) is about 5.5 million. Collectively, theseconditions suggest that southeastern Florida may be morehighly susceptible to accelerated salt water intrusioncaused by sea-level rise than other coastal areas.

This investigation uses a numerical groundwater flowand dispersive solute transport model to evaluate therelative importance of sea-level rise compared to theother dominant hydrologic processes for a municipal wellfield in southeastern Florida. The model represents thehydrologic changes that occurred as the area transformedfrom a natural coastal environment into an agriculturalsetting and then into an urban corridor (Renken et al.2005). The model was then used to predict the impactof future rises in sea level on salt water intrusionnear the well field. Bredehoeft (2003) summarizes thegeneral premise that model predictions tend to be moreaccurate when the calibration period contains eventsand conditions, and encompasses time scales that arecomparable to those expected in the future. The modelpresented here was calibrated for a 105-year period usingmeasured heads and salinity concentrations at monitoringwells. During the calibration period a salt water intrusionevent was observed near the well field followed bya subsequent freshening of the aquifer. Also duringthis period, sea level rose by about 25 cm, which issimilar to the lower-bound estimate of the IPCC (Church

2 C. Langevin and M. Zygnerski GROUND WATER NGWA.org

Figure 1. Map of study area showing physiographic features, surface water control structures, municipal groundwater wells,and monitoring wells. Lines in Florida map delineate county areas.

et al. 2001). The model was calibrated using highlyparameterized inversion techniques to help ensure thatthe model was a reasonable representation of the physicalsystem. Challenges encountered with the calibration effortare described here for others working on sea-level risegroundwater simulations.

Description of Study AreaThis study focuses on the Pompano Beach well

field in northeastern Broward County, Florida (Figure 1).The study area is defined as the active model domainboundary shown in Figure 1. The climate of the areaand southeastern Florida in general is characterized bydistinct wet (May through October) and dry seasons. Theextreme seasonal rainfall variability combined with thedesire to reclaim large parts of the former Everglades forurban and agricultural uses necessitated the constructionof an extensive water management system throughoutmost of southeastern Florida. This water managementsystem consists of a series of levees, canals, pumps, andgates, which are used to control the elevation of the watertable. A structure is a spillway, culvert, or weir locatedwithin a canal that can be used to control the water surfaceelevation. Primary structures are controlled and operated

by the South Florida Water Management District and bythe U.S. Army Corps of Engineers. Secondary and smallerdrainage features are operated by the county and localdrainage districts. During the wet season and hurricaneevents, excess water is released in to the Atlantic Oceanas a mechanism for providing flood protection. During thedry season, the canal system is used to provide aquiferrecharge in coastal areas to prevent salt water intrusioninto municipal well fields. The water management systemis also used by the agricultural community during dryperiods as a source of irrigation water. East of theeasternmost control structure, canals are tidally influencedand can have salinities close to that of sea water. Tidal“finger” canals, which were dredged to provide waterfrontproperty with ocean access, can be seen in Figure 2 in thearea east of the Pompano Beach well field.

Prior to the extensive development that occurredduring the 20th century, northern Broward County wascharacterized by Everglades fresh water wetlands thatextended from inland areas to the western side of theAtlantic Coastal Ridge (Parker et al. 1955). The HillsboroRiver and Cypress Creek (presently the Hillsboro Canaland the Cypress Creek Canal) flowed eastward throughlow areas in the Atlantic Coastal Ridge called thePeat Transverse Glades (Parker et al. 1955). With land

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Figure 2. Map of the area of interest showing the salt waterintrusion lines mapped by Dunn (2001) for the top of theproduction zone. The lines are contours of the 250 mg/Lchloride concentration for different years.

elevations exceeding 7 m, it is unlikely that the AtlanticCoastal Ridge in this area would ever have been inundatedby the fresh water wetlands to the west. During the20th century, the landscape of northern Broward Countychanged considerably. What were once the fresh waterwetlands of the Everglades were transformed first intoagricultural areas and then into the expansive urbancorridor of today (Renken et al. 2005).

Hydrostratigraphy and Aquifer PropertiesThis study focuses on the highly permeable, shallow

surficial aquifer system, which is the primary source ofpotable water in Broward County (Klein and Hull 1978;Causaras 1985). The underlying Floridan aquifer system,which is hydraulically separated from the surficial aquifersystem by an extensive confining unit, is not discussedin this paper or represented in the model. A study on theeffect of long-term (100,000 year) sea-level changes onthe Floridan aquifer system is reported by Hughes et al.(2009). The surficial aquifer system, which increases inthickness from west to east, is defined on the top by thewater table and at the bottom by the top of the Hawthornconfining unit (Fish 1988). The base of the surficialaquifer system slopes downward from an elevation ofabout −40 to −55 m in the western part of the study areato more than −110 m in the eastern part. In the PompanoBeach well field, Fish (1988) defined the base of thesurficial aquifer system at an elevation of about −114 m.In this paper, all elevations, including those referring to

sea level, are referenced to the National Geodetic VerticalDatum (NGVD) of 1929.

The surficial aquifer system in southern Floridacontains the highly transmissive Biscayne aquifer andthe gray limestone aquifer. According to Fish (1988)and Reese and Cunningham (2000), the gray limestoneaquifer is not present within the study area. The Biscayneaquifer, however, is present within the study area and isthe primary water producing part of the surficial aquifersystem. Fish (1988) defines the Biscayne aquifer as

that part of the surficial aquifer system in southeastFlorida comprised (from land surface downward) ofthe Pamlico Sand, Miami Oolite, Anastasia Formation,Key Largo Limestone, and Fort Thompson Formationall of Pleistocene age, and contiguous highly perme-able beds of the Tamiami Formation of Pliocene agewhere at least 10 feet of the section is very highly per-meable (a horizontal hydraulic conductivity of about1,000 ft/d or more).

With this definition, Fish (1988) mapped the base ofthe Biscayne aquifer in the western part of the study areaat an elevation of about −37 m. At the Pompano Beachwell field, Fish (1988) mapped the base of the Biscayneaquifer at an elevation of about −98 m, which is slightlyhigher than the elevation of −122 m suggested by Tarver(1964, 8) for the Pompano Beach well-field area.

Implicit in the Fish (1988) definition is that the topof the Biscayne aquifer coincides with the water table.Restrepo et al. (1992) and Dunn (2001), however, notethat a blanket of less permeable sand (of the Pamlico Sandand Anastasia Formation) is present in most areas. Theydefine the top of the Biscayne aquifer as being the firstoccurrence of highly permeable limestone. For the presentstudy, a similar distinction is made and the overlying lesspermeable sands are not included as part of the Biscayneaquifer. Accordingly, this paper discusses three parts ofthe surficial aquifer system: the upper part, the Biscayneaquifer, and the lower part. Ranges of aquifer properties assummarized from the literature are presented in Table 1.

Fish (1988) constructed a transmissivity map usingvalues from selected aquifer tests representative of thesurficial aquifer system. The transmissivity estimates usedto construct that map were used here with estimates ofBiscayne aquifer thickness to calculate hydraulic conduc-tivity. These hydraulic conductivities are thought to berepresentative of the average hydraulic conductivity overthe entire Biscayne aquifer thickness. Hydraulic conduc-tivities of individual zones within the Biscayne aquifer areprobably much different than these average values. Never-theless, these average values are used as starting hydraulicconductivities for the numerical model, which were thenadjusted as part of the calibration process.

Salt Water Intrusion near the Pompano Beach Well FieldConstruction of the Pompano Beach well field began

in 1926 with the completion of the first well in 1927 (Dunn2001). The well field was located on the Atlantic CoastalRidge because the underlying surficial aquifer system near


Table 1Summary of Aquifer Properties for the Surficial Aquifer System

Property Value References Comment

Kh (upper part of surficialaquifer system)

15 m/d Fish (1988)

Kh (Biscayne aquifer) 80–20,000 m/d Fish (1988, Table 4) Values calculated from multiplepumping test results and aquiferthickness at different locations

Kh (lower part of surficialaquifer system)

0.1–20 m/d Fish (1988)

Kv:Kh (Biscayne aquifer) 1:7 to 1:49 Camp and McKee, Inc. (1980)Sy (Biscyane aquifer) 0.004–0.30 Fish (1988)Sy (Biscayne aquifer) 0.093–0.25 Camp and McKee, Inc. (1980)Sy (Biscayne aquifer) 0.20–0.25 Merritt (1996a) Analysis based on rainfall-event-based

water level fluctuations inMiami-Dade County

αL, αT (Biscayne aquifer) 1–10, 0.1–1 m Langevin (2001, 2003) Calibration of variable-densitygroundwater model in Miami-DadeCounty

αL, αT (Biscayne aquifer) 76, 0.03 m Merritt (1995) Calibration of solute transport model inMiami-Dade County

αL, αT (Biscayne aquifer) 2.0–2.5 m Renken et al. (2008) From a tracer test in Miami-DadeCounty

n (Biscayne aquifer andlower part of surficialaquifer system)

0.37–0.48 Fish (1988) Analyses performed on core-scalesamples

n (surficial aquifer system) 0.20 Merritt (1996b)n (Biscayne aquifer) 0.20 Langevin (2001)n (Biscayne aquifer) 0.4 Renken et al. (2008) Based on one-dimensional simulations

of a tracer test in Miami-Dade County

Notes: A range is reported for some properties because more than one value is reported in the literature. Kh is horizontal hydraulic conductivity; Kv is verticalhydraulic conductivity; Sy is specific yield; αL is longitudinal dispersivity; αT is transverse dispersivity; n is porosity.

the ridge tends to have better groundwater quality thanareas to the west (Tarver 1964). Five additional productionwells were drilled during the 1950s. By 1972, the wellfield consisted of a total of 16 production wells (Figure 2).These wells were completed in a production zone of theBiscayne aquifer that extends from about 22 to 43 mbelow sea level. Production well 1 was abandoned inthe mid-1980s (Dunn 2001) because of elevated chlorideconcentrations.

Using measured chloride concentrations at monitor-ing wells and an estimate of the vertical chloride con-centration gradient, Dunn (2001) mapped the temporalevolution of the position of the 250 mg/L isochlor nearthe well field. Contours of the 250 mg/L isochlor at thetop of the production zone (about 22 m below sea level)are shown in Figure 2 for selected years between 1972 and1999. The isochlor advanced to its furthest inland positionin 1984 and then moved seaward to its last mapped posi-tion in 1999. Identifying the contributing factors, such asdrought and groundwater withdrawals, to the advance andsubsequent retreat of saline groundwater is not straight-forward as there are likely many factors contributing tosalt water movement.

Relevant data for the Pompano Beach well-fieldarea are shown in Figure 3 to summarize the hydrologic

conditions that led to the advance and subsequent retreatof saline groundwater in the surficial aquifer system.Rainfall variations have been suggested by Dunn (2001)as one of the primary drivers for the salt water intrusionevent that began in the mid-1970s. For the 1970 to 1981period, 11 out of the 12 years had rainfall values less thanthe long-term mean, and this period corresponds to a timeof salt water intrusion.

Groundwater withdrawals from the Pompano Beachwell field are probably a dominant cause of the saltwater intrusion event. From 1950 to 1980, withdrawalsat the Pompano Beach well field continued to increase.By 1980, groundwater withdrawals reached 1 × 105

m3/d (Figure 3). Based on a simple Theis analysisof predicted drawdown, Tarver (1964) warned thatwithdrawals exceeding about 7.6 × 104 m3/d could causesalt water intrusion and suggested that an expansionof the well field to the north and west would reducethe potential for salt water intrusion by distributing thewithdrawal effects. The withdrawal threshold calculatedby Tarver (1964) was first exceeded in 1971. In 1984,the City of Pompano Beach constructed the Palm Airewell field about 5 km west of the Pompano Beach wellfield (Figure 1). The late 1980s to the present showsa redistribution of groundwater withdrawals from the


Figure 3. Plots of rainfall, groundwater withdrawals, water levels, and TDS concentration for selected monitoring wells.

Pompano Beach well field to the Palm Aire well field(Figure 3). Reluctance by water managers to constructnew well fields in the western part of the county wasdue to the occurrence of poor quality groundwater (Howie1987).

Water levels of the Atlantic Ocean, Cypress Creekand Hillsboro Canals, and the G-853 monitoring well pro-vide insight into the salt water intrusion event (Figure 3).Both the Hillsboro and Cypress Creek Canals maintainrelatively constant stages from about 1970 onward. TheAtlantic Ocean, however, shows an increase of about25 cm from 1900 to 2005. By itself, the rise in sea leveldoes not explain the salt water intrusion event, but it mayhave been a contributing factor. The most striking featureof the water levels in Figure 3 is the sharp decline in theG-853 monitoring well, which is located near the centerof the well field. Water levels in this well remained nearor below sea level for the 1970 to 1990 period. A watertable map constructed by Sherwood et al. (1973) for May1971 showed water levels 1-m below sea level for muchof the Pompano Beach well-field area.

An interesting characteristic of the salt water intrusionevent was that salt water intruded more rapidly in the

production zone than in the layer beneath the productionzone. The G-2055A monitoring well was open to theproduction zone and salinity concentrations started to risein 1974. The G-2055 monitoring well, located next toG-2055A, but open in a deeper zone, did not begin toshow elevated salinity concentrations until about 1983.Data from these two wells indicate the presence of anisolated salt water wedge in the middle part of theaquifer.

The City of Pompano Beach owns and maintains themunicipal golf course adjacent to the Pompano Beachwell field (Figure 2). The golf course is irrigated usingtreated waste water. Irrigation rates were intentionallyincreased above what is needed to maintain the golfcourse in order to provide artificial recharge and preventsalt water intrusion. Irrigation with treated waste waterbegan in August 1989. The average irrigation rate from1989 to 2005 is about 4300 m3/d. Averaged over thearea of the golf course, this rate is about 120 cm/year,which is similar to the average annual rainfall rate ofabout 150 cm/year. The importance of excess golf courseirrigation on minimizing the potential for salt waterintrusion was evaluated with a sensitivity analysis.


Model Development and CalibrationA variable-density groundwater flow and solute trans-

port model was developed for the northern part ofBroward County to evaluate the causes of salt water intru-sion near the Pompano Beach well field and to determineif historical sea-level rise was a factor. The model wasthen used to predict the effect of alternative rates ofsea-level rise on salt water intrusion. To ensure that theinversion process had the flexibility to extract the mostinformation from the observation data set, the model wascalibrated for a 105-year simulation period (1900 to 2005)using a highly parameterized approach. Simulation of thisa long time period is computationally intensive, and so itis worthwhile to comment on the rationale for choosingthe calibration period length, which was established earlyin the study. First, sea level has risen by about 25 cmover this calibration period; therefore, sensitivity analysescan be used with the calibrated model to test the effectof that 25-cm rise on salt water intrusion in the area. Itmay not be possible to resolve the importance of sea-level rise with shorter simulations. Second, it is difficultto assign initial conditions to salt water intrusion mod-els. Models with long simulation periods tend to be lesssensitive to errors in initial concentrations than modelswith short simulation periods. Lastly, there was no wayto quantify how long it would take for saline groundwaterto respond to hydrologic variability. Because the hydrol-ogy changed drastically over the 105-year period, a longcalibration period seemed necessary in order to ensure thatit contained the hydrologic forcings responsible for caus-ing salt water movement. Parameter estimation with flowand transport observations has not been applied to three-dimensional sea water intrusion problems (Carrera et al.2010); however, Dausman et al. (2010) applied automatedinversion techniques for a related problem of buoyancy-driven plume migration. This study, therefore, is amongthe first to apply sophisticated calibration strategies to athree-dimensional salt water intrusion model.

Several numerical models of groundwater flow havebeen developed for Broward County. Restrepo et al.(1992) designed a groundwater model to address problemsassociated with water supply; however, the model didnot include a variable-density component. Two modelsdesigned to evaluate salt water intrusion in southernBroward County, south of the present study, are describedby Andersen et al. (1988) and Merritt (1996b). Othervariable-density models developed for nearby areas toevaluate groundwater flows or salt water intrusion aredescribed by Langevin (2001, 2003), Dausman andLangevin (2005), and Guha and Panday (2012).

Simulation CodesSEAWAT is a coupled version of MODFLOW

and MT3DMS designed to simulate variable-densitygroundwater flow and solute transport (Guo and Langevin2001; Langevin et al. 2003; Langevin and Guo 2006). Theprogram has been used to address a variety of issues,such as submarine groundwater discharge (Langevin2001, 2003) and salt water intrusion (e.g., Shoemaker

and Edwards 2003; Rao et al. 2004; Shoemaker 2004;Masterson 2004; Dausman and Langevin 2005; Hugheset al. 2010), for example. The simulations reported herewere performed using SEAWAT Version 4 (Langevin et al.2008), which is based on MODFLOW-2000 (Harbaughet al. 2000) and MT3DMS Version 5 (Zheng and Wang1999; Zheng 2006).

For the present application, the solute concentration(C) simulated by the model is the total dissolved solids(TDS) concentration of sea water salts. Fresh water isassumed to have a TDS concentration of zero; sea wateris assumed to have a TDS concentration of 35 g/L. Fluiddensity (ρ) is calculated by SEAWAT using a linear rela-tion subject to the constraints that fresh water has a fluiddensity of 1000 kg/m3 and sea water has a density valueof 1025 kg/m3. The resulting equation of state used forall of the simulations reported here is: ρ = ρf + 0.714 C.In some instances, chloride concentration measurementswere available. These concentrations were converted toTDS concentrations using a simple linear relation betweensea water, which has a chloride concentration of about19,800 mg/L, and fresh water, which is assumed to havea chloride concentration of zero. A chloride concentrationof 250 mg/L is commonly used as a maximum concentra-tion for potable water. In terms of TDS, this equates to aconcentration of 0.44 g/L.

Many of the preliminary simulations used the implicitfinite-difference solution method in MT3DMS and SEA-WAT to solve the solute transport equation. Later testsrevealed, however, that this solution scheme was caus-ing an excessive level of numerical dispersion, resultingin a high level of parameter surrogacy, and difficultieswere encountered in trying to reproduce observed salin-ity variations in monitoring wells. Parameter surrogacyoccurs when the inversion process adjusts parameter val-ues in order to compensate for errors in the model, suchas numerical dispersion. The simulations reported hereused the explicit third order, Total variation diminishing(TVD) scheme in MT3DMS and SEAWAT as an alter-native to the standard implicit finite-difference scheme.TVD is mass conservative and can minimize numericaldispersion, but because it is an explicit scheme, it is sub-ject to time step constraints and can be computationallydemanding. TVD simulations better represented the pre-sumed level of hydrodynamic dispersion as evidenced byan improved ability to represent observed salinity varia-tions compared with finite-difference transport solutions.Related work by Langevin and Hughes (2009) showed thatcalibration of a highly parameterized salt water intrusionmodel can result in parameter surrogacy, such as hetero-geneity artifacts in the presence of numerical dispersion.These artifacts can be reduced by using high levels of gridresolution or TVD schemes that minimize numerical dis-persion and also by using uniform concentration weightingschemes for calibration instead of assigning weights thatare proportional to the concentration value.

Preliminary simulations of the salt water intru-sion event had difficulties reproducing the relativelyquick response of salinity concentrations in groundwater


monitoring wells. Numerous attempts to capture theresponse with alternative parameterization approaches andparameter values repeatedly failed until the conceptualmodel for transport was revised. The surficial aquifer sys-tem in southern Florida is highly heterogeneous in both thevertical and horizontal directions. Recent work in south-eastern Florida (Cunningham et al. 2006, 2009; Renkenet al. 2008) has identified the presence of preferential flowpathways that likely play a key role in transport eventhough they comprise only a fraction of the aquifer totalthickness. To accommodate these important groundwaterflow pathways, the dual-domain capabilities in MT3DMS(and SEAWAT) were used (Zheng and Wang 1999). Withthe dual-domain approach, the aquifer is conceptualizedas having a fast moving mobile domain and an immo-bile domain. All advective transport occurs within the fastdomain, and solute exchange between the two domainsoccurs based on an exchange coefficient and the con-centration difference. Lu and Luo (2010) demonstratethe effect of the dual-domain conceptual model on saltwater intrusion simulations. The dual-domain approachwas used for all the simulations reported here.

The salt water intrusion model was calibratedusing the PEST software suite (Doherty 2009a, 2009b).PEST uses the Gauss-Marquardt-Levenberg algorithm toestimate parameters by minimizing weighted residualsbetween observations and simulated equivalents. To avoidproblems with numerical instabilities and to allow for theestimation of many more parameters than there are obser-vations, PEST contains several options for regularizingthe problem into one that is tractable. For example, PESTcontains subspace regularization methods (singular valuedecomposition [SVD]) as well as Tikhonov methods. Forthe present application, the SVD-assist technique (Doherty2009a, 2009b), which is a combination of both subspaceand Tikhonov methods, was the approach used for modelcalibration. Parameter estimation methods based on per-turbation sensitivities can benefit greatly from paralleliza-tion (Carrera et al. 2010). To facilitate tractability of theparameter estimation process, a cluster computer with 232computer cores was used.

Spatial and Temporal DiscretizationThe model grid consists of 115 rows and 160

columns (Figure 4). Each model cell is 150 by 150 m.In the Universal Transverse Mercator (UTM) Zone17 coordinate system and the horizontal 1983 NorthAmerican Datum (NAD 83), the southwest corner of themodel grid is located at x = 570,000 and y = 2,898,350.There is no rotation of the model grid from the UTMcoordinate system. The model is bounded on the west byWater Conservation Area 2A, to the north by the HillsboroCanal, to the south by the Cypress Creek Canal, and tothe east by the Intracoastal Waterway and the AtlanticOcean. Although the extent of the model grid includesthe barrier island system, groundwater flow within theshallow isolated lens of the barrier island is only roughlyapproximated owing to an insufficient grid resolutionrelative to the island width.

Figure 4. Model grid, inland and coastal pilot points, andlayer 1 boundary conditions for stress period 783 (December2005).

Nine model layers were used to discretize the surficialaquifer system. Model layers 1 and 2 correspond to theunconsolidated sediments of low to moderate permeabilitythat overly the Biscayne. Layers 3 through 8 correspondto the highly transmissive Biscayne aquifer, and layer 9represents the lower part of the surficial aquifer system,which tends to be less permeable than the Biscayneaquifer. Land surface elevation was estimated using 10-m horizontal resolution, U.S. Geological Survey (USGS)digital elevation models. The bottom of model layer 1 wasset uniformly at an elevation of −5.0 m. This elevationwas set lower than the lowest anticipated water tableelevation so that wetting and drying problems common toMODFLOW-based codes could be avoided. The bottomof model layer 2 was specified using elevation data fromthe bottom of layer 2 of an existing Broward County flowmodel (Restrepo et al., 1992). Layer 2 of that model alsocorresponded to the lower permeability sands overlyingthe Biscayne aquifer. Spatial interpolation using estimatesof the bottom of the Biscayne aquifer (Fish 1988) wasused to assign elevations for the bottom of model layer8. The thickness of the Biscayne aquifer (bottom oflayer 8 subtracted from bottom of layer 2) was thendivided equally among model layers 3 through 8. Spatialinterpolation using estimates of the bottom of the surficialaquifer system (Fish 1988) was used to assign elevationsfor the bottom of model layer 9.

SEAWAT follows the MODFLOW and MT3DMSconvention of stress periods, flow time steps, andtransport time steps (Langevin et al. 2003). Hydrologicstresses remain constant for each stress period, with theexception of specified heads. Specified heads are linearlyinterpolated within a stress period from starting andending head values assigned for each stress period. Time isfurther discretized in SEAWAT using transport time steps.


For each transport time step, SEAWAT first solves the flowequation and then solves the transport equation. AlthoughSEAWAT contains options for iteratively solving the flowand transport equations until the solution meets a specifiedconvergence criterion, this option was not used for thepresent study.

The 105-year simulation period, beginning January 1,1900, and ending December 31, 2005, was divided into783 stress periods. The first three stress periods representthe 40 years from January 1, 1900 to December 31, 1940.The first stress period represents the time period priorto the construction of major canals. The second stressperiod starts January 1, 1907, which is the approximateconstruction date of the Hillsboro Canal, and extendsthrough December 31, 1929. The third stress period startsJanuary 1, 1930, which is the approximate constructiondate of the Pompano Canal, and ends December 31, 1940.One flow time step, which can be used in SEAWATto control the frequency of writing output, was usedper stress period. Lengths of transport time steps werecalculated during the simulation using a specified Courantnumber of 0.75.

Representation of Hydrologic StressesHydrologic stresses were included in the model as

boundary conditions or as internal sources and sinks.In most instances, representation of hydrologic stressesrequired specification of a flux or head-dependent con-dition and the specification of a solute concentration orflux. Accordingly, each hydrologic stress is discussedboth in terms of its effect on groundwater flow andsolute transport. The hydrologic features and the MOD-FLOW/SEAWAT package used for their representation inthe model are summarized in Table 2.

A simplified linear equation was used to estimatethe Atlantic Ocean stage relative to NGVD 1929 for the1900 to 1940 period (C. Zervas, National Oceanic andAtmospheric Administration [NOAA], written communi-cation, 2007):

Stage = 2.39 mm/year (year − 2000) + 22.6 mm.

For the remainder of the simulation period, data fromthree NOAA tide stations were combined. From January1941 to June 1981, tide data from the NOAA MiamiBeach tide station (station identification number 8723170)were used. From August 1981 to August 1992, datafrom the Haulover Pier tide station (station identificationnumber 8723080) were used. From February 1994 toDecember 2005, data from the Virginia Key station(station identification number 8723214) were used. Theresulting Atlantic Ocean stage record, as used in themodel, is shown in Figure 5.

Parameterization, Regularization, and Initial ParameterValues

Application of formal parameter estimation tech-niques requires parameterization of aquifer properties andinitial parameter values from which calibration takes

place. The initial parameter values should be assignedbased on existing system information. For highly parame-terized models, some form of regularization must also beapplied for the problem to be tractable. For the presentstudy, preferred value regularization was applied to allparameters using the initial parameter value.

An irregular distribution of 97 pilot points (Doherty2003), with a higher density of points near the PompanoBeach well field, was used to parameterize Kh (Figure 4).These 97 pilot points were used for each model layer.Ordinary kriging was used with an isotropic exponentialvariogram and a range of approximately 7.5 km tointerpolate between pilot points. Statistics on the initialKh parameter fields and the minimum and maximumrestricted values during calibration are provided inTable 3. Initial Kh pilot-point values for the Biscayneaquifer (model layers 3 to 8) were assigned using aspatially variable Kh map prepared using the aquifer testsreported in Fish (1988). At each pilot point, 80% of theBiscayne aquifer transmissivity was apportioned evenlyamong layers 3 through 5 (the production zone) andused as the initial value for calibration. The remaining20% of the Biscayne aquifer transmissivity was evenlyapportioned among model layers 6 through 8. In coastalareas, Kh pilot-point values were allowed to vary forall layers. For inland pilot points, however, a single Khmultiplier was used to scale the initial Kh values in modellayers 3 through 8 by a single value.

A similar pilot-point methodology was used for theKh:Kv ratio and n. An initial parameter value of 100 wasassigned to Kh:Kv for all model layers. For inland pilotpoints, the Kh:Kv ratio in model layers 3 through 8 wereadjusted by a single factor. The Kh:Kv ratio was restrictedto a range between 1 and 10,000. An initial parameterfield of 0.25 for the mobile domain porosity (n) wasassigned for model layers 1, 2, and 9; based on preliminarysimulations of salt water movement, an n value of 0.10was assigned to the Biscayne aquifer (layers 3 through8). For calibration, n was restricted to a range between0.05 and 0.40. Use of a lower n value than found in theliterature for layers 3 through 8 was required to match thesalt water intrusion event and subsequent flushing. Themodel could not match the timing of these events withhigher n values, providing further support for the conceptof preferential flow zones in the Biscayne aquifer. Similarto Kh and Kh:Kv, n values for model layers 3 to 8 wereadjusted by a single factor at inland pilot-point locations.

During parameter estimation, the conductance foreach canal reach was updated using the spatially variableKh field because these dredged canals typically havegood hydraulic connection with the adjacent aquifer.This approach provided the inversion process with amechanism for adjusting aquifer-canal interaction. Otherparameters estimated as part of the calibration processare included in Table 4. These parameters do not varyspatially or temporally. In the absence of literature values,results from preliminary sensitivity simulations were usedto determine initial values for these parameters. Forexample, a relatively low value was required for the


Table 2Hydrologic Feature and the Package Used to Represent the Stress

Hydrologic FeatureMODFLOW/SEAWAT

Package Comment

Atlantic Ocean andIntracoastal Waterway

CHD Cells with center elevations above the Atlantic Ocean sea floor arerepresented as time-varying specified heads with the TDSconcentration for inflow specified as 35 g/L. Intracoastal waterwaycells are also included as time-varying specified heads, but with aTDS concentration of inflow specified as 27 g/L (BCDPEP 2001)and only in model layer 1.

Predevelopment freshwater wetlands

GHB Everglades fresh water wetlands were represented in western parts ofthe model in stress period 1 with a TDS concentration of zero. Thestage was set to 4 m, and the hydraulic conductance was calculatedusing the cell area, half the cell thickness of model layer 1, and theestimated vertical hydraulic conductivity of model layer 1.

Primary watermanagement canals

GHB Primary water management canals (Hillsboro, L36, Pompano, andCypress Creek) were represented in model layers 1 and 2 usinghistorical stage measurements. Canals were activated in the modelbased on construction date. Hydraulic conductance was calculatedfor each canal cell using an estimate of the aquifer-canal contactarea, the estimated horizontal hydraulic conductivity of the aquifer atthat cell, and a flow length of 50 m. A TDS concentration of 8 g/Lwas specified for the tidal part of the Hillsboro Canal and 18 g/Lwas assigned for the tidal parts of the Pompano and Cypress CreekCanals. These concentrations were calculated using water-qualitydata reported in BCDPEP (2001).

Secondary watermanagement canals

RIV Secondary and tertiary water management canals were represented inmodel layer 1 using the RIV Package. Canal activation date, stage,and hydraulic conductance were assigned using the same proceduredescribed for the primary water management canals.

Tidal canals GHB and RIV Tidal finger canals were assigned Atlantic Ocean stages and TDSconcentrations of the adjoining water body (Intracoastal Waterway,Hillsboro Canal, or Cypress Creek Canal). Tidal canal activationdate and hydraulic conductance were assigned using the sameprocedure described for the primary water management canals.

Recharge RCH A spatially uniform recharge rate was assigned to model layer 1 basedon measured rainfall totals. No attempt was made to subtract runoff,interception, and unsaturated zone evapotranspiration quantities. Thisapproach was used by Merritt (1996a) and Langevin (2001, 2003) forsimilarly constructed groundwater models of Miami-Dade County.

Evapotranspiration EVT The evapotranspiration surface was calculated by subtracting a value of1.0 m from land surface to approximate microtopographic effects ofsmall depressions. The extinction depth was set to 7.0 m; thisrelatively large depth was explained by Merritt (1996a) asapproximating other processes not represented by the model. For thefirst three stress periods, a maximum evapotranspiration rate of151 cm/year was assigned (Merritt 1996a). For the remaining stressperiods, the maximum evapotranspiration rate varied by monthaccording to the rates estimated by Merritt (1996a).

Well-field withdrawals WEL Withdrawals at public supply wells were specified in the model basedon estimated pumping records for each well. For public supply wellswith open-hole intervals that spanned multiple model layers, thewithdrawal rate was apportioned based on the estimated horizontalhydraulic conductivity at that cell.

Golf course irrigation WEL Excess golf course irrigation (artificial recharge) was modeled byspecifying a flux to layer 1 model cells within the Pompano Beachmunicipal golf course. Measured irrigation totals not available for1993–1994 and 2002–2005 were estimated from other years. Thepercentage of the irrigation water that recharges the aquifer wascalculated as part of the calibration process. The TDS concentrationof the irrigation water was calculated using an average chlorideconcentration of 400 mg/L.

BCDPEP, Broward County Department of Planning and Environmental Protection.


Figure 5. The Atlantic Ocean stage record (relative to theNational Geodetic Vertical Datum of 1929) as used in themodel.

dual-domain mass transfer rate, which indicates that thesystem is advection dominated with little mass transferbetween the mobile and immobile domains. An advectiondominated system with slow exchange between the mobileand immobile domains is supported by the relatively fastrates of observed salt water intrusion and subsequentaquifer flushing, and by the lack of a pronounced tail onthe observed TDS concentration plots (Figure 3).

Initial conditions can be complicated to estimate fortransient salt water intrusion models because they arerarely known with any certainty, and they can have alarge effect on model predictions. A common procedureis to perform a steady-state simulation and then use theresulting salinity field as input for a subsequent transientanalysis. This approach was used early in the model

development process; however, steady-state conditionswere difficult to estimate, concerns over changes in sealevel raised questions about the defensibility of thisapproach, and long runtimes were required to achievesteady-state conditions. As an alternative, a variant ofthe pilot-point methodology, as described in Doherty(2009c), was used to parameterize the initial salinity field.Initial heads were not parameterized in this manner asthey equilibrated quickly relative to the length of thesimulation. Initial interface elevations were assigned tothe pilot points shown in Figure 4 using the salinityfield from a preliminary steady-state simulation. Ordinarykriging was then used to spatially interpolate the two-dimensional interface surface to the model grid. Thisinterface surface was then intersected with the three-dimensional model grid. Model cells with centroids abovethe surface were assigned an initial TDS concentrationof zero; model cells with centroids below the interfacesurface were assigned an initial TDS concentration of35 g/L. To represent a diffuse interface, an interface widthparameter was introduced whereby TDS concentrationdecreased upward and increased downward according toa sigmoidal function. The interface width parameter wasassigned an initial value of 10 m and was limited to arange between 1 and 50 m. Dausman et al. (2010) useda similar approach to parameterize a salinity field. The

Table 3Statistical Description of the Spatially Variable Horizontal Hydraulic Conductivity (Kh) Fields Prior

to Calibration

ParameterGroup

Mean(log[Kh])

Standard Deviation(log[Kh])

Initial Kh PilotPoint (Min)

Initial Kh PilotPoint (Max)

CalibrationMinimum Limit

CalibrationMaximum Limit

Kh1 1.176 0.0 15 15 0.001 100Kh2 1.176 0.0 15 15 0.001 100Kh3 2.327 0.303 43 572 0.001 10,000Kh4 2.327 0.303 43 572 0.001 10,000Kh5 2.327 0.303 43 572 0.001 10,000Kh6 1.726 0.303 11 143 0.001 10,000Kh7 1.726 0.303 11 143 0.001 10,000Kh8 1.726 0.303 11 143 0.001 10,000Kh9 0.845 0.0 7 7 0.001 100

Note: Kh values are in m/d.

Table 4Spatially Uniform Model Parameters Estimated as Part of the Calibration Process

Parameter Initial Value Calibration Minimum Limit Calibration Maximum Limit

Specific storage 1 × 10−5 /m 1 × 10−7 /m 1 × 10−3 /mSpecific yield 0.20 0.10 0.40Evapotranspiration Extinction depth 7 m 0.1 m 10 mMultiplier for golf course Irrigation

to Aquifer recharge0.20 0.1 0.9

Dual-domain mass Transfer rate 1.02 × 10−7 /d 1 × 10−10 /d 1.0 /dImmobile domain porosity 0.30 0.2 0.5


Table 5Observation Groups Used for Model Calibration

ObservationGroup Description

Weight Assignedto IndividualObservations

Number ofObservations witha Nonzero Weight

Objective FunctionValue Prior to

Calibration

HEADS Water levels in monitoring wells outsidethe area of interest

0.0 0 0

HEADS_POMP Water levels in monitoring wells withinthe area of interest

3.45 1735 6347

CONCS Salinity concentrations in monitoringwells outside the area of interest

2.55 1659 2064

CONCS_POMP Salinity concentrations in monitoringwithin the area of interest (this groupalso contains a time series of salinityconcentration difference at the G2055and G2055A nested monitoring wells)

7.43 2138 9209

C_WELL Measure of the total salt mass withdrawnat each public supply well over theentire simulation period (concentrationsless than 0.4419 g/L not included incalculation)

0.04 130 11,085

Note: The area of interest is shown in Figure 2.

advantage of this approach is that the parameter estimationprocess is given the freedom to adjust the initial salinityfield, if necessary, in order to better match observed saltwater intrusion patterns, and thus lengthy steady-state runscan be avoided.

Observations and WeightsWater levels and TDS concentrations in groundwater

monitoring wells and public supply wells comprised theobservation dataset used to calibrate the model. Temporaland spatial interpolation of model results was used toderive simulated values that corresponded in time andspace to the observations. The observation data set wasdivided into five observation groups (Table 5). Weightswere assigned uniformly to observations within a group.Weights assigned to each group were manually adjustedto achieve the intended contribution of the observationgroup to the composite measurement objective function.A wide variety of weighting schemes and weight valueswere tested as part of the calibration process. For example,concentration weights are typically related to the inverseof the concentration value to accommodate the assumedlevel of measurement error (Hill and Tiedeman 2007;Sanz and Voss 2006). While this approach tended toimprove the match for low concentrations, simulatedTDS breakthrough curves did not adequately characterizethe salt water intrusion event. Ultimately, the weightspresented in Table 5 were used.

The contribution of each observation group to thecomposite objection function was assigned on the basisof modeling objectives, an assessment of measurementerror, and experience gained from preliminary calibra-tion runs. The C_WELL observation group was intention-ally assigned the highest contribution to the measurement

objection function. Historical water-quality records anddiscussions with well-field personnel indicated that withthe exception of the public supply well at the southend of the well field, TDS concentrations of withdrawngroundwater never exceeded the potable limit (a chlorideconcentration of 250 mg/L, which equates to a TDS con-centration of about 0.4419 g/L). TDS concentrations ofwithdrawn groundwater simulated by the uncalibratedmodel (using the initial parameter values), however,exceeded potable limits at certain times indicating thatsalt water had intruded into the Pompano Beach wellfield. Accordingly, the C_WELL observation group wasassigned a relatively large weight to improve the capa-bility of the model to represent fresh water conditionsat municipal wells. TDS concentrations in monitoringwells near the Pompano Beach well field (Figure 2;CONCS_POMP) were weighted the next highest. TheCONCS_POMP group also contains a time series of con-centration differences at monitoring wells G2055 andG2055A. These derived observations were added tohelp the inversion process reproduce the isolated saltwater wedge in the middle of the aquifer. Water lev-els near the Pompano Beach well field and then TDSconcentration differences at other monitoring wells wereweighted the next highest. Outside of the Pompano Beachwell-field area, heads were assigned a weight of zero fortwo reasons. First, there was generally good agreementbetween simulated and observed heads with the uncali-brated model. This was not by chance, as many differentconceptualizations, parameter sets, and boundary imple-mentations were tested. The mean error and mean abso-lute error for the HEADS group were 0.03 and 0.41 m,respectively. Second, because groundwater levels in theBiscayne aquifer are highly dependent on exchanges with


the surface water system, errors in assignment of canalboundary levels have a large effect on simulated heads.Data exist for assigning some canal boundary levels, butthey were derived or interpolated when missing. Con-sequently, when nonzero weights were assigned to theHEADS group, the parameter estimation process adjustedhydraulic conductivity as the sole option for improvingthe head match (canal levels were not parameterized).Consequently, the resulting parameter fields did not seemreasonable as they tended to compensate for the structuralerror caused by errors in assigned canal stage. Becauseof this weighting approach and the focus on the PompanoBeach well field, the domain outside the area of interestwas not formally calibrated using PEST. This issue did notseem to affect the area of interest because the secondarycanal network is restricted to only the westernmost part ofthe area of interest, and because historical stage measure-ments for the Pompano and Cypress Creek Canals weregenerally of good quality.

Model CalibrationPEST was used with the SVD-assist methodology

for model calibration (Doherty 2009a, 2009b) to estimatea large number of parameter values, many of whichwere highly correlated. A preferred value regularizationconstraint was set for all of the estimated parametersbased on literature values and results of preliminarycalibration attempts with fewer parameters. The strengthof the regularization constraints was controlled throughPEST using a tuning variable. This variable was adjusteduntil a good fit was obtained with the measurementsand the estimated parameter values and distributionswere reasonable. The parameter estimation process madesubstantial progress in improving the fit between measuredvalues and simulated equivalents as shown in Table 6. Theinversion process was manually terminated on the 10thoptimization iteration as progress toward reducing themeasurement objective function had slowed considerably.For some previous calibration runs, the inversion processwas allowed to continue for more than 40 optimization

iterations, and while the matches between observedand simulated values were extraordinary, the resultingparameter fields contained a high level of heterogeneitythat was not considered reasonable.

Overfitting of the model to observations can reducethe accuracy of predictions (Doherty and Welter 2010).Even if the model was provided with the best possibleset of parameter values, there would still be disagreementbetween observed values and simulated equivalents. Thisis because the model observations contain measurementerror and because of structural errors in the modelcaused by numerical errors, simplifications of physicalprocesses, spatial and temporal averaging, inaccurateboundary values, and other model inadequacies. Thus,if the calibration process is allowed to overfit theobservations, parameter values may become polluted bymeasurement and structural errors. This overfitting mayreduce the predictive capability of the model if theprediction is dependent on the affected parameters. Tominimize the potential for this problem, the estimatedparameter fields and values were carefully evaluated toensure that the level of calibration achieved with theestimation process was consistent with the quality of theobservations and model errors.

Selection of the appropriate level of calibrationwas based on residual statistics, time-series plots ofobserved versus simulated values, plots of spatiallyvarying parameter fields, and estimated parameter values.To facilitate the discussion, the uncalibrated model isreferred to as Opt.0. The calibrated model for the firstoptimization iteration is referred to as Opt.1, and so forth.Opt.6 was selected as the model used for sensitivity andscenario analyses and is referred to later as the base casecalibrated model.

Time-series plots of water level and TDS concen-tration (Figure 6) highlight the progression of the cali-bration procedure for several of the key wells near thePompano Beach well field. Simulated water levels at theG-853 monitoring well near the center of the well fieldare in good agreement with observed water levels. This

Table 6Table of Residual Statistics for Selected Observation Groups

Optimization Iteration

Group Statistics 0 1 2 3 4 5 6 7 8

ME −0.260 −0.241 −0.193 −0.138 −0.104 −0.077 −0.046 −0.021 −0.030HEADS_POMP MAE 0.433 0.409 0.364 0.314 0.279 0.253 0.228 0.211 0.207

RMS 0.307 0.275 0.219 0.164 0.130 0.108 0.089 0.077 0.074ME −13.113 −12.350 −10.891 −8.641 −6.483 −4.950 −2.207 −0.820 −0.471

CONCS MAE 16.193 15.313 13.541 11.011 8.685 7.133 4.446 3.032 2.479RMS 478.334 426.133 329.704 216.841 136.608 93.741 43.902 28.892 22.575ME 4.059 3.990 3.791 3.151 2.575 2.051 1.844 1.322 1.190

CONCS_POMP MAE 9.687 9.105 8.178 6.736 5.631 4.956 4.320 3.951 3.465RMS 195.063 173.486 140.950 98.411 70.578 53.031 39.869 33.100 26.653

Notes: Residual statistics were calculated for those with nonzero weights. The number of values used to calculate these statics are listed in Table 5.ME = mean error; MAE = mean absolute error; and RMS = root-mean-square error.


Figure 6. Plots of observed and simulated water levels and TDS concentrations for selected monitoring wells. The fit betweenobserved and simulated values improves with increasing optimization number. Solid lines are for the Opt.6 base case model,which was used for the sensitivity analyses. Faint dashed lines are for other optimization iterations.

is true for all of the optimization iterations, includingthe uncalibrated model. Simulated TDS concentrations arehighly affected by the calibration process and it is clearthat calibration has improved the fit between observedand simulated values, but there are some obvious defi-ciencies. For monitoring wells G-2054, G-2055A, andG-2063, for example, maximum simulated concentrationsdo not match with maximum observed concentrations. Inthe mid-1980s, simulated concentrations are as much as10 g/L less than observed concentrations. Another modeldeficiency is the inability to accurately represent the

isolated salt water wedge detected at the G-2055Aand G-2055 wells. In addition to the observed TDSconcentration values used for calibration, a separate obser-vation set of temporal concentration differences at thesetwo wells was also used for calibration. Although thereare many explanations for this model deficiency, the lead-ing explanation is numerical dispersion caused by a lackof vertical model resolution. Thus, while broad salt watertransition zone characteristics over the width of the aquifermay be adequately represented, concentration differencesbetween layers may be underestimated.


(a)

(b)

Figure 7. Horizontal hydraulic conductivity (Kh, as a base10 logarithm) of the Biscayne aquifer estimated from (a) Fish(1988) aquifer tests and from (b) the Opt6. model calibration.

In general, estimated parameter values were within10% of their specified initial values, but there were someexceptions. For example, the multiplier used to convertthe irrigation flux to a net recharge flux was increasedfrom 20% in Opt.0 to 70% in Opt.6. Heterogeneity wasalso introduced in Kh, Kh:Kv, and n. Plots of the Opt.0and Opt.6 Kh fields (log transformed) for the Biscayneaquifer are shown in Figure 7. The vertically averagedKh fields were calculated by summing the transmissivityvalues for model layers 3 through 8 and dividing by theBiscayne aquifer thickness. The Opt.0 and Opt.6 Kh fieldsshare similar characteristics because the Fish (1988) datawere used as initial parameter values and as preferredvalue regularization information. Thus, in the absenceof informative observation data, estimated Kh valuesremained at their initial values. Near the Pompano Beachwell field, heterogeneity in the Kh field was introduced aspart of the calibration process to improve representationof the spatial and temporal pattern of the salt waterintrusion event. Most importantly, a band of lower Kh wasidentified near the well field. There are no other sources ofdata to suggest if this lower Kh band is real or not, but theability of the calibrated model to match G-853 water levels

(Figure 6) within the highly stressed well field providessome assurance that the estimated Kh field is reasonable.Plots of Kh:Kv and n (not shown) show similar degreesof heterogeneity as shown for Kh.

Prior to calibration, simulated TDS concentrations ofgroundwater withdrawn at the Pompano Beach well fieldwere higher than observed values. Historical data indicatechloride concentrations of the pumped groundwater neverexceeded drinking water standards for chloride (approxi-mately equal to a TDS concentration of 0.44 g/L) exceptin one withdrawal well. All the simulations show anincrease and subsequent decrease in the TDS concentra-tion of pumped groundwater. As the optimization numberincreases, the TDS concentrations of pumped groundwa-ter decrease to more realistic values near or below thepotable limit, which is consistent with historical obser-vations. In particular, there appears to be a large TDSdecrease and improvement in the simulated pumped con-centration between Opt.5 and Opt.6. This improvementbetween Opt.5 and Opt.6 is caused primarily by a low-ering of the Kh in the area to the east of the well field(Figure 7).

The model does a good job representing many ofthe important characteristics of the flow system at thewell-field scale. Simulated heads are in good agreementwith measured heads at G-853, for example, and thesimulated water table map (Figure 8) is consistent withpreviously published water table maps (e.g., Tarver 1964).Most importantly for the present investigation, the modelqualitatively represents characteristics of the salt waterintrusion event and subsequent flushing. Figure 8 showssimulated TDS concentrations in model layer 3 for six ofthe years evaluated by Dunn (2001). Figure 8 also showsthe 0.44 g/L TDS contour mapped by Dunn (2001) forthe top of the Biscayne aquifer. Thus, the inland extent ofthe colored salt water zones in Figure 8 can be compareddirectly with the Dunn (2001) contours also shown inthe figure. The model shows a gradual salinization of theaquifer during the late 1970s and 1980s, when drawdownsare the largest, and a subsequent freshening during the1990s, after water levels had risen. The model does not,however, represent some details of the events, such asthe exact spatial patterns of the intrusion or the precisetiming of the retreat. At the coastline, the model simulatesa zone with TDS concentrations less than 0.44 g/L. Thiszone forms at the top of the Biscayne aquifer due tofresh groundwater recharge from above. There are nogroundwater salinity data to confirm whether or not theBiscayne aquifer is fresh in this area, and so these resultsshould be evaluated with caution. Deeper model layersshow elevated TDS concentrations for this area.

Although a slight cone of depression can be seen inthe water table for 1999, water levels clearly increasedfrom 1984 to 1999 (Figure 8). The higher water tableelevations had a positive impact by flushing out someof the salt water at the top of the Biscayne aquifer. Theflushing can be attributed to a reduction in groundwaterwithdrawals, an increase in rainfall relative to the droughtperiod, and artificial recharge at the golf course. Effects of


Figure 8. Comparison between simulated TDS concentrations in model layer 3 and the mapped 0.44 g/L TDS contour of Dunn(2001). Contours of the simulated water table elevation are also shown to indicate the effect of groundwater withdrawals ongroundwater flow patterns.

the 25-cm rise in sea level over the 105-year simulationperiod cannot be directly quantified from the calibratedmodel, nor can the relative importance of the otherhydrologic stresses. For this reason, a sensitivity analysiswas performed to isolate the relative importance of thesefactors on salt water intrusion.

Effect of Historical Sea-Level RiseA qualitative sensitivity analysis was used to compare

the importance of historical sea-level rise to several

other key hydrologic factors: well-field withdrawals,annual recharge variations, and artificial recharge atthe golf course. The evaluation was performed bymaking a targeted adjustment to the input for the basecase calibrated model (Opt.6) and then rerunning thesimulation. This approach is consistent with the approachoutlined by Loaiciga et al. (2012) for isolating the effectof different stresses on salt water intrusion. In the caseof historical sea-level rise, a constant sea level at theestimated 1900 level was used for the entire 105-yearsimulation for the tidal canals, the Intracoastal Waterway,


and the Atlantic Ocean. The importance of well-fieldwithdrawals was evaluated by running a simulationwithout groundwater withdrawals. The next simulationwas used to evaluate the importance of droughts andannual variations in recharge. Dunn (2001) hypothesizedthat the 1971 to 1982 period of below average rainfall waspartially responsible for the observed salt water intrusionevent at the well field. To evaluate this hypothesis, asimulation was performed using a constant recharge ratecalculated from the average annual rainfall total. Lastly,the utility of the artificial recharge system was evaluatedby performing a simulation without artificial recharge.

As shown in Figure 9, historical sea-level rise doesnot have a large effect on the position of the 1 g/LTDS contour in model layer 4, compared to the effectof pumping, but the effect is discernible. In 1955, forexample, the 1 g/L contour for the simulation withoutsea-level rise is about 100 m seaward of the 1 g/L contourfor the calibrated model. The largest effect from historicalsea-level rise can be seen in 1995 near the southeasternpart of the well field. In this area, the 1 g/L contour is asmuch as 1 km farther inland for the calibrated model thanfor the simulation without sea-level rise. This difference inthe contour position is the result of the larger fresh waterflux toward the coast for the simulation without sea-levelrise. Thus, as sea level rises, the hydraulic gradient isreduced, the fresh groundwater flux decreases, and saltwater intrusion occurs. This response is consistent with ahead-controlled system.

An analysis of simulated well-field TDS concentra-tion (not shown) also indicates the effect of sea-level rise.

The calibrated model shows an increase in TDS beginningin about 1971 and with TDS values exceeding the potablelimit in 1984. Without a rise in sea level, the increase inTDS occurs within about a year of the calibrated model,but the well-field TDS concentration never exceeds thepotable limit. Most importantly, well-field TDS concen-trations are consistently about 0.2 g/L less from about1980 to 2002 for the case without sea-level rise. Althoughthis is a relatively small difference, it equates to a differ-ence in chloride concentration of about 100 mg/L, whichis important considering the drinking water standard is250 mg/L.

To further evaluate the head-controlled nature ofthe system in response to sea-level rise, the simulatedwater table from the calibrated model was compared tothe simulated water table from the sensitivity simulationwithout sea-level rise. Over most of the model domain,the elevation of the water table compares to within about0.02 m or less. Along a narrow band near the coast,however, the water table for the calibrated model is higherthan the water table for the simulation without sea-levelrise. Specifically, to the east of a line that connectsstructure G56 with G57 (the easternmost structures thatseparate the fresh water canals from the tidally influencedcanals; Figure 1), there are no fresh water canals toact as a strong head control and the relatively highland surface elevations along the Atlantic Coastal Ridgeallow the water table to rise without much restriction byevapotranspiration.

The sensitivity analysis clearly indicates that well-field withdrawals have the largest effect on the position

Figure 9. Results from the qualitative sensitivity analysis showing simulated results for the base case and for simulations ofconstant recharge, no sea-level rise, no groundwater withdrawals, and no artificial recharge. Contours are of the 1 g/L TDSconcentration in model layer 4.


of the 1 g/L TDS contour (Figure 9). By eliminatingpumping altogether, the 1 g/L TDS contour does notchange appreciably and the slight changes shown inFigure 9 can be attributed to construction of the tidalfinger canals, historical sea-level rise, and recharge vari-ations. To further evaluate the effect of well-field with-drawals, a range of different withdrawal increases anddecreases were simulated. By eliminating withdrawalsaltogether, there is no historical rise in TDS concentra-tions at the well field. Doubling withdrawals, however,show substantial increases in well-field TDS concentra-tions. Slight decreases in well-field withdrawal rates alsohave a large effect on well-field TDS concentrations. Hadthe actual well-field withdrawals been 25% to 50% less,model results suggest that salt water intrusion may nothave been a concern.

Sensitivity results indicate that rainfall variations andartificial recharge can affect salt water intrusion, but theeffects are much less important than effects of well-fieldwithdrawals. Results from the simulation with a constantrecharge rate are similar to the base case calibrated model,suggesting that the 1971 to 1982 period of less-than-average rainfall was not a predominant cause of salt waterintrusion near the well field (Figure 9). A likely expla-nation is that surface water was brought into the areaduring that time to maintain water levels of the primarycanals (Hillsboro and Cypress Creek). These canals do notshow a decrease in stage during that period (Figure 3), andwould have provided recharge to the aquifer to compen-sate for the drought conditions. Model results suggest thatartificial recharge at the Pompano Municipal Golf Coursehas a beneficial impact on salt water intrusion. In 1995,for example (Figure 9), elimination of artificial rechargein the sensitivity simulation results in the 1 g/L TDS con-tour being located as much as 1.5 km landward of theposition in the base case calibrated model. Contour posi-tions in 2005 also suggest that artificial recharge helps toprevent salt water from intruding near the well field.

Sensitivity to Projected Rates of Sea-Level RiseA sensitivity analysis was performed with the Opt.

6 model using four different rates of projected sea-levelrise and using the average annual hydrologic conditions(well-field withdrawals, canal stages, rainfall and artificialrecharge, and evapotranspiration rates) from the last yearof the calibration period (2005). Results from these 100-year simulations cannot be used to predict future ratesof salt water intrusion in response to sea-level rise,because the simulations do not include anthropogenicchanges, alternative rainfall patterns from climate change,or well-field management strategies. The results can beused, however, to investigate the sensitivity of salt watermovement to different rates of projected sea-level rise.For the first simulation, sea level was held constant atthe average annual 2005 level. For the remaining threesimulations, sea level linearly increased over the 100-year simulation at rates of 24, 48, and 88 cm/century asestimated in the IPCC TAR (Church et al. 2001). Sea-level

Figure 10. Simulated well-field TDS concentration for thesensitivity analysis of projected rates of sea-level rise. Theconcentrations were calculated as a volumetric average forgroundwater extracted from municipal wells at the PompanoBeach well field.

rise was represented in the model by linearly increasingthe stage of the Atlantic Ocean and tidal canals. Intra-annual variations in sea level were not represented in thesesimulations.

Figure 10 shows a plot of well-field TDS concen-tration relative to time for the four simulations. Thewell-field TDS concentration was calculated as a volu-metric average using the withdrawal rates and simulatedTDS concentrations at individual extraction wells. Useof average 2005 hydrologic conditions and a constantsea level result in TDS concentrations of the well-fieldexceeding drinking water standards after 70 years. Thisfinding suggests that the 2005 withdrawal rates may notbe sustainable with the 2005 hydrologic conditions. Whensea-level rise is included in the simulations, drinkingwater standards are exceeded 10 to 21 years earlier (after60 years for a rise of 24 cm/century; 55 years for a rise of48 cm/century; and 49 years for a rise of 88 cm/century).

Apparent rates of lateral salt water intrusion in modellayer 4 were calculated from these sensitivity simulationsusing the 1 g/L TDS contour. They are referred to hereas apparent because there is an upward component ofgroundwater flow near the well field, and thus, intrusionis not limited to horizontal movement. Apparent lateralintrusion rates are 15, 17, 18, and 21 m/year for the 0, 24,48, and 88 cm/century sea-level rise rates, respectively.Webb and Howard (2010) reported lateral salt waterintrusion rates (referred to as interface velocity in theirwork) for different ratios of hydraulic conductivity torecharge and for different rates of sea-level rise. Theirlargest reported intrusion rate was 4 m/year, which isabout four to seven times less than the rates reported here,but similar considering the substantial differences betweentheir simplified two-dimensional system and the PompanoBeach well-field area.

DiscussionThe Pompano Beach well-field area and nearby

coastal areas in southeastern Florida represent an end-member in the spectrum of impacts of sea-level rise on


salt water intrusion. The following are a number of generalobservations about southeastern Florida that help explainwhy the shallow coastal aquifer system is particularly vul-nerable to salt water intrusion caused by sea-level rise.

1. As shown by Werner and Simmons (2009), systemsthat are head controlled are more susceptible to saltwater intrusion caused by sea-level rise than thosethat are flux controlled. For confined aquifers thatare flux controlled, sea-level rise may not have anyeffect on salt water intrusion (Chang et al. 2011). Thewidespread canal system in southern Florida places anextensive head control on water levels in the shallowsurficial aquifer. The head control is particularly strongin southeastern Florida due to the direct hydraulicconnection between canals and the highly permeableBiscayne aquifer. Also, land surface is relatively flatwith little relief, and the unsaturated zone is thin (typ-ically less than a meter or two). Flooding from highwater tables can be a problem in many neighborhoods.Evapotranspiration rates are also relatively high andcan be similar to rainfall rates during the summermonths. These combined conditions effectively elim-inate the possibility for groundwater levels to rise assea level rises. Consequently, the seaward hydraulicgradient and associated fresh groundwater flow towardthe coast is expected to decrease.

2. Southeastern Florida has many tidally influencedcanals that extend inland into the permeable coastalaquifer. In some cases, tidal canals extend inland asfar as municipal well fields. These canals provideocean access for a thriving boating community. Nearthe Pompano Beach well field, the tidal portion ofthe Cypress Creek Canal extends inland as far as thePompano Beach well field. Tidal canals are also presentbetween the well field and the Intracoastal Waterway.These tidal canals, which have elevated salinities, havestages at or near the stage of the Atlantic Ocean. Arising sea level makes it difficult to maintain a seawardhydraulic gradient that is strong enough to prevent saltwater intrusion.

3. The highly permeable shallow aquifer system alsocontributes to the susceptibility of southeastern Floridato sea-level rise. The high hydraulic conductivitiesserve to reduce the seaward hydraulic gradient, causerapid water level declines after aquifer recharge events,and allow salt water to intrude the aquifer at relativelyfast rates.

4. Southeastern Florida is heavily populated with a largewater demand for potable as well as for environmentalpurposes; nearly all of the potable water is derivedfrom the shallow aquifer system, although there havebeen recent efforts to explore alternative water sources.Most groundwater is withdrawn near the coast at wellfields located along the Atlantic Coastal Ridge. TheAtlantic Coastal Ridge is the preferred location for wellfields because additional treatment is often required forpoorer quality groundwater withdrawn farther inland.Construction of the Palm Aire well field, located west

of the Pompano Beach well field, was an effectivemechanism for reducing groundwater withdrawals nearthe coast; shifting withdrawals inland raised the watertable near the coast and reduced the threat of salt waterintrusion.

The modeling analysis described in this investiga-tion can be used to quantify effects of sea-level risefor other areas. Therefore, it is important to summarizeimportant and transferable lessons such as those relatedto dual-domain transport, grid resolution, computationalissues, and modeling approach. Numerous challengeswere encountered in the development and calibration ofthe county-scale (300 km2) dispersive salt water intrusionmodel. Representing solute transport with a dual-domainapproach is consistent with geological knowledge of per-meable flow zones in the Biscayne aquifer and seemed toprovide a more accurate representation of salt water intru-sion than the traditional advection-dispersion approach.Without the dual-domain approach, there was no way tocalibrate the model (with a reasonable parameter set) sothat it could simultaneously represent the salt water intru-sion event and subsequent retreat of saline groundwater.

Numerical dispersion and use of appropriate gridresolution and transport schemes were among the mostdifficult challenges. Sanford and Pope (2010) encounteredthe same problem for a large 2000 km2 salt water intrusionmodel of the Eastern Shore of Virginia and questionedwhether concentrations at an individual well can beaccurately simulated by a numerical model of that scale.They suggest that in some instances, 10-cm thick modellayers may be required to accurately characterize thetransition zone between fresh and saline groundwater.Owing to computational limitations, Sanford and Pope(2010) were not able to use the TVD scheme inMT3DMS/SEAWAT for their problem, which would havehelped to reduce numerical dispersion as it did for thepresent application. For computation reasons, Sanfordand Pope (2010) used the relatively fast, implicit finite-difference scheme for solute transport. This made theproblem tractable with present computing technology.Additional numerical resolution would have been usefulfor the present study. The model was unable to representsome of the observed salinities in monitoring wells(e.g., G-2055); maximum concentrations tended to beunderestimated, for example. There are many possiblereasons why the model had difficulty in simulating thedetails of the salt water intrusion event (e.g., errors inthe conceptual model or problems with the data); itwould have been useful to eliminate numerical dispersionas a possibility. As shown by Langevin and Hughes(2009), calibration of a salt water intrusion model witha high level of numerical dispersion can have deleteriouseffects on the predictive capability of the model. If, forexample, some of the hydraulic conductivity heterogeneitywas introduced by the calibration process in order tocompensate for the effects of numerical dispersion, thenmodel predictions would be in error if the predictions weresensitive to that heterogeneity. As mentioned by Sanford


and Pope (2010), the capability to add resolution wherenecessary is desirable in this situation. A finite elementor finite volume model would have been one option.Another option for future studies would be to implementa local-grid refinement approach (Mehl and Hill 2002)in SEAWAT as a way to increase horizontal and verticalmodel resolution in areas where transport is importantand predictions depend on accurate representation of largehydraulic gradients. For these types of larger-scale studieswith potential difficulties in simulating dispersive solutetransport, one might also consider an entirely differentmodeling approach based on an existing sharp interfaceformulation, which is available in the Salt Water Intrusion(SWI) Package for MODFLOW (Bakker 2003; Bakkerand Schaars 2005). The sharp interface approach wasdesigned for regional salt water intrusion modeling, andwhile it cannot simulate solute concentrations, it is bydesign, free of any type of dispersion including numericaldispersion.

Calibration of the salt water intrusion model withina highly parameterized context was found to be usefulfor this study. The Pompano Beach well field consistsof 16 groundwater withdrawal wells. Extraction rates forthe wells are highly variable between wells and through-out time. The system also has many other spatially andtemporally variable stresses (variations in fresh and tidalcanal levels, recharge, artificial recharge, rainfall, evapo-transpiration) that confound interpretation of hydrologicrecords. Karst aquifers, such as the Biscayne aquifer, arehighly discontinuous and heterogeneous, both in their spa-tial and temporal functioning, and it is commonly difficultto separate the signal caused by a natural hydrologic eventfrom one caused by an anthropogenic event. It was dif-ficult to infer from the data subsurface areas that maybe more or less permeable, and there were few reliablepoint measurements of hydraulic conductivity. With thehighly parameterized calibration approach, features of thesystem were quantified by monitoring where and howparameters changed. In many instances, unrealistic param-eter distributions were used to identify deficiencies inthe numerical model, such as an erroneous prescribedcanal level or an error in a monitoring well location.Although not considered in this assessment, a next step inthis type of analysis is to quantify prediction uncertainty.Robust uncertainty measures can be calculated within thehighly parameterized context provided one can assignmeasures of parameter uncertainty. Future efforts to quan-tify sea-level rise impacts would benefit from consideringuncertainty quantification.

Uncertainties in the predicted salt water intrusionpatterns that result from sea-level rise were not quantified,but experience with the model suggests that there is a highlevel of uncertainty. As suggested by Konikow (2011)and experienced in this effort, solute transport modelsare particularly difficult to develop, and one should notexpect the same level of reliability as one might expectfor a groundwater flow model. Uncertainties caused bystructural model errors can be reduced by evaluatingdifferences in model simulations instead of focusing on

a specific numeric value produced from a single forwardmodel run (Doherty and Welter 2010). For the sensitivityanalysis of the projected sea-level rise, this means it ispreferable to state that well-field concentrations exceedthe potable limit 10 to 21 years sooner than for the casewithout sea-level rise.

This study focused on evaluating the sea-level riseprojections reported by the IPCC (Church et al. 2001).More recent projections by the IPCC (Meehl et al. 2007)seem to project sea level rising at a slower rate, butthe revised estimates do not include some feedbackmechanisms that are anticipated to occur, such as rapidice sheet melting. Recent studies (Pfeffer et al. 2008)have shown that sea level may rise by 0.8 to 2.0 mby 2100. Heimlich et al. (2010) summarize some of therecent sea-level rise projections and their possible effectson southeastern Florida. These larger rates of sea-levelrise were not tested with the model. It is reasonable toassume that increased rates of sea-level rise much largerthan those considered here would have serious impactson the fresh coastal groundwater supplies of southeasternFlorida. For these larger rates of sea-level rise, it is unclearif adaptation measures and changes to the infrastructurecould meet potable water demands while simultaneouslyproviding flood protection.

ConclusionsConditions near the Pompano Beach well field in

northern Broward County, Florida, provide a uniqueopportunity to examine the effects of historical andprojected sea-level rise on the fresh groundwater resourcesof a low-lying highly permeable coastal aquifer. Results ofa numerical modeling analysis suggest that groundwaterwithdrawals were the dominant cause of a multi-decadesalt water intrusion event, and that historical sea-level rise(about 25 cm for the simulation period) contributed to theextent of the intrusion by about 1 km. The historical rateof sea-level rise was similar to the lower-bound estimate(24 cm) of the IPCC (Church et al. 2001) projection forthe next century. A sensitivity analysis of four projectedrates of sea-level rise (24, 48, and 88 cm/century)comparatively illustrates the relative severity of thesituation in south Florida. Even if sea level does not risein the future, model simulations suggest that correctiveactions would likely be required to protect the aquiferfrom salinization. Corrective actions would be required asmuch as 21 years sooner depending on the future rate ofsea-level rise. The findings from this study are consistentwith general observations about the vulnerability ofsoutheastern Florida to salt water intrusion caused by sea-level rise. Southeastern Florida is particularly vulnerablebecause of (1) the overlying canal system, which acts asa strong head control, (2) the presence of tidal canalsthat extend inland, (3) the highly permeable shallowaquifer system, which includes the Biscayne aquifer, and(4) the large groundwater withdrawals from the coastalaquifer.


AcknowledgmentsSpecial acknowledgments to Darrel Dunn and Katie

Lelis of the Broward County Environmental ProtectionDepartment/Water Resources Division, Francis Hendersonand Dave Markward of the Broward County Officeof Environmental Services/Water Management Division,and Randy Brown, Maria Loucraft, and Alan Clarkof Pompano Beach Utilities Department for providingextensive information and data on the study site. A specialthanks to Winnie Said and Krista Guerrero-Reger of theSouth Florida Water Management District as well as GuyBartolotta of Broward County Environmental OperationDivision for providing model data sets and historicalwell-field pumping records, and to John Doherty for hiscontinued support with the parameter estimation program(PEST). Technical assistance was also provided by AlyssaDausman, Joann Dixon, and Roy Sonenshein. The authorsare grateful to John Masterson, Jeremy White, and threeanonymous reviewers for providing thoughtful commentsthat substantially improved the manuscript.

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