Estimating Pollutant Residence Time and NO3 Concentrations in the Yucatan Karst Aquifer; Considerations for an Integrated Karst Aquifer Vulnerability Methodology

water

Article Estimating Pollutant Residence Time and NO3 Concentrations in the Yucatan Karst Aquifer; Considerations for an Integrated Karst Aquifer Vulnerability Methodology

Carolina Martínez-Salvador 1, Miguel Moreno-Gómez 2,* and Rudolf Liedl 3

1 Erasmus Mundus GroundwatCH Master Study Program, Technische Universität Dresden, 01069 Dresden, Germany 2 Research Group “INOWAS”, Department of Hydrosciences, Technische Universität Dresden, 01069 Dresden, Germany 3 Institute for Groundwater Management, Technische Universität Dresden, 01069 Dresden, Germany * Correspondence: [email protected]; Tel.: +49 3501 530067

Received: 22 June 2019; Accepted: 11 July 2019; Published: 12 July 2019

Abstract: Karst aquifers are a major source of drinking water with intrinsic features that increase the pollution risk from anthropogenic and natural impacts. In Yucatan, Mexico, groundwater is the sole source of drinking water, also acting as receptor of untreated wastewater due to the low regional coverage of sewer systems. To protect karst groundwater, vulnerability methodologies are widely used. Worldwide, multiple karst vulnerability schemes have been developed and tested; however, none of these consider pollutant residence time or pollutant concentration as core parameters to estimate vulnerability. This work aims to define important considerations regarding the behavior of nitrates (NO3) in a real scenario, to be included in a new integrated vulnerability method. This work has two main objectives: to set up a groundwater model to depict as close as possible the groundwater behavior of the Yucatan karst system, and to introduce a transport model to estimate the behavior of a pollution plume. Model outcomes suggest that pollutants have a short residence time, reaching the coast in the north after 3 years. Well fields are also affected by pollution at variable NO3 concentrations. Results can be further discretized to establish a base and to include these parameters as part of a new integrated groundwater vulnerability approach.

Keywords: karst; vulnerability; residence time; Nitrate pollution; Yucatan; numerical modeling

1. Introduction Karst refers to a landscape where solubility of carbonate rocks allows the formation of caves, sinkholes and conduits [1]. Karsts aquifers are sensitive to pollution due to their intrinsic features including acting as a bypass between surface and water table, which allows pollutants to reach groundwater more easily and faster with little to no degradation in comparison with unconsolidated aquifers [2,3]. Besides the low natural protectiveness of karst, global change factors and urbanization increase the pollution risk in areas where wastewater and rainwater directly infiltrate into the aquifer. The Yucatan peninsula is an outstanding area for its karst features; however, the lack of systems to collect and treat wastewater enhances the pollution stress on the aquifer. Nowadays, the Yucatan aquifer is threatened from pollution sources at the surface and salt water intrusion [4]. Use of artisanal septic tanks is a common practice in Yucatan State. Since they are not impermeable, constant infiltration of wastewater into the aquifer occurs. This situation increases the pollution risk of well fields located in the periphery of urban areas [5–7].

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Local studies have assessed both the presence and the possible vulnerability implications of NO3 pollution in the Yucatan State (hereinafter Yucatan). Most of them conclude that some areas have already exceeded the permissible concentrations for human consumption according to national water quality standards [8–13]. The most relevant pollution scenario occurs in the sub-surface of Merida city. Due to a high population density and the lack of wastewater systems, a continuous infiltration of wastewater from artisanal (permeable) septic tanks has created a pollution plume contaminating the upper 15 m of the aquifer below the city [4,14]. However, the occurrence of this phenomenon in the subsurface of other cities in the region has not been investigated. In general, the actual anthropogenic scenario in Yucatan shows evidence of the continuous infiltration of pollutants from different sources including housing, poultry, livestock, landfills and industry. Vulnerability maps are a first step in the development of protection strategies; these multi- parameter methodologies estimate the travel time of a theoretical immutable pollutant from the surface to the water table, based solely on the intrinsic characteristics of the area and established definitions of intrinsic vulnerability [15,16]. Nevertheless, other important processes like pollutant residence time in the aquifer and pollutant concentrations that occur in real scenarios are not considered because the inclusion and evaluation of two or more independent criteria can lead to ambiguous results in a vulnerability analysis [17]. The current pollution scenario faced by Yucatan highlights the need to evaluate groundwater vulnerability in order to support protection strategies and a sustainable approach for the development of the region. However, relying on vulnerability maps, which only estimate the theoretical travel time from the surface to the water table can lead to questionable vulnerability classes due to their lack of correlation with regional characteristics [18]. Therefore, residence time and concentration of pollutants are important parameters to be analyzed and included as factors to estimate vulnerability classes for present and future scenarios. This could help to more accurately determine well protection areas or allocation, hazards management and future urban areas according regional development strategies. This work presents a model aiming to analyze pollution plume behavior under the city of Merida and its possible repercussions on well fields and communities located in the periphery. Analysis of NO3 concentrations and the travel time of pollutants will serve as a basis to propose important considerations to be taken into account in an Integrated Karst Aquifer Vulnerability methodology (IKAV).

2. Materials and Methods

2.1. Study Area The Yucatan Peninsula is located in the southeast of Mexico and is one of the biggest trans-boundary aquifers in the world—around 165,000 km2. It is shared by Mexico, Guatemala and Belize [19]. The Mexican part includes the states of Yucatan, Campeche and Quintana Roo (Figure1a). The Peninsula is composed mainly of limestone, with dolomite and anhydrite from the Mesozoic and Cenozoic periods reaching thicknesses > 1500 m [20]. The Peninsula aquifer contains a well-developed conduit system at variable scale ranges with primary and secondary porosity in the rock matrix [19]. Around 7.5 Mm3 of groundwater per year is extracted for human consumption [21]; however, fresh water extraction does not jeopardize the water availability since aquifer recovery is constant and fast [22]. Water balance in the region is positive, with a high availability per capita of about 7600 m3/person/year [23]; this value is high compared to the Mexican national average. Yucatan is a developing area, which places groundwater resources under special pollution stress and therefore, calls for strong protection policies. Yucatan is characterized by a tropical weather with a marked precipitation regime with variations in time and space. Mean precipitation ranges between 200–400 mm/year along the coastal area and 1000–1200 mm/year in the southeast [24]. Two distinctive periods are characterized: dry, from November to April, and wet, from May to October. The present study focuses on Yucatan, speciﬁcally on the Merida Metropolitan Area (MMA). With around 1.1 million inhabitants, out of the total Yucatan population of 2.1 million, the MMA is a densely populated area Water 20192019,, 1111,, 1431x FOR PEER REVIEW 3 of 1516

(MMA). With around 1.1 million inhabitants, out of the total Yucatan population of 2.1 million, the composedMMA is ofa sixdense municipalitiesly populated where area urbanization composed isof continuously six municipalities increasing where (Figure urbanization1b). The MMA is iscontinuously located inside increasing the hydrogeological (Figure 1b). The region MMA known is located as the inside Inner the Cenote hydrogeological Ring (ICR), region one ofknown four hydrogeologicalas the Inner Cenote regions Ring in (ICR), Yucatan one [ 25of]. four The hydrogeological ICR, also known regions as the Chixchulubin Yucatan sedimentary[25]. The ICR, basin, also isknown delimited as the by Chixchulub a semi-circular sedimentary belt of approximately basin, is delimited 180 km by ina diametersemi-circular [26]; belt this of belt, approximately also named the180 Cenotekm in diameter Ring, has [26]; a high this belt, sinkhole also density.named the This Cenote ring Ring, is considered has a high to sinkhole be a surface density. expression This ring of anis considered asteroid impact to be a at surface the end expression of the cretaceous of an asteroid period impact [27]. The at the ICR end is aof relatively the cretaceous new sedimentary period [27]. basinThe ICR with is aa low relatively level of new karstification, sedimentary although basin with it is fractured, a low level which of karstification, explains the low although number it ofis sinkholesfractured, insidewhich the explains ring compared the low number with the of crater sinkholes rim. Some inside of the the ring main compared characteristics with the of the crater area rim. are theSome flatness of the of main the terraincharacteristics and lack of of the surface area flow.are the The flatness ICR has of athe mean terrain slope and of 1.5%lack of and surface an average flow. altitudeThe ICR ofhas 28 a mmean above slope sea of level, 1.5%except and an for average a small altitude area in of the 28 southeastm above sea of thelevel, inner except ring. forThe a small flat topographyarea in the southeast and fracturing of the doinner not ring. allow The generation flat topography of surface and streams, fracturing infiltrating do not allow precipitation generation at fast of ratessurface [28 streams,]. Additionally, infiltrating flatness precipitation and high hydraulicat fast rates conductivity [28]. Additionally, originate flatness in low hydraulicand high hydraulic gradients rangingconductivity from originate 7 to 10 mm in/ kmlow with hydraulic groundwater gradients flow ranging in a north-west from 7 to direction10 mm/km [29 ].with groundwater

Figure 1. General characteristics of the study area; ( a) extension of the Yucatan PeninsulaPeninsula and main karst features; features; (b ) ( municipalitiesb) municipalities composing composing the MMA, the and MMA, (c) a basic and hydrogeological (c) a basic hydrogeological representation ofrepresentation the Merida city of the sub-surface Merida city (modiﬁed sub-surface from (modified Marín [4]). from Marín [4]).

The Yucatan aquifer faces faces constant constant pollution since sanitary sewer systems are almost non-existentnon-existent [4].[4]. Only Only around around 10% 10% of of the the generated generated grey grey and and black black water water is is treated treated in in Yucatan. Yucatan. Groundwater pollution risk increases in the MMA due to the increasing population density and the disposal of of household household and and industrial industrial wastewater, wastewater, which which is mainly is mainly disposed disposed into artisanal into artisanal septic septic tanks. Wastewatertanks. Wastewater undergoes undergoes short residence short residence times, atimes, couple a couple of hours, of inhours, such in tanks such because tanks because they are they not sealed;are not therefore, sealed; untreated therefore, wastewater untreated percolates wastewater and reachespercolates groundwater and reaches almost groundwater immediately almost[14,30]. Thisimmediately continuous [14,30]. infiltration This continuous from permeable infiltration septic tanksfrom permeable has created septic a plume, tanks contaminating has created thea plume, upper 15contaminating m of the aquifer the upper below 15 Merida m of citythe aquifer [31]. However, below Merida in recent city years [31]. theHowever, extension in ofrecent this pollutionyears the plumeextension has of been this measured,pollution plume reaching has up been 20 mmeasured, of depth (L.reaching Marín, up personal 20 m of communication, depth (L. Marín, July personal 2016) butcommunication, its extension Julyand hydraulic 2016) but behaviorits extension is still and unknown hydraulic (Figure behavior1c). Additionally, is still unknown in urban (Figure areas, 1c). rainwaterAdditionally, infiltrates in urban directly areas, into rainwater groundwater infiltrates through directly boreholes into groundwater located along through the streets; boreholes this is Water 2019, 11, x FOR PEER REVIEW 4 of 16 Water 2019, 11, 1431 4 of 15 located along the streets; this is a common practice for rainwater disposal in this region. aConceptualizati common practiceon forof t rainwaterhe general disposal Yucatan in aquifer this region. shows Conceptualization an unconfined fresh of the water general lens floating Yucatan aquiferabove saline shows water an unconfined which intru freshdes more water than lens 40 floating km inland above [32,33]; saline the water exception which is intrudes an area morealong thanthe 40coast km that inland is classified [32,33]; the as an exception aquitard is [34]. an areaFor simplification along the coast purposes, that is classifiedthis aquitard as an is not aquitard included [34]. in the model presented in this work. For simplification purposes, this aquitard is not included in the model presented in this work.

2.2.2.2. Methodology Methodology

2.2.1.2.2.1. Modeling Modeling ApproachApproach andand ConceptualConceptual ModelModel ToTo estimate estimate pollutant pollutant residence residence time, time,groundwater groundwater modeling modeling was carried was out carried using MODFLOW out using codeMODFLOW 2005 run code in Model 2005 Muserun in version Model 3.10.0.0Muse version (released 3.10.0.0 in March (released 2018). in The March working 2018). space The working was built byspace dividing was built theMMA by dividing into 50 the columns MMA in andto 7050 rowscolumns with and square 70 rows grids with of 1square km2. Forgrids output of 1 km analysis2. For purposes,output analysis an additional purposes, discretization an additional was discretization made between was columnsmade between 21 to 58columns and rows 21 to 30 58 to and 70 withrows a grid30 to size 70 ofwith 0.0025 a grid km size2 (Figure of 0.00252). Model km2 (Figure discretization 2). Model was discretization performed by was importing performed a Digital by importing Elevation a ModelDigital (DEM) Elevation into an Model ASCII (DEM) file using into ArcGIS an ASCII version file 10.5. using To ArcGIS get model version top elevation 10.5. To and get to model define top the thicknesselevation of and sub-surface to define layers,the thickness the fitted of sub surface-surface interpolation layers, the includedfitted surface in MODFLOW interpolation was included utilized. Thein MODFLOW bottom of the was aquifer utilized. was Thedefined bottom at 80 of m the below aquifer the surface. was defined Studies at have80 m estimated below thethe surface. saline interfaceStudies have as around estimated 58 m the of depth saline below interface Merida as around city. Since 58 m the of depth area of below interest Me inrida this city work. Since is the the MMA, area thisof interest depth is in representative this work is the enough. MMA, Hydraulicthis depth conductivitiesis representative (K) enough. are the sameHydraulic as those conductivities estimated from (K) aare groundwater the same as flow those model estimated in the from area assuminga groundwater EPM flow behavior model presented in the area in theassuming work of EPM Gonz behaviorález [22 ]. presented in the work of González [22].

Figure 2. Discretization of the study area, view from South to North. The X axis represents Universal Figure 2. Discretization of the study area, view from South to North. The X axis represents Universal Transverse Mercator coordinates (UTM) and Y axis depth in meters. Transverse Mercator coordinates (UTM) and Y axis depth in meters. To describe turbulent flow in the karstic aquifer, the Conduit Flow Process (CFP) package is To describe turbulent flow in the karstic aquifer, the Conduit Flow Process (CFP) package is used [35,36]. However, the CFP package has a drawback when modeling target pollution studies due used [35,36]. However, the CFP package has a drawback when modeling target pollution studies to its incompatibility with the groundwater solute transport simulator of MODFLOW (MT3DMS). due to its incompatibility with the groundwater solute transport simulator of MODFLOW Therefore, two modeling steps were applied to solve this problem: (MT3DMS). Therefore, two modeling steps were applied to solve this problem: The CFP was applied for particle tracking to obtain a general idea of the residence time of any • The CFP was applied for particle tracking to obtain a general idea of the residence time of any particleparticle in in the the aquifer, aquifer, not not considering considering transporttransport processes.processes. An equivalent porous media (EPM) model was adjusted with the CFP parameters to enable the • An equivalent porous media (EPM) model was adjusted with the CFP parameters to enable the MT3DMSMT3DMS to to run run with with nitrate nitrate data data to to analyze analyze the the pollution pollution plume plume behavior behavior within within the studythe study area. area. The void diameter percentage, required for the CFP,was set at 0.9 given the existence of preferential flowsThe paths void at di diameterfferent depths percentage, of the aquifer. required However, for the CFP, as a waspre-test, set at the 0.9 void given value the was existence evaluated of betweenpreferential 0.9 and flows 0.5, paths without at different significant depths effects. of the Reynolds’s aquifer. However, numbers were as a pre maintained-test, the atvoid 2000 value and was 4000 asevaluat the defaulted between settings 0.9 in and the 0.5 program., without significant effects. Reynolds’s numbers were maintained at 2000 and 4000 as the default settings in the program. 2.2.2. Assumptions 2.2.2. Assumptions Since the study area is part of a major trans-boundary coastal aquifer, some simplifications to define the system were taken for the numerical model; these are as follows:

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Temperature and density remain constant through the whole system, which implies that the saline • interface does not play an important role even though it is a coastal aquifer. The saline intrusion occurring inland, 110 km from the coast towards the Cenote Ring, does not • have a great impact in the fresh water lens behavior. Therefore, the saline interactions were not taken into consideration. This is supported by reports and studies performed by water authorities in the area [37–41]. Currently, there is no model derived from CFP flow solutions that can be coupled with the sea water intrusion process [42]. Since the CFP has at least two different ways to solve the conduit problems, it was decided to use the simplest one: layers of turbulent flow imbedded with laminar flow zones. This decision is based on previous studies which suggest at least three different preferential flow paths located between 11 to 12 m, 15 to 16 m, and 29 to 32 m of depth [43]. The aquifer was simulated using an EPM approach for transport since the study area is located • inside a young sedimentary basin with low development of karstic features such sinkholes and caves; also, the fracture density is quite low in comparison with areas outside the ICR. Steady state was assumed given the low variability in the water table time series. This also means • that the current status of the aquifer is labeled as underexploited. Recharge was assumed to be instantaneous, thus no process occurring within the vadose zone was • included. In order to model what happens in the unsaturated zone, information regarding depth, conductance and some other parameters, which are not available for the region, are necessary to run the unsaturated zone flow (UZF) package in Model Muse. This is a major simplification that neglects the possible simulation of the Epikarst part of the aquifer and its buffer role in pollutant adsorption.

Available public data was gathered and managed to create the necessary input ﬁles for the model (Table1). Recharge was computed using the multi-parameter GIS-based methodology APLIS, (altitude, slope, lithology, inﬁltration and soils respectively) to take into consideration in situ characteristics of karst areas [44].

Table 1. Available public data bases used to build the Yucatan model.

Data Source Type of Database Data Treatment INEGI: Database #1 Edaphology shape files; hydrogeological Selected to compute Recharge rates (public) division; Lithology shape files. using APLIS methodology. Used to build transport model CONAGUA: Monitors network time series and reports; assuming diffuse infiltration in the Database #2 (digital) precipitation time series (from 1995 to 2015). Merida Infiltration basin object. Used to build transport model JAPAY: Databases #3 Waste water volumes and quality. assuming diffuse infiltration in the (digital) Merida infiltration basin object. Digital elevation model, Aster GDEM Base for layers thickness and USGS 30 m resolution. groundwater levels.

2.2.3. Packages The MODFLOW packages used for CFP and EPM simulations are described as follows:

Time-Variant Speciﬁed-Head Package (CHD): for the north boundary of the study area, a constant • head of 0 m (sea level at the coastline) was established. The discharge area towards the ocean has variable thickness along the coast with depths ranging between 5 and 18 m [19,45]. The CHD was also established at the south limit towards the cenote ring. Hydraulic heads in this boundary were computed interpolating point measurements provided by the water authority (CONAGUA) time series from 2002 to 2015 with recordings, on average, every 4 months. Water 2019, 11, x FOR PEER REVIEW 6 of 16

authority (CONAGUA) time series from 2002 to 2015 with recordings, on average, every 4 months.  Recharge (RCH): Since the aquifer recovers in the range of hours, according to local studies and time series of water table levels, the storage does not change on average for a hydrological year. Monthly recharge rates were estimated to run the model with 12 stress periods; each period of Water 20198,4600, 11 , s1431, or one day, represented each month in a steady state condition. For the transport6 of 15 model, a whole stress period of 60 years was run in transient mode using a computed average Rechargerecharge out (RCH): of the Since 12 individual the aquifer stress recovers periods; in the recharge range of was hours, further according discretized to local according studies andthe • timeAPLIS series methodology of water table values levels, (Figure the 3). storage does not change on average for a hydrological year.  MonthlyHead-Observation recharge rates(HOB): were This estimated package to wa runs used the model to define with real 12 stressobserved periods; head eachvalues. period These of 8,4600values s,we orre one used day, represented to calibrate each the month model. in a MODFLOW steady state condition. compares For observed the transport values model, with acalculated whole stress ones period from the of 60program years was solutions run in and transient give useful mode statistics using a computed to calibrate average the model recharge once outit has of been the 12 solved. individual In the stress model, periods; each HOB recharge element was (an further observation discretized well) according is defined the within APLIS a methodologygrid, assigning values a head (Figure value3 ).from available time series of head observations. Then, the model Head-Observationcomputes the residuals (HOB): between This packagemodeled was and used obse torved define heads real, giving observed in return head a values. RMSE Thesevalue • valuesthat helps were toused define to how calibrate accurate the model. the model MODFLOW is. compares observed values with calculated onesFor analysis from the purposes program two solutions places andwere give defined useful as statistics the origin to of calibrate the particles: the model the constant once it has head been at the southsolved. of the In the MMA model, and each Merida HOB city. element The former (an observation was selected well) to isinvestigate defined within the time a grid, it would assigning take for particlesa head value to reach from the available coast to time assess series the of effects head of observations. the pumping Then, well the fields model distributed computes in the Meridaresiduals city periphery between and modeled to evaluate and observedif a preferential heads, flow giving path in (layer return 3) a exerts RMSE influence value that on helpsparticle to movement.define how The accurate later was the modeldefined is. to evaluate the pollution plume behavior in the Merida sub-surface.

Figure 3. Locations of well fields, monitoring wells with the spatial distribution of the recharge package. Figure 3. Locations of well fields, monitoring wells with the spatial distribution of the recharge Axis X and Y display UTM coordinates in meters. package. Axis X and Y display UTM coordinates in meters. For analysis purposes two places were defined as the origin of the particles: the constant head Default values for transport were used and the activated packages for MT3MS were the basic at the south of the MMA and Merida city. The former was selected to investigate the time it would transport (BTN), the advective-transport (ADV), dispersion (DSP), sink and source mixing (SSM) take for particles to reach the coast to assess the effects of the pumping well fields distributed in the and the generalized conjugate gradient solver (GCG) pane. The species particle was NO3 and the Merida city periphery and to evaluate if a preferential flow path (layer 3) exerts influence on particle finite differences solver was used, code 0. At the beginning of the transport simulation, plumes are movement. The later was defined to evaluate the pollution plume behavior in the Merida sub-surface. constrained near to the areas where the pollutant infiltration takes place. Simulations in this work do Default values for transport were used and the activated packages for MT3MS were the basic not consider the probable increment of NO3 due to economic and population growth. A 3D transport (BTN), the advective-transport (ADV), dispersion (DSP), sink and source mixing (SSM) representation of the model is displayed in Figure 4. and the generalized conjugate gradient solver (GCG) pane. The species particle was NO3 and the finite differences solver was used, code 0. At the beginning of the transport simulation, plumes are constrained near to the areas where the pollutant infiltration takes place. Simulations in this work do not consider the probable increment of NO3 due to economic and population growth. A 3D representation of the model is displayed in Figure4. Water 2019, 11, 1431 7 of 15 Water 2019, 11, x FOR PEER REVIEW 7 of 16

Figure 4. A 3D presentation of the study site, including all active objects and packages used to run the Figure 4. A 3D presentation of the study site, including all active objects and packages used to run groundwater numerical solution and the transport model. the groundwater numerical solution and the transport model. 2.2.4. Calibration 2.2.4. Calibration To calibrate the model, two parameters were adjusted along the process: hydraulic conductivity for theTo X calibrate and Z axisthe model, (first K twox and parameters then Kz, ifwere the adjusted vertical infiltrationalong the process: is higher) hydraulic and recharge conductivity rates. Thefor the time X seriesand Z foraxis monitoring (first Kx and wells then from Kz, if 2002–2015, the vertical provided infiltration digitally is higher) by CONAGUA,and recharge servedrates. The to analyzetime series the values for monitoring adjusted during wells thefrom calibration 2002–2015 process., provided digitally by CONAGUA, served to analyzeAfter the several values trials adjusted it was during evident the that calibration the modifications process. in the Kz were not significant. Therefore, the onlyAfter parameter several trials left forit was trial evident was K xthat. It the was modifications decided not toin gothe above Kz were the not suggested significant. values Therefore of Kx , foundthe only in theparameter literature le sinceft for they trial are was already Kx. It quitewas decided high even not for to karst go above standards the accordingsuggestedto values Marín of [29 K].x Calibrationfound in the was literature ended atsince the they best RMSare already value (0.2221)quite high without even for going karst beyond standards the suggested according K tox values Marín of[29]. 1.115 Calibration m/s. There was are ended no uniform at the criteriabest RMS to definevalue (0.2221) what constitutes without going a good be RMSE,yond the so wesuggested defined K ax thresholdvalues of of1.115 0.2500 m/s. to There stop theare calibration.no uniform Tablecriteria2 displays to define best what fit forconstitutes CFP parameters a good RMSE, achieved so bywe manualdefined calibration.a threshold Values of 0.2500 for Ktoz werestop the all fixedcalibrati as 1.115on. Table m/s. 2 displays best fit for CFP parameters achieved by manual calibration. Values for Kz were all fixed as 1.115 m/s. Recharge playsTable a fundamental 2. Parameters obtainedrole in the after water calibration budget to of run the the study transport area model. with at least 30% of the contribution to the final discharge. Although the main input is the groundwater flow coming from Parameter Value Comments the south, recharge is expected to be a driven hydraulic process when it comes to pollutant behavior. Coastal area = 2.5 times the Most of the coastal area has high hydraulic conductivities Recharge values, officially reported by the water authority, are part of a study of the whole aquifer. precipitation raster input file since sandy textures cover part of the area. Despite a The average rechargeMetropolitan for the area MMA (not isincluding approximatelylayer, acting 0.18 as Mm a semi-unconfined3/km2 according aquifer to andthe existing study mentionedRecharge above rate ; the rechargeMerida City) rate= obtained0.2 times the after calibrationnear thecoastline, is approximately it was not considered 0.23 Mm3 in/km this2, work.which indicates that the modelprecipitation tends toraster overestimate input file recharge.This adjustment However, was modeled performed discharge since that recharge values rates are Rest of the area = 0.0025 times the were both underestimated and overestimated with the close with those reportedprecipitation by CONAGUA raster input [21]. file Appendix TableGIS A1 methodology displays the APLIS general settings utilized for the model before calibration. Layer 1 = 1 m/s A better RMSE was showed with Kx for layer 1 and 2 Hydraulic Layer 2 = 0.5 m/s with inversed values. Nevertheless, we consider that this Conductivity (Kx)Table 2. ParametersLayer 3 = 1.115obtained m/s after calibrationconfiguration to run the did transport not depict model. the initial assumptions Layer 4 = 1 m/s about layer 1, behaving as Epikarst. Parameter Value Comments Most of the coastal area has high hydraulic Coastal area = 2.5 times the Recharge plays a fundamental role in the water budgetconductivities of the study since area sandy with textures at least cover 30% par oft theof precipitation raster input file contribution to the final discharge. Although the main inputthe is the area. groundwater Despite a layer, flow acting coming as a from Metropolitan area (not including the south, recharge is expected to be a driven hydraulic processsemi-unconfined when it comesaquifer toand pollutant existing near behavior. the Recharge rate Merida City) = 0.2 times the coastline, it was not considered in this work. Recharge values, officiallyprecipitation reported raster by the input water file authority, are part of a study of the whole aquifer. This adjustment3 2 was performed since that recharge The average recharge forRest the of the MMA area is = approximately0.0025 times the 0.18 Mm /km according to the study mentioned rates were both underestimated3 2 and overestimated above; the recharge rateprecipitation obtained after raster calibration input file is approximately 0.23 Mm /km , which indicates with the GIS methodology APLIS that the model tends to overestimate recharge. However, modeled discharge values are close with Layer 1 = 1 m/s A better RMSE was showed with Kx for layer 1 and those reported by CONAGUA [21]. AppendixA Table A1 displays the general settings utilized for the Hydraulic Layer 2 = 0.5 m/s 2 with inversed values. Nevertheless, we consider model before calibration. Conductivity (Kx) Layer 3 = 1.115 m/s that this configuration did not depict the initial Layer 4 = 1 m/s assumptions about layer 1, behaving as Epikarst.

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3. Results3. Results 3.1. Particle Tracking 3.1. Particle Tracking The firstThe first particle particle tracking tracking simulation, simulation, with with a particlea particle release release originating originating atat thethe southsouth boundary, revealedreveal negligibleed negligible effects effects caused caused by by the the well well fields fields surrounding surrounding Merida Merida with with thethe currentcurrent pumpingpumping rates.rates. The exceptionThe exception is the is wellthe well field field JAPAY JAPAY IV located IV located in the in the west, west suggesting, suggesting the the influence influence of of a cone a cone of depressionof depression that delays that delay particless particles in this in areathis area and and taking taking more more time time to to move move northward. northward. TheThe second simulation,simulation, which which changed chang theed the origin origin of theof the particles particles to to Merida Merida city, city, indicated indicated a a periodperiod ofof 4 years for for any particleany particle to reach to reach the coastalthe coastal area area in the in north,the north, particularly, particularly in Progreso, in Progreso city. city. The The main main outcome outcome for the particlefor the particle tracking tracking was the was pathway the pathway itself. Givenitself. Given the hydraulic the hydraulic gradient gradient and the and preferential the preferential flow paths,flow particles paths,follow particles a distinctive follow a distinctive path from path the northfrom ofthe Merida north of city Merida towards city Progreso. towards AsProgreso. displayed As in Figuredisplaye5, particlesd in Figure reach 5, particles two observation reach two wells observation in approximately wells in approximately one year (FIUADY one year and (FIUADY Komchen), and locatedKomchen), approximately located 15approximately km away from 15 km the away Merida from city the center. Merida The city observation center. The well observation PREDECO well is reachedPREDECO after 2 is years, reached and after thus, 2 theyears particles, and th haveus, the already particles left have the Meridaalready cityleft the area. Merida Particles city reacharea. the CONTENEDORESParticles reach the CONTENEDORES observation well, observation located 26 km well, away located from 26 the km particleaway from release the particle point, andrelease the southernpoint, limits and the of Progresosouthern limits city in of the Progreso third year.city in Outcomes the third year. also showedOutcomes that also there show mayed that be somethere may be some concerns regarding the well field, JAPAY III. concerns regarding the well field, JAPAY III.

Figure 5. Particle tracking with Merida city as the particle release area. Two particles per axis were released for each grid corresponding to Merida City. A clear movement northward indicates the theoretical vulnerability of small communities between Merida and Progreso.

Water 2019, 11, x FOR PEER REVIEW 9 of 16

Water 2019Figure, 11, 5. 1431 Particle tracking with Merida city as the particle release area. Two particles per axis were9 of 15 Waterreleased 2019, 11 , for x FOR each PEER grid REVIEW corresponding to Merida City. A clear movement northward indicates 9 the of 16 theoretical vulnerability of small communities between Merida and Progreso. 3.2. TransportFigure Model5. Particle tracking with Merida city as the particle release area. Two particles per axis were released for each grid corresponding to Merida City. A clear movement northward indicates the 3.2. Transport Model Bytheoretical the end of vulnerability the simulation, of small the communities pollution plumebetween coming Merida and from Progreso. Merida city has reached Progreso City andBy the one end of the of pumping the simulation, well fields the that pollution supply drinkingplume coming water tofrom Merida Merida city (JAPAYcity has III). reached Even JAPAYProgreso3.2. Transport II isCity slightly and Model one aff ected of the but pumping given that well cells fields with that NO supply3 concentrations drinking water lower to thanMerida 0.5 city mg /(JAPAYL were notIII). included EvenBy JAPAY the in end the II coloredof is theslightly simulation, grid, affected the plume the but pollution isgiven not visible.that plume cells Concentrations comingwith NO from3 concentrations Mevenerida reach city JAPAY lower has reached IVthan even 0.5 thoughmg/LProgreso were NO 3 Citynotconcentrations andincluded one of inthe arethe pumpingminimal. colored well grid, According fields the that plume to supply the is model, notdrinking visible. the water pollution Concentrations to Merida plume city alsoeven (JAPAY travels reach downwardJAPAYIII). Even IV reaching evenJAPAY though II theis slightly bottomNO3 concentrations affected of the simulatedbut given are that aquifer;minim cellsal this.with According may NO3 a concentrationsffect to thetheareas model, l whereower the than drinkingpollution 0.5 waterplumemg/L is also extracted. were travels not included However,downward in concentration thereaching colored the grid, bottom curves the plume doof the not simulated is show not visible. a significant aquifer; Concentrations this increase may affect of even NO the reach3 in areas the wellwhereJAPAY fields. drinking IV Higher even water concentrations though is extracted. NO3 concentrations are However, displayed concentration are in the minim upperal. curves According layers (1do to not to 3), theshow although model, a significant most the pollution dispersion inc seemsplume to bealso located travels at downward layer 3 (Figure reaching6). the bottom of the simulated aquifer; this may affect the areas where drinking water is extracted. However, concentration curves do not show a significant increase of NO3 in the well fields. Higher concentrations are displayed in the upper layers (1 to 3), although most dispersion seems to be located at layer 3 (Figure 6).

FigureFigure 6.6. PollutionPollution plumeplume simulationsimulation afterafter 6060 years.years. TheThe pollutionpollution plumeplume followsfollows thethe groundwatergroundwater ﬂow,flow,Figure moving moving 6. Pollution towards towards plume the the coast, coast, simulation indicating indicating after the the60 vulnerability years.vulnerability The pollution of of towns towns plume located located follows in in the the the middle. middle. groundwater flow, moving towards the coast, indicating the vulnerability of towns located in the middle. HighHigh NONO33 concentrationsconcentrations are inin layerlayer 11 wherewhere thethe pollutionpollution sourcessources areare locatedlocated (3(3 mm belowbelow thethe toptop ofof theHighthe model,model, NO3 concentrations simulatingsimulating septicseptic are in tanks);tanks); layer 1 the thewhere waterwater the tabletablepollution doesdoes sources notnot alwaysalways are located reachreach (3 thatthat m below levellevel ininthe thethe model.model.top of Therefore,Therefore, the model, MT3DMSMT3DMS simulating doesdoes septic notnot tanks); showshow anytheany water transporttransport table resultsresults does not andand always thethe analysisanalysis reach that focusfocus level onon layersilayersn the 22 andandmodel. 3.3. FigureFigure Therefore,7 7 also also shows MT3DMSshows that that does pollution, pollution, not show even even any in in transport smaller smaller concentrations resultsconcentrations and the analysis (a (a little little above focusabove on 0.001 0.001 layers mg mg/L) 2/ L) reachesreachesand 3. the theFigure aquifer aquifer 7 also and and shows the the well thatwell ﬁeld pollution, field JAPAY JAPAY even III. III. Nevertheless,in smallerNevertheless, concentration this this concentration concentrations (a little isabove dependent is dependent0.001 mg/L) on the on initialthereaches initial concentration the concentration aquifer established and establishedthe well in MT3DMSfield in JAPAY MT3DMS to runIII. theNevertheless, to model run the with modelthis no concentration consideration with no consideration is of dependent the population of on the growthpopulationthe initial rate orgrowth concentration further rate characterization or establishedfurther characterization in of MT3DMSspatial concentrations. of to spatial run the concentrations. model with no consideration of the population growth rate or further characterization of spatial concentrations.

Figure 7. FigureFigure 7. The 7.The The east-weste aseast-westt-west viewview view ofof of thethe the model modelmodel showsshows thatthat thethe plumeplume has hashas reached reachedreached at atat least leastleast one oneone of of ofthe thethe well wellwell ﬁelds that supply drinking water to the city, although with low NO3 concentrations. However, well fieldsfields that that supply supply drinking drinking water water toto thethe city,city, although withwith low low NO NO3 3concentrations. concentrations. However, However, well well ﬁelds supplying Merida or towns located at the west part of the city can be characterized as more vulnerable to contamination.

Water 2019, 11, x FOR PEER REVIEW 10 of 16 Water 2019, 11, x FOR PEER REVIEW 10 of 16 Water 2019, 11, 1431 10 of 15 fields supplying Merida or towns located at the west part of the city can be characterized as more fields supplying Merida or towns located at the west part of the city can be characterized as more vulnerablevulnerable to tocontamination. contamination. Pollutants move horizontally through the system, mainly through layers 2 and 3, northward. However,PollutantsPollutants it seems move move that horizontally horizontally preferential through flowthrough paths the the dosystem system, not exert, mainlymainly significant throughthrough eff ectslayers on 2 the and movement 3,3, northward.northward. of the However,pollutionHowever, plume.it itseems seems Higher that that preferential concentrationspreferential flow flow were paths paths expected do do not not along exertexert thesignificantsignificant horizontal effects layers, on mainlythe movement in the third ofof thelayerth pollutio givenn the plume. high Higher hydraulic concentrations conductivity. were Nevertheless, expected along the velocity the horizontal at which layers, water mainly travels in from the thirdsouth layer to north, given and the the high dispersion hydraulic process conductivity. through Nevertheless, layer 2 influence the thevelocity pollution at which behavior water since travels NO3 fromconcentration south to isnorth higher, and in the horizontaldispersion thanprocess in the through vertical layer direction 2 influence (Figure the8). pollution behavior since NO3 concentration is higher in the horizontal than in the vertical direction (Figure 8).

FigureFigureFigure 8. 8. 8.BehaviorBehavior Behavior of of of the thethe pollution pollutionpollution plume plumeplume under under M Meridaerida City. City. The The The pollutionpollution pollution travels travels towards towards thethe the coastcoast coast nnorthorthnorth of of ofthe the the city, city, city, increasing increasing increasing its its its concentration concentration concentration in inin layer layerlayer 2 22 and andand 3. 3.3.

ConcentrationConcentration curves curves (Figure(Figure9 )9) show show a a lapse lapse of of around around 300300 daysdays forfor NONO33 releasedreleased in in Merida Merida to to Concentration curves (Figure 9) show a lapse of around 300 days for NO3 released in Merida to reachreach the the monitoring monitoring wells wells at detectable at detectable concentrations. concentrations. Given Given the general the general groundwater groundwater path, path, it seems it reach the monitoring wells at detectable concentrations. Given the general groundwater path, it thatseems these that wells these may wells never may reﬂect never highreflect NO high3 concentrations, NO3 concentrations, unless unless the concentration the concentration released released in the seems that these wells may never reflect high NO3 concentrations, unless the concentration released cityin the increases city increases signiﬁcantly. significantly. in the city increases significantly.

Figure 9. NO3 concentration curves for layers 1 and 2 for selected observation wells along the FigureFigureMerida-Progreso 9. 9. NONO3 3concentrationconcentration transect. The curves curvesminimum for for layersNO layers3 concentration, 1 1 and and 2 2 for for according selected selected observationto observation the Mexican wells wells standards along along forthe the MeridaMerida-Progresowater- Progresosupply, is transect. transect.10 mg/L The(NOM-127- The minimum minimumSSA1 NO NO-1994).3 3concentration,concentration, according according to to the the Mexican Mexican standards standards for for waterwater supply, supply, is is 10 10 mg/L mg/L (NOM (NOM-127-SSA1-1994).-127-SSA1-1994). Recharge greatly influences NO3 concentration patterns along the layers according to the model. Recharge greatly influences NO concentration patterns along the layers according to the model. AnalyzingRecharge seasonal greatly influences patterns, NO NO3 3 concentration3 concentration increases patterns withalong recharge the layers from according July to to November, the model. Analyzing seasonal patterns, NO concentration increases with recharge from July to November, and Analyzingand also seasonal shows an patterns upward, NO tendency33 concentration from January increases to April, with while recharge from from November July to Novemberto April it , andalsodecreases. also shows show an Thiss upward an suggests upward tendency a flush tendency from effect January from that isJanuary to more April, visible to while April, within from while theNovember from wet season.November to April Moreover, it to decreases. April the it decreases.Thisinfluence suggests This of the a suggests flush recharge eff ect a process flush that iseffect is more restricted that visible is to more withinthe visibletop the of layer wet withinseason. 2, the the interface wet Moreover, season. between the Moreover, influence the water the of influenthetable recharge ceand of the the process unsaturated recharge is restricted process zone (Figure is to restricted the 10). top This of to layer thephenomenon 2,top the of interface layer backs 2, the betweenup theinterface hypothesis the between water that table therecharge and water the tableunsaturated and the zoneunsaturated (Figure 10zone). This (Figure phenomenon 10). This phenomenon backs up the hypothesisbacks up the that hypothesis recharge dynamicsthat recharge play

Water 2019, 11, x 1431 FOR PEER REVIEW 1111 of of 16 15 dynamics play a significant role in the pollutants’ behavior and reasserts the role of Epikarst acting a signiﬁcant role in the pollutants’ behavior and reasserts the role of Epikarst acting as a buﬀer zone as a buffer zone that delays the movement of pollutants. that delays the movement of pollutants.

Figure 10. Relationship between recharge and NO3 concentration in Progreso City according the model. Figure 10. Relationship between recharge and NO3 concentration in Progreso City according the 4. Discussionmodel. The behavior of the plume under Merida city displays several interesting characteristics. Pollution 4. Discussion concentrates mainly between layer 2 and 3, while the north of the city has a higher NO3 concentration thanThe the south. behavior Also, of pollution the plume follows under the Merida hydraulic city gradient displays and s travelseveral towardsinteresting the characteristics. coast. This fact Pollutioncould be helpfulconcentrates to define mainly the between vulnerable layer zones 2 and in further3, while studies. the north In of order the tocity consider has a higher pollutants’ NO3 concentrationresidence time than and the concentration south. Also, as pollution part of an follows integrated the hydraulic karst vulnerability gradient and approach, travels vulnerabilitytowards the coast.becomes This a fact relative could parameter be helpful since to define it will the be vulnerab dependentle zones on two in sites:further a supplystudies. target In order (a well to consider field or pollutantseven a city)’ residence and the point time whereand concentration pollution originates. as part of The an spatial integrated distribution karst vulnerability of the pollution approach, plume vulnerabilitysuggests that becomes most contaminants a relative parameter will be carried since it out will by b thee dependent general groundwater on two sites: paths, a supply which target seem (a wellto diverge field or from even the a drinkingcity) and waterthe point supply where fields. pollution It is possible originates. that The JAPAY spatial well distribution fields, I, II andof the VI, pollutionwhich supply plume water suggests to Merida that most city, arecontaminants not affected will with be the carried current out extraction by the general rates. However,groundwater our pathsresults, which indicate seem that to JAPAY diverge III, from located the in drinking the eastern water part supply of Merida, fields. is It more is possible likely to that extract JAPAY polluted well fields,water. I, The II and plume VI, generated which supply underneath water to Merida Merida aff ectscity, this are wellnot field,affected which with can the be current classified extraction as more rates.vulnerable However compared, our results with the indicate others. that Although JAPAY pollution III, located moves in towardsthe eastern the coastpart of at aMerida, similar is velocity, more likelythere is to a extractdistinctive, polluted high concentration water. The plume path that generated moves directly underneath towards Merida Progreso affects city, this and well this seems field, whichto be one can of be the classified major pollution as more paths. vulnerable There compared are many smallwith communitiesthe others. Although scattered pollution between Meridamoves towardsand Progreso; the coast these at communities a similar velocity, use shallow there and is a artisanal distinctive wells, high for drinking concentration water path supply, that meaning moves directlythey are towards susceptible Progreso to pollutant city, and water this in seems the near to be future, one of assuming the major that pollution NO3 concentrations paths. There are have many not smallincreased communities already. scattered between Merida and Progreso; these communities use shallow and artisanalThe wells definition for drinking of vulnerability water supply, (high, meaning moderate they or low)are susceptible with regard to topollutant residence water time in andthe nearconcentration future, assuming will always that dependNO3 concentrations on regional have characteristics. not increase Ford already. instance, in Mexico, the drinking waterThe standards definition specify of vulnerability a maximum NO (high,3 concentration moderate or of low) 10 mg with/L for regard drinking to water;residence this time of course, and concentrationvaries according will to always the country. depend According on regional to the characteristics. model presented For here, instance, there arein M severalexico, parametersthe drinking to waterconsider standards in future specify approaches a maximum to vulnerability, NO3 concentration these are shownof 10 mg/L in Table for drinking3. This could water; help this to of establish course, variesa new, according integrated to methodology the country. toAccording prioritize to areas the model for further presented investigation here, there and are to defineseveral how parameters specific tokarst consider features in actually future approaches impact the localto vulnerability conditions., these are shown in Table 3. This could help to establishThere a new are some, integrated results methodology that suggest to that prioritize pollution areas has for spread further and investigat more samplingion and pointsto define are hneededow specific to assess karst the features current actually situation. impact This the work local does conditions. not aim to design a new rating system for a vulnerability index, but to give some general ideas as to how this might be done and which factors may be useful in the region. We suggest that the definition of high vulnerability should be based on the areas within the pollution plume paths and the wells with higher NO3 concentrations. As expected, recharge shows an important influence on NO3 concentrations. Recharge variability must also be used as a differentiation vulnerability parameter, as stated in previous studies on the

Water 2019, 11, 1431 12 of 15 region [18]. Since pollutant transport is inﬂuenced by higher recharge, months with higher rates may need diﬀerent and special measures. This is also true when dealing with extraordinary natural events, such as hurricanes, which imply high recharge rates in shorter time lapses.

Table 3. Estimated time and NO3 concentrations to be considered for an integrated groundwater vulnerability approach.

Vulnerability Target Estimated Time Maximum NO3 Concentrations On 60 years-simulation period, the maximum concentration is 0.01 mg/L from an initial Well ﬁelds: JAPAY III 60 years concentration of 28 mg/L coming from Merida city. On 60 years-simulation, the maximum Two years for low recorded concentration and concentration is 11.8 mg/L from the original Progreso City 4 years for a concentration higher than 5 mg/L pollution coming from Merida city (28 mg/L), without considering local inputs a which means around 40% of the initial pollution concentration reached the City. Most pollution travels towards the coast, Maximum concentration remains the same as away from the southern municipal wells Merida City the input if no changes are included, like where drinking water is pump out for human increased rates due to population growth. consumption, mainly JAPAY II and III FIUADY around 150 days Observation wells Komchen around 365 days Layer dependent cells (HOB) along PREDECO around 730 days Contenedores around 1095 days a This is relevant because local NO3 inputs in Progreso city are much higher than the average used for the Merida basin, being around 78 mg/L against 28 mg/L in Merida city. No discussion in this paper of the origin of pollution in the coastal city was made.

5. Conclusions To the best of our knowledge, no other groundwater model, including the CFP, has been applied to this region; model files were created from scratch and the model can be improved according to newly available data. Given the specifics of the CFP, the transport model does not fully depict karstic features, which can result in an inaccurate picture of the pollution plume. To overcome these issues, a model would have to be further developed and coupled with non-linear flow packages. The disadvantages of manual calibration are that it is a very time-consuming process, and also, the possible combinations that have already been tried may not be comprehensive enough to find all the possible optimal solutions. The main limitation in this work is the incompatibility of CFP (preferential flow paths) with MT3DMS. Results from the EPM approach do not completely reflect the karst features, but by assigning high conductivity values we aimed to compensate for the lack of a transport model in CFP. However, because the ICR a sedimentary basin, it might generally resemble an EPM model. Among other limitations, conceptualization is a dynamic task for any modeling path; the conceptual model oversimplifies the dynamics in the unsaturated area by assuming immediate infiltration, and not accounting for the delaying processes (Epikarst acting as perched aquifer) that occur within the unsaturated area. Further steps to improve the model are suggested as follows:

The first step would be to construct an evapotranspiration file (ETV) using estimation models • since only evaporation data is available for the region, in order to implement the UZF package to evaluate unsaturated phenomena. To set up the newly developed Non-Linear Flow Package to simulate transport in karst. • To use a GHB at the coast to simulate tide dependency changes in coastal heads. • To evaluate how the saline intrusion interacts with the heads and pollution behavior. • In general, this work demonstrates that groundwater in a given region can also be characterized by pollutant concentration and behavior in terms of vulnerability. The findings and considerations Water 2019, 11, 1431 13 of 15 discussed here could serve as a basis for further development of an integrated groundwater vulnerability approach based on real situations, including the potential to analyzing future scenarios.

Author Contributions: Data gathering and literature research, C.M.-S. and M.M.-G; Conceptualization of the model, C.M.-S., M.M.-G. and R.L.; Project Leader, R.L.; modeling, C.M.-S.; writing—original draft preparation, C.M.-S.; writing—review and editing, C.M.-S., M.M.-G. and R.L.; supervision, M.M.-G. and R.L. Funding: This research was funded by The Erasmus Mundus Scholarship for Joint Master Programs granted to Carolina Martinez Salvador from 2016–2018 as part of the funding of the Master program “Groundwater and Global Changes”, held at IST Lisbon, IHE-UNESCO Delft and TU Dresden; the Mexican National Council for Science and Technology (CONACYT) CVU [466945]; the German Federal Ministry of Education and Research (BMBF) within Junior Research Group INOWAS under reference [01LN1311A]. Acknowledgments: We acknowledge support by the Open Access Publishing Funds of the SLUB/TU Dresden. We express our gratitude to Thomas Reimann (TU Dresden) for his valuable comments and suggestions to improve this work regarding karst modeling. Conﬂicts of Interest: The authors declare no conﬂict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.

Appendix A

Table A1. Initial parameters used to run de model before calibration.

Parameter or Package Values Layer 1: DEM 10 m − Layer 2: (DEM 35) 0.3 − × Layer 3: DEM 35 m − This layer is then discretized to depict the beginning of the Layers: saturated area and the preferential flow path that tries to Layer 1 to 3 are convertible while 4 is confined. account for the most relevant karst feature. Layer 4: DEM 80 m − The 80 m depth for the aquifer would only account for the freshwater lens. This work only focuses on the upper part of the aquifer, regardless the saline lens in the model. Hydraulic conductivity per layer: Given that the CFP implies one layer of preferential flow, it was defined layer 3 as the Layer 1: 0.1 m/s most conductive layer. Conductivity values are Layer 2: 0.1 m/s suggested by González in a previous numerical Layer 3: 1.115 m/s model where the best calibration was obtained Layer 4: 0.1 m/s for K = 1.115 m/s. This value t was assigned to the preferential layer. Constant head at sea level: 0 m. The discharge area was defined based on some studies that suggest that this area is quite variable and can go between 5 to 18 m thick. So, in the model, the formula was defined as: Boundary conditions: Discharge area = (Model Top 18)/2, trying to account for the Constant head at sea level in 0 m. − small differences in the discharge area, and made them In further steps, and to adjust the conceptual depended on the elevation of the terrain in the model top layer. model after feedback, some trials were run with This is an arbitrary boundary that does not match with any GHB package (a general boundary package, specific karstic, topographic or political boundary, at least in which also depends on conductance). the MMA model. But, when running just particles for ICR, the Constant head at the south of the model. boundary condition is the Cenote Ring itself. This boundary condition acts as natural drainage that redirects water from inland to the ocean. It concentrates part of the discharge of the whole aquifer in the outlets of the Cenote ring. Water 2019, 11, 1431 14 of 15

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