and flow modeling of tard percolation in the Cariri valley Northeast Brazil art hfrischkorn

O R I G I N A L P A P E R

Hydrogeochemical and Flow Modeling of Aquitard

Percolation in the Cariri Valley-Northeast Brazil

Carlos Jose´ Freire MachadoÆMaria Marlu´cia Freitas SantiagoÆ

Luiz Alberto Ribeiro Mendonc¸aÆHorst FrischkornÆJosue´ Mendes Filho

Received: 17 March 2006 / Accepted: 5 June 2007 / Published online: 5 July 2007 _{Springer Science+Business Media B.V. 2007}

Abstract Flow modeling and hydrogeochemical inversion calculations were performed on the aquifer systems of the Crato-Juazeiro Graben in the Araripe Sedimentary Basin of the Cariri Valley, Northeast Brazil, in order to assess aquifer interconnections through an aquitard of the Araripe Plateau. Steady state hydraulic head numeric calculations with the finite difference method used Modflow software with hydrologically based boundary conditions and a piezometric surface as initial condition. Hydrogeochemical inversion with PHREEQC was performed for two water samples representing typical initial and final waters along the flow path. Flow simulation shows that approximately 20% of all recharge water from the superior aquifer system passes through the Santana aquitard reaching the middle aquifer system. Quantification of mineral dissolution/precipitation processes, ion exchange and microbiological redox reactions taking place in the aquifer systems also

C. J. F. Machado

Universidade Federal do Para´/Campus de Santare´m, Fı´sica, PA CEP 68040-070, Brazil

e-mail: cjfm@ufpa.br

M. M. F. SantiagoJ. Mendes Filho

Depto. de Fı´sica, Universidade Federal do Ceara´, Fortaleza, Ceara CEP 60455-760, Brazil

M. M. F. Santiago

e-mail: marlucia@fisica.ufc.br L. A. R. Mendonc¸a

Depto. Hidrologia, CENTEC, Juazeiro do Norte, Fortaleza, Ceara´, Brazil

e-mail: martaluiz@yahoo.com.br H. Frischkorn (&)

Depto. Engenharia Hidra´ulica e Ambiental, Universidade Federal do Ceara´, Fortaleza, Ceara´, Brazil

e-mail: cariri@ufc.br J. Mendes Filho

indicates hydraulic interconnection of the superior and middle aquifer systems through the Santana aquitard.

Keywords HydrogeochemistryPHREEQCModflowAraripe Sedimentary Basin

Cariri Valley

1 Introduction

During the last two decades flow modeling has become a routinely used tool for solving hydrogeologic problems. Over the last decade hydrochemical modeling, mainly using PHREEQC, has also proved a powerful instrument for chemical simulation (Parkhurst

1995; van der Kemp et al.2000; Wurl et al.2003; Dai and Samper2004; Lecomte et al.

2005, and others). In this study we have used both flow and hydrogeochemical modeling to determine whether or not aquifer recharge on the top of the Araripe Plateau contributes to groundwater storage in the Cariri Valley. This problem is rather controversial, as the superior aquifer system (Plateau) and the middle aquifer system are separated by the limestone Santana Formation, considered by many hydrogeologists (DNPM 1996) an aquiclude because its hydraulic conductivity is estimated to be on the order of 1010m/s. However, based on isotope and hydrochemical characteristics of groundwater in the Valley, Santiago et al. (1997) proposed a model in which rainfall waters on the Plateau percolate the sandstone formations Exu and Arajara (constituting the Superior Aquifer System (SAS)) and pass through fractures in the Santana Formation, reaching the Rio da Batateira Formation of the Middle Aquifer System (MAS) in the Cariri Valley. Aquifer functioning is an important matter in the Valley as it is a rapidly growing urban region exclusively supplied by groundwater. In addition, large-scale agricultural projects have been proposed for the Plateau. In the present study we use Modflow (McDonald and Harbaugh1984) for regional flow modeling and PHREEQC (Parkhurst and Appelo1999) for hydrogeochemical inversion for identifying the contribution of groundwater flow through the Santana aquitard (of unknown hydraulic conductivity) to Cariri Valley aquifers.

2 Materials and Methods

2.1 Study Area

In the State of Ceara´, where in 75% of the area crystalline basement rock outcrops, the Cariri aquifers represent the biggest and the most important groundwater resources of the State. They extend over 11,500 km2 where wells yielding more than 100 m3/h of low-salinity water (below 500 mg/l) are common. These resources are the driving force for agricultural, industrial and socio-economic development of the region that comprises 26 townships, being responsible for 10% of the internal gross product of the State.

annual rainfall in the Cariri is unequal: more than 1,000 mm, in the central part, only

&500 mm in the east.

The Crato-Juazeiro Graben is located in the Araripe Sedimentary Basin, Northeast Brazil, containing the townships of Crato, Juazeiro do Norte and Barbalha (Fig.1). The Cariri Valley and the Araripe Plateau, at about 400 m above the Valley, define its topography. Sedimentary Basin aquifers are important groundwater reservoirs in the semi-arid Northeast of Brazil. The Basin is delimited in the north and south by outcropping crystalline basement rock. The narrow strips of the Arajara and Santana Formations rep-resent the cliff that rims the Plateau.

2.2 Litho-stratigraphic Profile

The Exu Formation lithology constitutes a monotonous sequence of unconsolidated clayey sandstone, and intercalation of lenses of course conglomerated, unconsolidated sandstone, with lithofacies typical of fluvial deposits (Ponte and Appi1990). Soils are 99% hyaline quartz with adhering ferruginous matter and 1% clayey ferruginous concretions (Jacomine et al.1973).

The Arajara Formation (Fig. 1) consists of a sequence of siltites, argillite and fine-grained clayey sandstones with typical lacustrine lithofacies (Ponte and Appi1990). The Santana Formation is composed, from top to bottom, of Romualdo, Ipubı´ and Crato

Members (Beurlen1971). The Romualdo Member consists of shale intercalations, marls, limestone and unconsolidated sandstone lenses with up to 60 m thickness (Oliveira1988). The Ipubı´ Member is characterized by evaporitic lenses of mainly gypsum and anhydrite with 30 m mean thickness (Silva1983,1988). The Crato Member is composed, from top to bottom, of micaceous clayey limestone and micaceous shale and is the central lithofacies of a depositional lacustrine system (Silva1983). There is a large amount of total organic carbon (up to*25% (Assine1992)) in this laminated 50 km section.

The Rio da Batateira aquifer lithology is constituted of medium and fine-grained clayey sandstones, clayey siltite and bituminous shale with fossils, with an approximate thickness of 200 m (Ponte and Appi 1990). Mineralogy shows vitreous colorless quartz with fer-ruginous adhering matter, manganous concretions, clayey ferfer-ruginous concretions and weathered K-feldspar (Jacomine et al.1973).

2.3 Flow Modeling

Modflow software was used for steady-state regional groundwater flow modeling. Speci-fied head boundary conditions were imposed by the rivers Salamanca and Batateira, the level of springs discharging from the Arajara/Santana Formations interface and Jardim Fault (that acts as a water divide on the Plateau) connecting points P5 (Exu well) and P6 (Fig.1) for which hydraulic heads were linearly interpolated. Due to the scarcity of data on the Plateau, the head for the Exu well, exploiting the Jardim fault, was attributed to the entire fault in the Rio da Batateira aquifer. This procedure seems reasonable as the hydraulic gradient is expected to be small in the longitudinal direction of the Plateau. A well database (COGERH2003; DNPM 1996) of topographic positions and static levels was used to interpolate hydraulic heads for any point of the 100-column/100-row grid covering an area of 1,000 km2. This hydraulic head surface was used in the calibration of the model, when hydraulic conductivity of the Santana Formation and local recharge to the Batateira Valley aquifer were adjusted. As the crystalline basement is impervious, corre-sponding cells were considered inactive.

Recharge on top of the Plateau depends on the characteristics of the area simulated. Mendonc¸a (2001), using the Green and Ampt (1911) model, calculated 4% of annual precipitation for forest areas, but only one-fifth of this value for deforested ones. For the mean annual rainfall of 1,000 mm/year this results in 40 and 8 mm/year, respectively.

Hydraulic conductivities were k_E = 13.5 · 106 m/s for the Exu Formation,

kA= 1.7·106m/s for the Arajara Formation andkRBP= 6.9·106m/s for the Rio da

Batateira Formation underneath the Plateau (calculated by Mendonc¸a 2001), and

k_RBV= 50·₁₀6 _{m/s for the Rio da Batateira Formation in the Valley (obtained from}

DNPM1996).

2.4 Hydrogeochemical Inversion

the only well (P5 in Fig. 1) penetrating the entire Plateau and exploiting the Rio da Batateira Formation. This water is highly mineralized, with EC = 904mS/cm.

3 Results and Discussion

3.1 Flow Modeling

Steady-state numerical calculation was performed with boundary condition and initial hydraulic head distribution as described above. In total, 18 wells (Fig.1, Table1), 17 in the Valley and one (Exu well, P5) on the Plateau, were used for calibration, through which local Valley recharge and hydraulic conductivity, k_S, of the Santana Formation were adjusted.

A Valley recharge of 130 mm/year was obtained. While this value seems high, one must keep in mind that recharge through water discharging from the springs at the SAS/Santana contact is included.

More important to the question of aquifer functioning is the hydraulic conductivity of the Santana Formation. Figure 2A represents error parameters that judge the quality of adjustment to the hydraulic head distribution: standard deviation (r), the mean absolute

deviation ðhj jiÞe for all wells, and the deviation for the Exu well only (e_exu). All three

parameters are in good agreement:k_S= 9·₁₀11_{m/s is the best value (and is close to the}

estimated 1010m/s). Figure2B presents Modflow simulated heads versus observed heads for the 18 calibration wells.

Table 1 Coordinates, hydraulic head (observed and calculated), depth, flow and identification labels (ID)

for calibration wells

Coordinates (UTM) Hydraulic head (m) Depth (m) Q(m3/h) ID

X Y Observed Calculated

462500 9193678 404.9 413.9 110 11.3 P56

461980 9190945 413.3 424.1 102 3 P90

462284 9194906 415.3 411.6 100 40 P110

459520 9200739 408.7 425.4 72 10.1 P351

455227 9199507 434.7 382.5 109.5 203.4 P396

459120 9201813 406.0 369.1 60 16 P431

465346 9200958 368.9 386.0 170 15 P548

467339 9202403 368.8 392.3 100 17.5 P589

463935 9201111 382.4 388.8 140 100 P686

464795 9199207 401.2 394.1 227 48 P692

464182 9198777 403.5 398.0 132 113 P696

464519 9200159 374.9 390.7 210 47 P697

464427 9199760 384.0 402.8 155 198 P701

464415 9197262 411.1 400.9 129.9 88 P1002

461163 9197506 417.6 408.3 107.5 11.3 P1565

465133 9193516 427.0 397.8 88 65.1 P1480

467340 9200130 382.8 380.5 90 11.3 P574

Figure 3 shows a cross-section of the simulation area with flow through the various formations indicated by (plane-projected) velocity proportional flow vectors.

The hydraulic budgets for the two aquifer systems, SAS and MAS, are listed in Table2. Of a total recharge of 9.66·₁₀6_m3_{/year on the top of the Plateau, 64% discharge from the}

springs on the northern slope (due to the existence of the water divide along P5-P6), about 16% is directed to the southern slope (in the State of Pernambuco), and about 20% (amounting to&2·₁₀6 _m3_{/year) percolates the Santana Formation, reaching the MAS}

Rio da Batateira aquifer where it constitutes 3.2% of the total input.

3.2 Hydrogeochemical Inversion

Recharge through the Santana Formation suggested by numerical modeling should be manifest in the chemical evolution of Rio da Batateira groundwater. For this reason,

Fig. 2 (A) Errors versus conductivity for Santana Formation (left). (B) Simulated versus observed hydraulic

head (right)

25000 Rio da Batateira Formation

Dry cells 0 6 3 Noflow cells 0 0 7 2 8 0 2 15000 3 0 9 Constant Head 10000 0 2 7 0 3 6 5000 ) m( e d uti tl a 0 4 5 0 1 8 0 5 4

20000 35000 Arajara Formation

Santana Formation

Non saturated part of cell 30000

Exu Formation

(m) 40000

PHREEQC inversion was performed in order to see whether the chemical composition of Valley groundwater also indicates the influence of the hydrogeochemical Santana envi-ronment. Aquifers on the top of the Araripe Plateau are composed of low-solubility minerals with great resistance to weathering. As their hydraulic conductivity is high, this promotes the rapid passage of Plateau recharge through the SAS, reaching the Santana Formation with a conductivity of 40mS/cm (Santiago et al.1997). The dominant species are Na+and Cl, probably originating from marine aerosol. Part of this water percolates the Santana Formation where it suffers the influence of several formation-typical hy-drogeochemical processes. According to the lithological sequence (see Sect. 2.2), calcite and dolomite dissolution/precipitation occur in the Romualdo Member; subsequently, incongruent dissolution of gypsum occurs in the Ipubi Member, due to the Ca2+–Mg2+– HCO3 facies acquired during the first step, and the water becomes supersaturated in

CaCO3 precipitating calcite. Cl concentration is higher in the final than in the initial

water, requiring a Cldonor mineral (Table3). The Santana Formation has a high fraction of evaporite minerals and halite (NaCl), being highly soluble, may be responsible for the increase in Clconcentration. Due to high concentrations of Ca2+and Mg2+in the final water, exchange of these ions with Na+in clay minerals, abundant in the Rio da Batateira Formation, occurs in this final step (as may be seen from the last two lines of Table4).

Organic matter, present in elevated concentration in Rio da Batateira Formation water, gives rise to biological activities that influence groundwater composition. Since ferric iron (from goethite in the Rio da Batateira Formation) and sulfate (from gypsum in the Santana Formation) are present, redox reactions of iron and sulfate will occur:

CH2Oþ4Fe3þþH2OCO2þ4Fe2þþ4Hþ ð1Þ

4CH2Oþ2SO24þ3HþH2SþHSþ4CO2þ4H2O; ð2Þ

Table 3 Physicochemical groundwater parameters used in hydrogeochemical inversion

Sample pH T

(8C) CE (mS/ cm) Ca2+ (mmol/ l) Mg2+ (mmol/ l) Na+ (mmol/ l) K+ (mmol/ l) Fe2+ (mmol/ l) Cl (mmol/ l) SO42 (mmol/l) HCO3 (mmol/l)

Initial 6.0 26.8 40.0 0.18 0.15 0.65 0.12 – 0.91 0.009 0.35 Final 7.3 39.8 904 3.22 2.45 2.48 0.41 0.02 1.77 3.91 4.12

Table 2 Hydraulic budget for Superior (SAS) and the Middle Aquifer System (MAS)

SAS MAS

Inputa Outputa Inputa Outputa

Recharge 9.64 (99.8%) 38.19 (63.6%)

Springs 6.19 (64.0%)

Rivers 19.90 (33.2%) 60.04 (100.0%)

Const. Headb _{0.02 (0.2%) 1.53 (15.9%)}

SAS to MAS 1.95 (20.1%) 1.95 (3.2%)

a

106m3/year b

The stability diagram (Fig. 4) shows that pyrite (FeS2) has a redox potential slightly

higher than that of sulfide, meaning that this highly insoluble mineral precipitates as soon as sulfides exist in solution:

FeS2þ2Hþþ2eFe2þþ2HS

; K¼10

18:479 ð3Þ

The relative contributions of all these processes are determined by the thermodynamics of the reactions occurring in the system, transforming water from its initial to its final composition (Table3). With these constraints, PHREEQC (Parkhurst and Appelo1999)

Table 4 PHREEQC simulated water transfer results (in mmol/l)

Phase Stoichiometry Results

#1 #2

Gypsum CaSO42H2O 6.03 6.54

Calcite CaCO3 4.88 5.59

Dolomite CaMg(CO3)2 2.36 2.24

Halite NaCl 0.82 0.82

CH2O CH2O 3.78 4.73

Goethite FeOOH 1.02 1.28

Pyrite FeS2 1.01 1.26

Anorthite CaAl2Si2O8 0.03 0.37

Albite NaAlSi3O8 0.00 0.00

K-feldspar KAlSi3O8 0.30 0.30

Ca-Montmorillonite Ca0.165Al2.33Si3.67O10(OH)2 0.00 0.45 Na-Montmorillonite Na0.5Al1.5Mg0.5Si4O10(OH)2 0.24 0.00

CaX2 CaX2 0.59 0.53

NaX NaX 1.17 1.05

calculates two possible sets of results, listed in Table4(where positive and negative values indicate addition and subtraction to water solution, respectively).

Both models have no difference in halite and K-feldspar dissolution, because these are the only donor phases for Cl, and K+. Neither model involves albite precipitation/dis-solution, indicating no substantial quantities of this mineral along the water flow path. The greatest difference between the two models is in clay precipitation. Result #1 shows Na-montmorillonite precipitation with relatively low-anorthite dissolution, whereas #2 sup-poses Ca-montmorillonite precipitation with anorthite dissolution 12 times higher than #1 to compensate for the decrease in Ca2+. The amount of calcite precipitation with dolomite and gypsum dissolution shows that dolomite and gypsum incongruent dissolution are important and common geochemical processes in this evolution. It is not possible to choose between these two sets of results in the absence of detailed information on mineralogy and water flow paths. In fact, a linear combination of the two models may be the best choice.

4 Conclusion

Results obtained from both flow modeling and hydrogeochemical inversion give a valuable contribution to understanding aquifer functioning in the Araripe Sedimentary Basin. Modflow indicates the percolation of 20% of recharge on the Plateau through the Santana Formation. PHREEQC hydrochemical simulation supports this flow model mainly through the strong influence of dolomite and gypsum dissolution. These minerals are typical of the limestone Santana Formation, but are absent in the sandstone aquifers of the Superior and Middle Aquifer Systems.

Thus, simultaneous application of Modflow and PHREEQC allowed the identification and quantification of Santana aquitard percolation and that way calls attention to the Araripe Plateau as recharge area to Cariri Valley aquifers that constitute the exclusive water suppliers to one of the most densely populated areas of Ceara´ State.

From the methodological point of view it is evident that the two modeling tools, using completely different data sets, lead to converging results, confers increased credibility on the conclusions drawn.

Acknowledgements The authors wish to thank COGERH (Companhia de Gesta˜o dos Recursos Hı´dricos

do Estado do Ceara´) and FUNCAP (Fundac¸a˜o de Amparo a` Pesquisa do Estado do Ceara´) for logistic and financial support, CAPES (Coordenac¸a˜o de Aperfeic¸oamento de Pessoal de Nı´vel Superior—Ministe´rio da Educac¸a˜o—Brazil) for a fellowship of one of the authors (Machado) during postgraduate studies. We thank Dr. A. Donegan for a critical reading of the manuscript and Aquatic Geochemistry reviewers for suggestions for improving it.

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