A spatial analysis of structural controls on Karst groundwater geochemistry at a regional scale

Journal of Hydrology (2007) 340, 244– 255

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A spatial analysis of structural controls on Karst groundwater geochemistry at a regional scale `le Valdes a,b,*, Jean-Paul Dupont a, Benoıˆt Laignel a, Sylvie Ogier a, Danie Thierry Leboulanger a, Barbara J. Mahler a a

ˆtie `re UMR CNRS 6143, Universite ´ de Rouen, 76821 Mont-Saint-Aignan Cedex, France Morphodynamique Continentale et Co ´ Paris-Sud, 91405 Orsay Cedex, Interaction et Dynamique des Environnements de Surface UMR 8148 – CNRS, Universite France b

Received 24 October 2006; received in revised form 23 April 2007; accepted 24 April 2007

KEYWORDS Major ions; Spatial analysis; Structural context; Regional scale; Chalk aquifer

The coupled spatial investigation of the geometrical and geochemical properties of a chalk karstic aquifer provides information on the degree to which geologic structure controls aquifer functioning and groundwater quality. Major ion concentrations in the chalk aquifer of the Haute-Normandie region (France) were measured at a high spatial resolution (more than 100 sampling sites over a 6000 km2 area) and mapped. The first observation is a continuity of the geochemical properties, in spite of the karstic properties of the aquifer principal components analysis of geochemical maps revealed two types of spatial distributions: ions with an autochthonous origin 2 (Ca2+, HCO3), and ions with a principally allochthonous origin (Cl, Na+, NO 3 , SO4 ). Mg2+ was categorised as both autochthonous (chalk dissolution) and allochthonous (brought in by infiltration of Tertiary deposits). To better understand the spatial distribution of the geochemistry, the aquifer geochemistry was compared to the physical properties of the aquifer, in particular aquifer thickness (representing aquifer geometry) and piezometric level (representing aquifer flow). Use of spatial correlation between the geochemical and the geometrical properties provided insight regarding the directional structure of the data and give evidence of directional relations between geochemical and geometrical properties. The degree of mineralisation (principally composed of Ca2+ and HCO 3 ions) increased along the direction of flow, corresponding to an increase in chalk dissolution rate along the flowpath. The steepest mineralisation gradients were related to an increase in the Mg/Ca ratio, evidence of longer residence times and corresponding to zones where aquifer flow capacity is limited because of a Summary

* Corresponding author. Address: Interaction et Dynamique des Environnements de Surface UMR 8148 – CNRS, Universite ´ Paris-Sud, 91405 Orsay Cedex, France. Tel.: +33 1 69 15 49 13; fax: +33 1 69 15 49 17. E-mail address: [email protected] (D. Valdes). 0022-1694/$ - see front matter ª 2007 Elsevier B.V. All rights reserved. doi:10.1016/j.jhydrol.2007.04.014

A spatial analysis of structural controls on Karst groundwater geochemistry at a regional scale

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decrease of the thickness of the flow section (anticlines or faults). These results highlight the dominant role played by the geometry and the structural context in controlling aquifer geochemistry. ª 2007 Elsevier B.V. All rights reserved.

Introduction The aqueous geochemistry at each point of within an aquifer reflects the quality of the water upgradient (in the saturated zone) and the quality of infiltration from the surface (in the unsaturated zone). Heterogeneities of atmospheric inputs and natural water–rock reactions result in a high degree of spatial variation in the geochemical properties of an aquifer. This study investigates the geochemistry of a Cretaceous chalk in Haute-Normandie which has karstic properties (Massei et al., 2003; Rodet, 1999; Valdes et al., 2006). The karst aquifers are supposed to be very discontinuous, so they are usually studied at the scale of small groundwater basins (from the input system: swallowing point to the output system: karst spring in the valley). This paper proposes to study this aquifer at a regional scale (6000 km2). In spite of its karst properties is there an organisation of the geochemical properties at the large scale of the general flows? Study of groundwater basins at a large scale have already been performed, but with a low resolution of geochemical data (e.g., the chalk aquifer Paris Basin, Kloppmann et al., 1998; or in the Somme catchment in France, Negrel and Petelet-Giraud, 2005). In this study, we use a high spatial resolution of geochemical data (about 150 sampling sites) that allow us to investigate more precisely the spatial variability of the aquifer geochemistry. The geochemistry of groundwater in the chalk aquifer of northern France and southern England has been widely studied in the Paris Basin (Kloppmann, 1995; Kloppmann et al., 1998; Negrel and Petelet-Giraud, 2005) and in England (Edmunds et al., 2003; Feast et al., 1998; Hiscock, 1993; Hiscock et al., 1996). The main factors used by these authors to explain the spatial differences of groundwater quality are the human influence, the land use, the drainage of the river valley, the thickness of superficial layers and the atmospheric inputs. The dominant major ions of the groundwater are Ca2+, 2+ HCO 3 , and Mg , these ions are autochthonous, they result from the dissolution of the chalk controlled by the CO2 partial pressure (PCO2 ) and pH (Bakalowicz, 1979). Cl, Na+,  SO2 4 and NO3 principally have an allochthonous origin. They may originate from atmospheric inputs (Meybeck, 1983, 1986; Ne ´grel, 1999), human activities on the catchment (Sherwood, 1989), agriculture (Negrel and PeteletGiraud, 2005; Widory et al., 2004) and are influenced by position valley (Hiscock, 1993) and thickness of superficial layer (Feast et al., 1998). GIS tools and geostatistical analysis of geochemical data often give insight into the underlying factors controlling hydrogeological processes. Kriging has been especially useful for analysing hydrochemical data at a regional scale (Goovaerts et al., 1993). The value of coupling these types of analyses with statistical analysis, such as principal com-

ponents analysis (PCA), was demonstrated by Reis et al. (2004) and Wang et al. (2001). Spatial analyses, such as spatial autocorrelations and cross-correlations, are more rarely used, but they may provide insight into the directional structure of the data or the spatial dependence of two regionalised variables. These tools are applied to a karst zone (low-order streams, Hauchard et al., 2002) as most of the flows is through subsurface and follows one main direction from South to North. The objectives of this study are • To determine if there is a continuity in the geochemical properties of the aquifer. • To determine the factors influencing the groundwater geochemistry: human influence, land use, atmospheric inputs, river valleys, geological features (structural settings) and hydrological features (groundwater flow). We use a three-step process to interpret the spatial variability of groundwater geochemistry in the context of the groundwater flow and geologic structural: first, the spatial distribution of each geochemical species, the groundwater flow, and the structural context are mapped at a high spatial resolution; second, PCA is performed on the data to group the ionic species by type; and third, spatial autocorrelation and cross-correlation are used to investigate the directional features of the data and the spatial dependence between the geochemical properties and the hydrogeological and structural context.

Hydrogeological setting and methods Hydrogeological setting The Eure department of France (Fig. 1) is located in a catchment of about 11,000 km2 (in the Seine catchment). This study focuses on the Eure department (about 6000 km2) rather than the entire catchment because much of the data are available only for this department. There is little urbanisation in the Eure department, and land use mostly is agriculture and livestock (Fig. 2a). The climate is temperate and maritime, with average temperatures of 10–12 C and average annual rainfall varying spatially from 600– 800 mm. The highest annual rainfall rates occur in the west and in the northeast of the department (Fig. 2b). The chalk plateaus are covered with impervious claywith-flints from 5 to 40 m thick (Fig. 1), which result from weathering of the chalk during different periods of the Cenozoic (Laignel, 2003). Quaternary loess (Lautridou, 1985) and Tertiary deposits occur as infill on weathered surfaces (pockets) in some places and in others provide continuous cover. The plateaus over most of the Eure department are composed of Cretaceous formations, except those at the

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Figure 1

Schematic diagram of the regional geology (after Quesnel et al., 1996; Laignel, 2003).

Figure 2 Characteristics of the Eure department: (a) agricultural land use (Corine Land Cover, BRGM), (b) spatial distribution of the average annual rainfall, (c) piezometric level and groundwater basins, and (d) spatial distribution of the saturated aquifer thickness and principal geologic structures.

western end, which are Jurassic. The oldest formations (Cenomanian) outcrop in the south and the youngest (Campanian) in the northeast. All the Upper Cretaceous formations are chalk except the Cenomanian, which has a sand facies (‘‘perched sands’’) in the southern part of the department. In the northeast, between the Eure and the

Seine rivers, the chalk is covered by Tertiary deposits (Fig. 2b). These deposits are composed of clayey sands and clays with a smectite content of up to 90%; the smectite often contains Mg2+ (Laignel, 2003), and infiltrates into the aquifer. Several structural features mark the region. The Seine fault (Fc) and the anticlines and synclines in the south

A spatial analysis of structural controls on Karst groundwater geochemistry at a regional scale and east of the Eure department have a predominantly N140-150 orientation perpendicular to the general groundwater flow. There are two major faults in the north-west: Fa, with the north segment uplifted, and Fb, with the south segment uplifted (Wazi, 1988). The Chalk aquifer is unconfined in the study area and discharges into the Seine river (Fig. 2c). In addition, three major rivers – the Iton, the Risle and the Eure – discharge into the Seine, dividing the aquifer south of the Seine into three groundwater basins with a northward direction of flow. The aquifer is karstified to some degree (Massei et al., 2003; Rodet, 1999; Valdes et al., 2006), and groundwater flow velocities are extremely heterogeneous: fissures and conduits provide underground drainage routes for the highly localised transport of water at velocities from 50–300 m/h (Calba et al., 1979). The hydrologic network is typical of a karst zone, with mostly low-order streams (Hauchard et al., 2002), as most of the flow is through the subsurface. The saturated aquifer thickness varies from a few meters to more than 300 m (Fig. 2d). Large variations in aquifer thickness are related to variations of the depth of the chalk base as well as to the geologic structure. The greatest thicknesses are located on the synclinal axis (in the south and northeast of the department, north of the Seine River)

247

and the smallest aquifer thicknesses correspond to an anticlinal axis in the south of the department, except for an area in the northwest of the department, where small thicknesses correspond to the aquifer outlet. Around the faults, the aquifer thickness varies greatly, decreasing on the uplifted segment.

Data and methods The Acce `s aux Donne ´es des Eaux Souterraines (ADES) database (the French national groundwater database, Bureau de Recherches Ge ´ologiques et Minie `res (BRGM)) provided mean geochemical properties for 157 springs and wells in the Chalk aquifer in and around the Eure department 2+  + (Fig. 3). The study focuses on Ca2+, HCO 3 , Mg , Cl , Na ,  2 NO3 , SO4 , CO2, and pH (Table 1). Sampling was conducted from 95 to 2005. For each sampling site, the number of measurements ranged from 2 to 20 with a mean of five measurements per site. A selection of the data were performed. About 5% of sampling sites were not used, when the standard deviation of the measures was judged to be too large with respect to the mean. These cases corresponds (1) to errors of measures or (2) to sites connected to karst systems and which may be disturbed by surface water contribution during rain events (Valdes et al., 2005). So the data represent the quality of groundwaters without surface water contribution. High-resolution (500 m lag) piezometric and aquifer thickness data were provided by the BRGM. Principal component analysis Principal component analysis (PCA) is a multivariate statistical technique used for data reduction of large data sets. This method commonly is used for environmental studies with a high degree of temporal variation (Ben Othman et al., 1997; Eisenlohr et al., 1997) or spatial variation (Reisenhofer et al., 1998; Wang et al., 2001). PCA were performed on the regionalised geochemical variables (Ca2+,  2 2+  + HCO 3 , Mg , Cl , Na , NO3 and SO4 ; and CO2, pH); aquifer thickness and piezometric level were added as supplementary variables and do not contribute to the factorial space of the PCA.

Figure 3

Table 1

Spatial analyses Interpolations. The data were interpolated by ordinary kriging (Goovaerts, 1999) with IDRISI software using an omnidi-

Sampling sites.

Principal statistical characteristics of the data set

Number of samples Min Max Mean Standard deviation

Ca2+ (mg l1)

HCO 3 (mg l1)

Mg2+ (mg l1)

Cl (mg l1)

Na+ (mg l1)

NO 3 (mg l1)

SO24 (mg l1)

pH

CO2 (mg l1)

Saturated aquifer thickness (m)

Piezometric level (m)

150

146

150

155

151

153

149

154

117

–

–

68.0 126.2 102.4 9.7

174.4 370.5 299.4 37.4

– 303.0 114.9 73.1

– 220.9 93.6 49.6

3.3 18.0 7.3 2.8

12.2 28.0 20.9 3.2

7.2 12.9 10.7 1.3

14.3 43.9 26.0 7.1

13.0 15.7 14.1 0.5

7.20 7.46 7.30 0.05

34.9 53.1 44.1 4.2

248 rectional variogram, which represents the variance between two samples for increasing lag space without taking the direction between the samples into account. The geochemical and hydrological variables were mapped with a 2000-m lag. Spatial correlations. Correlation analyses in hydrology are usually used for time-series (Box et al., 1994; Mangin, 1984). However, these analyses also can be used for spatial data using spatial autocorrelations or cross-correlations. Spatial autocorrelations provide information about the spatial structure of a regionalised variable (Zhang and Selinus, 1998). This function quantifies the linear dependence of successive values over the space. The correlation of each variable to itself is determined for increasing lag space (Dd) and for all directions, in order to characterise the spatial variability of the regionalised variable. The correlogram

D. Valdes et al. C(k) estimates the spatial variability of the regionalised variable for all directions h, resulting in a 2D autocorrelation function; r(k) is the spatial autocorrelation function: Cðk; hÞ ¼

nk 1X ðx d  xÞðx dþk  xÞ; n d¼1

rðk; hÞ ¼

Cðk; hÞ r2x

where r2x ¼

N 1 X ðx d  xÞ2 ; N d¼0

ð1Þ ð2Þ

where k is the lag (k = 0–m), h is the direction (the autocorrelation function being symmetric,h = 0–180), n is the length of the space series, x is a single regionalised value, x is the mean of the regionalised value, m is the truncation point, adjusted experimentally by Mangin (1984) to n/3, and r2x is the variance of the variable. An example is presented in Fig. 4a.

Figure 4 (a) Principles of spatial autocorrelation: A well-defined spatial structure is observed along the q1 direction; if there is no variation of the variable along the q1 direction, then the autocorrelation is equal to 1 for all lag space Dd1. The maximum variation is observed along the direction q2, therefore the spatial autocorrelation decreases rapidly when Dd2 increases. (b) Principles of spatial cross-correlation between two variables X and Y. A well-defined spatial structure is observed for both variables X and Y along the q1 direction. When there is no variation of both variables along the q1 direction, the cross-correlation is constant for all Dd1, but less than 1 because of a lag of Dd2 along the q2 direction.

A spatial analysis of structural controls on Karst groundwater geochemistry at a regional scale

249

The spatial cross-correlations provide information about the spatial dependence between two regionalised variables (Zhang and Selinus, 1998). Each variable is correlated to the other for increasing lag space and for all directions, in order to characterise the spatial dependence between the two regionalised variables (x and y) over the space for all directions h: nk 1X ðx d  xÞðx dþk  yÞ; n d¼1 qffiffiffiffiffi qffiffiffiffiffi Cðk; hÞ rðk; hÞ ¼ where rx ¼ r2x ; ry ¼ r2y ; rx ry

Cðk; hÞ ¼

ð3Þ ð4Þ

where r is the standard deviation of the variable. The crosscorrelation function is not symmetric, h varies from 0 to 360. An example is presented in Fig. 4b.

Results The Chalk aquifer groundwater facies overall are Ca–HCO3, but the ion concentrations vary throughout the Eure department (Table 1). Geochemical and geometrical properties of the aquifer were investigated and compared first along a flowpath and second at the regional scale of the Eure department. Principal components analysis was used to determine spatial relationships between major ion concentrations and their relation to morphostructural features such as faults, synclines, and saturated thickness. Spatial autocorrelations were investigated to determine whether the hydrologic, structural, and allochthonous features have a significant directional structure. Spatial cross-correlations were used to determine relations between concentrations of allochthonous ions, overall hydrogeology, and geologic structure.

Geochemical and geometrical properties along a flowpath A physical profile of the aquifer and geochemical profiles (Fig. 5) were constructed from south to the north-east of the study area along section AB (Fig. 2). The physical profile of the aquifer consists of the profiles of the DEM, the upper part of the chalk, the piezometric level, and the base of the chalk; these data visualisation of the variations of the saturated thickness of the aquifer.

Spatial approach: Geochemical and geometric properties PCA of the geochemical spatial distributions Principal components analysis were performed from the raster (with a 2000-m lag) of the geochemical data and aquifer properties (Table 2). The Ca2+ and HCO 3 concentrations are positively correlated with CO2 concentrations and negatively correlated with pH. The spatial distributions of Cl, 2 Na+, NO 3 and SO4 concentrations are positively correlated with each other. Mg2+ plots between the two groups (Ca2+,  2  + HCO 3 ) and (Cl , Na , NO3 , SO4 ). The correlation between the piezometric level and the ionic species considered together is negative. The correlation between the saturated thickness and the other variables is less than 0.5.

Figure 5

Geometric and geochemical profiles (mg l1).

The structure of the factorial space is strong, with two factors explaining 77% of the total variance (Fig. 6). Factor F1, which explains 51% of the variance, is interpreted as representing the origin of the ions. Factor F1 is strongly

250 Table 2

D. Valdes et al. Correlation matrix (significant values (p < 0.05) in bold)

Ca2+ HCO 3 Mg2+ Cl Na+ NO 3 SO24 pH CO2 Saturated aquifer thickness Piezo-metric level

Ca2+

HCO 3

Mg2+

Cl

Na+

NO 3

SO24

pH

CO2

Saturated aquifer thickness

Piezo-metric level

1

0.872 1

0.198 0.531 1

0.398 0.472 0.012 1

0.351 0.202 0.426 0.728 1

0.324 0.370 0.190 0.632 0.583 1

0.410 0.459 0.032 0.550 0.436 0.800 1

0.592 0.649 0.248 0.598 0.413 0.307 0.365 1

0.830 0.807 0.291 0.590 0.363 0.281 0.332 0.559 1

0.241 0.335 0.474 0.291 0.042 0.228 0.213 0.306 0.424 1

0.445 0.616 0.518 0.184 0.319 0.092 0.239 0.371 0.494 0.124

Figure 6 Factorial space of the PCA. and h, supplementary variable.

1

, contributing variable

and positively weighted on the allochthonous ions (i.e., 2 originating from the surface: Na+, Cl, NO 3 , SO4 Þ and somewhat more weakly and negatively weighted on the autochthonous ions (i.e., the ions originating from within 2+ the aquifer: Ca2+ and HCO 3 Þ. The central position of Mg reflects its mixed origin: allochthonous when its origin is infiltrated tertiary deposits and autochthonous when it is a product of chalk dissolution. The largest positive scores for the F1 factor, corresponding to the highest concentrations of allochthonous ions, are found in the south of the Eure department; the largest negative scores, corresponding to the lowest concentrations of allochthonous ions, are found in the north-eastern part of the department, on the anticlinal axis (Fig. 7a). Because Cl is an allochthonous ion that is regarded as conservative, its spatial distribution is used to explain the functioning of the allochthonous ions without the influence of an internal contribution or reaction. The spatial distribution of Cl concentration is organised along a direction dictated by the geologic structure (Fig. 7b). Factor F2, which explains 26% of the variance, is interpreted as representing the degree of mineralisation of the

groundwater. All of the variables have positives F2 scores (Fig. 6). Of note are the location of CO2 and the piezometric level in the variable space. CO2 is positively correlated with Ca2+ and HCO 3 and the piezometric level is negatively correlated with all the geochemical variables, or in other words, negatively correlated with the degree of mineralisation of the water. The lowest scores for factor F2, i.e., corresponding to less mineralised water, are located in the south of the department, and increase in the direction of the Seine River. However, in the east and north of the study area, north of faults Fa and Fb, the factor scores are similar. The highest degree of mineralisation occurs on the left bank of the Seine River and to the south of faults Fa and Fb (Fig. 7c). The highest Mg/Ca ratios are found between the Eure and Seine Rivers (Fig. 7d), in the groundwater below the tertiary deposits that supply Mg2+ to the chalk aquifer. Outside of this zone, the highest ratios are found in the south along syncline S1 and south of faults Fa and Fb. These high ratios indicate longer residence times in these areas. Spatial analyses Spatial autocorrelations were performed for three variables: the piezometric level, the saturated thickness, and Cl concentrations (Fig. 8). The two first variables describe the hydrological and structural context and the third is used to represent the allochthonous ions. The piezometric level shows strong autocorrelation along the direction 127 ± 5N; as aquifer flow by definition is orthogonal to this direction, we deduce that the overall direction of aquifer flow is 37N. Saturated aquifer thickness has a strong autocorrelation along the direction 145 ± 5N, which corresponds to the structural directions of the anticlines, synclines, and the Seine fault (Fc). The Cl autocorrelations lie along two principal directions: 127 ± 5N, corresponding to that of the piezometric head autocorrelation, and 145 ± 5N, corresponding to that of the saturated aquifer thickness autocorrelation. Spatial cross-correlations were performed between the aquifer thickness and Cl concentration, and the piezometric head and Cl concentration (Fig. 9). The cross-correlation of Cl with the aquifer thickness is relatively symmetric about the axis 145N. Negative scores around this

A spatial analysis of structural controls on Karst groundwater geochemistry at a regional scale

Figure 7

Figure 8 space.

251

Spatial distributions of (a) factor F1, (b) chloride concentration, (c) factor F2, and (d) Mg/Ca ratio.

Autocorrelation of (a) piezometric level, (b) saturated aquifer thickness, and (c) chloride concentration. Dd is the lag

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D. Valdes et al.

Figure 9 Spatial cross-correlation between (a) the saturated thickness of the aquifer and chloride concentration and (b) the piezometric level and chloride concentration. Dd is the lag space.

axis (Fig. 9a) reflect a negative correlation between the aquifer thickness and Cl concentration along the structural direction 145N. The cross-correlation between the piezometric level and Cl concentration is not symmetric (Fig. 9b). The scores of the cross-correlation are negative southwest of the direction 127N and are positive northeast of this direction.

Discussion Geochemical properties of the Chalk aquifer are controlled by factors at scales ranging from the microscale (e.g., chemical reaction) to the macroscale (e.g., regional flow and structural settings). The results presented here reveal the strong spatial structure of the geochemical properties of the chalk aquifer of the Eure department at the regional scale. The PCA shows that 77% of the spatial variation of the geochemistry is represented by two processes: the origin of the ions (autochthonous versus allochthonous) and mineralisation. The objective is to interpret the observed spatial distributions of the geochemistry, to determine the controlling factors, and to understand the role of aquifer flow and structure on the geochemistry.

Spatial distribution of the allochthonous ions and controlling factors The origin and the spatial distribution of the allochthonous ions usually are attributed to atmospheric inputs and/or to anthropogenic factors such as land use or domestic sewage

(Meybeck, 1983; Negrel and Petelet-Giraud, 2005; Sherwood, 1989) and/or to the position of the river valley (Feast et al., 1998; Hiscock, 1993). Meybeck (1986) described the variation in major-ion geochemistry of rain in France in an eastward direction from the Atlantic Ocean. On the basis of his work, the concentration of Cl in rain in the Upper Normandy region is estimated to vary decrease from 7 to 5 mg l1 from west to east. This gradient, however, is not observed in the allochthonous ions in groundwater: the highest Cl concentrations in groundwater (Fig. 7b) occur where the annual rainfall is lowest (Fig. 2b). Anthropogenic activities can affect concentrations of 2 Cl, Na+, NO ions in groundwater (Edmunds 3 and/or SO4 et al., 2003; Edmunds and Smedley, 2000; Kloppmann et al., 1998; Negrel and Petelet-Giraud, 2005). The good correlations Cl–NO3 (0.632), Cl–SO4 (0.55) and NO3–SO4 (0.800) and Fig. 10 show that sulfate, nitrate and chloride have the same origin. They probably come from the fertilisers. The spatial distribution of these allochthonous chemical species is well represented by the spatial distribution of the F1 factor. The comparison between the maps of the F1 factor (Fig. 7a) and of the land use (Fig. 2a) shows the maximum of concentration of allochthonous ions falls in an area of intensive land use, that confirms an origin from the fertilisers. On the other hand, in the north-east of the department (north of the Seine river) the concentrations of allochthonous are low in spite of the intensive land use in this area. So the land use plays a significant role in the concentration of allochthonous ions in the groundwaters, but is not the only explanatory factor.

A spatial analysis of structural controls on Karst groundwater geochemistry at a regional scale

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The results of the spatial autocorrelations and cross-correlations indicate that there is a relationship between concentrations of autochthonous ions, the hydrogeologic context (as represented by the piezometric level), and the structural context (as represented by the aquifer thickness). The increase in correlation between the piezometric level and Cl concentration along the direction 37N (the general direction of groundwater flow) suggests that the allochthonous ions are transported along the direction of flow. The saturated thickness of the aquifer is controlled by the geologic structure, which in turn controls the concentrations of the allochthonous ions. The negative correlation between the aquifer thickness and Cl concentration along the structural direction 145N (Fig. 9a) indicates that the highest values of Clconcentration (and more generally allochthonous ion concentrations) correspond to the smallest aquifer thickness. These results seem to show relations between Cl concentration and aquifer thickness and groundwater flow, however our current knowledge does not allow to explain these relations.

Mineralisation of the aquifer: spatial distribution and controlling factors

Figure 10 and [Cl].

Correlation between (a) [SO4] and [Cl], (b) [NO3]

Hiscock (1993) demonstrated the role of the position of river valleys for the groundwater quality in chalk aquifer in UK. He demonstrated the age of Chalk groundwater varies considerably, being modern in the fluvial zone, where recharge occurs directly with groundwater flow controlled by significant fissure development and very old (up to 18,000 years old) in interfluvial areas, where both recharge and fissure development are limited. In this study, just a few valleys drain the aquifer and their impact is not visible in the maps of geochemical properties. However, it is important to note that the resolution of the data are relatively low to show a variation in geochemistry in the valleys. Feast et al. (1998) and Hiscock (1993) showed groundwater in the river valley where overlying glacial deposits are thin or absent is characterised by high nitrate levels and is chemically oxidising in nature, whereas groundwater in interfluvial region is generally reducing and contain no detectable nitrate. In our study, the aquifer is unconfined and the mean concentration of dissolved oxygen in chalk groundwaters is about 7.37 mg/l with a maximum of 8.5 mg/l and a minimum of 4.5 mg/l, the groundwaters are oxidising and denitrification cannot occur. As rain-water geochemistry, land use or river valley positions do not completely explain the spatial distributions of the allochthonous ions, these spatial distributions must be controlled in addition by other factors.

The mineralisation of the chalk aquifer in the Eure department is represented by the F2 factor of the PCA. The facies change (sands/chalk) of the Cenomanian formation in the south of the department generates a change in the aqueous geochemistry: water with a low dissolved-solids content in the Perched Sands (conductivity <250 S cm1, data provided by the ADES databank) mineralises once it flows into the chalk, where water–rock interaction results in an increase 2+ in Ca2+, HCO concentrations. 3 , and Mg The projection of the piezometric level on the F2 axis in the PCA variable space is negative and opposed to the mineralisation (as represented by the projection of the ions) (Fig. 6). The negative correlation between the piezometric level and the mineralisation is evidence that the chalk aquifer water generally becomes more mineralised along the flow path, from upgradient (south) to downgradient (north), in the direction of the Seine River. The increase in the con2+ centrations of Ca2+, HCO (except under the ter3 , and Mg tiary deposits) results from the dissolution of the host matrix. The chalk groundwaters are at or close to saturation with calcite so that a change in the value of one variable in 2+ the carbonate system (Ca2+, HCO 3 , Mg , pH, or CO2) is balanced by a change in the concentration of one or more of the other ionic species (Bakalowicz, 1979). The pH of the waters decreases downgradient, while the concentration of CO2 increases (Fig. 5). Increases in concentrations of 2+ Ca2+, HCO along the flowpath are positively cor3 , and Mg related with the increase in CO2 concentration (correlation with Ca2+ or HCO 3 > 0:8, Table 2) and negatively correlated with the pH (negative correlation <0.6 between the pH and Ca2+ or HCO 3 , Table 2). The decrease in pH and increase in CO2 results in a more aggressive water, causing increased dissolution of the chalk and an increase in Ca2+, HCO 3 , and Mg2+ concentrations. The geologic structure controls aquifer flow, affecting residence time and thereby aquifer geochemistry. The Mg/ Ca ratio commonly is used as an indicator of the residence

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D. Valdes et al.

Figure 11

Influence of geologic structure on groundwater flow.

time of the water (Edmunds and Smedley, 2000; Kloppmann et al., 1998; Langmuir, 1971), resulting from the incongruent dissolution of magnesium calcite and dolomite (Bakalowicz, 1979; Musgrove and Banner, 2004). The spatial distribution of the Mg/Ca ratio reflects the heterogeneity of the flow capacity of the aquifer, resulting in zones with different residence times. Three zones have a relatively high Mg/Ca ratio (Fig. 7d), which appear to be related the geometry of the aquifer and thus to the structural context (Fig. 11). The first zone is located along the syncline in the south of the department, where the decreasing thickness of the aquifer from the syncline to the anticline (from about 300 m to about 50 m; Fig. 5) acts as a barrier to flow (for the same width of flow, the flow velocity will increase with decrease in the aquifer thickness). This results in an increase in the residence time and Mg/Ca ratio (Elliot et al., 1999). The two others zones are located to the south of faults Fa and Fb (Fig. 7d). The section north of fault Fa is uplifted: the base of the aquifer is abruptly raised, decreasing the cross-sectional area of flow and resulting in flow in a direction lateral to the fault. A similar situation occurs in the uplifted section south of fault Fb (Fig. 11).

physical properties of the aquifer (the piezometric level and the aquifer thickness) indicate that structural and hydrogeologic factors play an essential role in influencing aqueous geochemistry. Further, mineralisation increases along the flowpath, corresponding to increasing dissolution of the chalk matrix. The highest mineralisation rates are related to longer residence times, and correspond to zones where the aquifer flow capacity is limited because of a decrease in the cross-sectional area of flow, related to the location of anticlines or faults. These results indicate the predominance of an ‘‘internal’’ control over the geochemistry of the groundwaters: the flow and the structural features of the aquifer. The studied area is particularly relevant, the flow being oriented from south to the north with the structural settings perpendicular to this direction. The results presented here demonstrate that the use of spatial autocorrelations and cross-correlations allows analysis of the distribution of continuous geochemical characteristics of the aquifer studied. The methodology used in this study, that is, the joint spatial analysis of geochemistry and physical properties, is of wide interest, as it can be applied to any aquifer or to other spatial problems in the environment.

Conclusion The high spatial resolution of the geochemical data for the chalk aquifer (Eure department, France) allow the description of groundwater geochemistry in a large watershed at a regional scale. The first observation is a continuity of the geochemical properties along the flowpath, in spite of the karstic properties of the aquifer (the karst being a discontinuous medium by definition). However, discrimination of heterogeneities within the Ca-HCO3 groundwaters are observed. The spatial variability of groundwater geochemistry often is usually explained by the spatial variability of the geochemistry of the recharge water, which in turn is influenced by anthropogenic factors, the spatial variability of the geochemistry of the rain or the position of river valleys. In this study, the land use has an evident impact but cannot explain totally the spatial distributions observed, the position of the river valleys is not really visible (the resolution of the data in the valleys being too low) and the rain distribution does not correspond to the spatial distributions of allochthonous ions. Investigations and interpretation of the relation between the spatial distribution of the geochemistry and that of the

Acknowledgements The authors would like to thank the Seine-Normandie Water Authority and the Conseil Ge ´ne ´ral de l’Eure (France) for financial support, and the BRGM for the data provided. Finally, we gratefully thank Wolfram Kloppmann for his constructive and insightful comments.

References Bakalowicz, M., 1979. Contribution de la ge ´ochimie des eaux a ` la connaissance de l’aquife `re karstique et de la karstification. Ph.D. Thesis, Universite ´ Paris VI. Ben Othman, D., Luck, J.-M., Tournoud, M.-G., 1997. Geochemistry and water dynamics: application to short time-scale flood phenomena in a small Mediterranean catchment: I. Alkalis, alkali-earths and Sr isotopes. Chemical Geology 140 (1–2), 9–28. Box, G.E.P., Jenkins, G.M., Reinsel, G.C., 1994. Time Series Analysis: Forecasting and Control. third ed.. Prentice-Hall, Englewood Cliffs, NJ.

A spatial analysis of structural controls on Karst groundwater geochemistry at a regional scale Calba, F., Charrie `re, G., Conrad, G., Lefebvre, D., Rodet, J., 1979. Relations entre le de ´veloppement du karst de la craie, la dynamique et la qualite ´ des eaux souterraines du Pays de Caux. Bulletin Trimestriel de la Socie ´te ´ Ge ´ologique de Normandie et des Amis du Museum du Havre 66 (4), 45–68. Edmunds, W.M., Smedley, P.L., 2000. Residence time indicators in groundwater: the East Midlands Triassic sandstone aquifer. Applied Geochemistry 15 (6), 737–752. Edmunds, W.M., Shand, P., Hart, P., Ward, R.S., 2003. The natural (baseline) quality of groundwater: a UK pilot study. The Science of the Total Environment 310 (1–3), 25–35. Eisenlohr, L., Bouzelboudjen, M., Kiraly, L., Rossier, Y., 1997. Numerical versus statistical modelling of natural response of a karst hydrogeological system. Journal of Hydrology 202 (1–4), 244–262. Elliot, T., Andrews, J.N., Edmunds, W.M., 1999. Hydrochemical trends, paleorecharge and groundwater ages in fissured Chalk aquifer of the London and Berkshire Basins, UK. Journal of Applied Geochemistry 14, 333–363. Feast, N.A., Hiscock, K.M., Dennis, P.F., Andrews, J.N., 1998. Nitrogen isotope hydrochemistry and denitrification within the Chalk aquifer system of north Norfolk, UK. Journal of Hydrology 211, 233–252. Goovaerts, P., 1999. Using elevation to aid the geostatistical mapping of rainfall erosivity. Catena 34 (3–4), 227–242. Goovaerts, P., Sonnet, P., Navarre, A., 1993. Factorial kriging analysis of springwater contents in the Dyle River basin, Belgium. Water Resources Research 29 (7), 2115–2125. Hauchard, E., Laignel, B., Delahaye, D., 2002. Proposition d’un nouveau schema structural du Nord-Ouest du bassin de Paris reposant sur l’analyse fractale des reseaux de thalwegs et les donnees recentes de la geologie regionale: proposition of a new structural map of the northwestern Paris Basin, based on the fractal analysis of the talweg networks and the new results of regional geology. Comptes Rendus Geoscience 334 (4), 295–302. Hiscock, K.M., 1993. The influence of pre-Devensian glacial deposits on the hydrogeochemistry of the Chalk aquifer system of the North Norfolk, UK. Journal of Hydrology 144 (1–4), 335–369. Hiscock, K.M., Dennis, P.F., Saynor, P.R., Thomas, M.O., 1996. Hydrochemical and stable isotope evidence for the extent and nature of the effective Chalk aquifer of north Norfolk, UK. Journal of Hydrology 180 (1–4), 79–107. Kloppmann, W., 1995. Datation des eaux de la nappe de la craie (France et Allemagne): approche chimique et isotopique. Ph.D. Thesis, Univ. Paris Sud. Kloppmann, W., Dever, L., Edmunds, W.M., 1998. Residence time of Chalk groundwaters in the Paris Basin and the North German Basin: a geochemical approach. Applied Geochemistry 13 (5), 593–606. Laignel, B., 2003. Caracte ´risation et dynamique e ´rosive de syste `mes ge ´omorphologiques continentaux sur substrat crayeux. Exemple de l’Ouest du Bassin de Paris dans le contexte nord-ouest europe ´en. Livret I: Axes et De ´veloppement de la Recherche. H.D.R., Universite ´ de Rouen. Langmuir, D., 1971. The geochemistry of some carbonate ground waters in central Pennsylvania. Geochimica et Cosmochimica Acta 35 (10), 1023–1045. Lautridou, J.-P., 1985. Le cycle pe ´riglaciaire ple ´istoce `ne en Europe du Nord-Ouest et plus particulie `rement en Normandie. Universite ´ de Caen. Mangin, A., 1984. Pour une meilleure connaissance des syste `mes hydrologiques a ` partir des analyses corre ´latoire et spectrale. Journal of Hydrology 67, 25–43. Massei, N., Wang, H.Q., Dupont, J.P., Rodet, J., Laignel, B., 2003. Assessment of direct transfer and resuspension of particles

255

during turbid floods at a karstic spring. Journal of Hydrology 275 (1–2), 109–121. Meybeck, M., 1983. Atmospheric inputs and river transport of dissolved substances. Dissolved loads of rivers and surface water quantity/quality relationships. In: Webb, B.W. (Ed.), Proceeding of the Hamburg Symposium, 1983. International Association of Hydrological Sciences. IAHS Publication 141, pp. 173–192. Meybeck, M., 1986. Chemical composition of headwater streams in France. Sciences Geologiques – Bulletin 39 (1), 3–77. Musgrove, M., Banner, J., 2004. Controls on the spatial and temporal variability of vadose dripwater geochemistry: Edwards aquifer, central Texas. Geochemica et Cosmochimica Acta 68, 1007–1020. Ne ´grel, P., 1999. Geochemical study of a Granitic Area – The Margeride Mountains, France: chemical element behavior and 87Sr/86Sr constraints. Aquatic Geochemistry 5 (2), 125–165. Negrel, P., Petelet-Giraud, E., 2005. Strontium isotopes as tracers of groundwater-induced floods: the Somme case study (France). Journal of Hydrology 305 (1–4), 99–119. Quesnel, F., Laignel, B., Lefebvre, D., Meyer, R., Lautridou, J.-P., Lebret, P., 1996. Les formations re ´siduelles a ` silex en Haute-Normandie. Evolution continentale cenozoı ¨que du NW du Bassin de Paris et utilisation potentielle comme granulats. Livret excursion, In Colloque Ge ´omorphologie et Formations superficielles, Rouen, 19–21 mars 1996, BRGM Ed. 248, pp. 65–99. Reis, A.P., Sousa, A.J., Ferreira da Silva, E., Patinha, C., Fonseca, E.C., 2004. Combining multiple correspondence analysis with factorial kriging analysis for geochemical mapping of the gold– silver deposit at Marrancos (Portugal). Applied Geochemistry 19 (4), 623–631. Reisenhofer, E., Adami, G., Barbieri, P., 1998. Using chemical and physical parameters to define the quality of karstic freshwaters (Timavo river, North-Eastern Italy): a chemometric approach. Water Research 32 (4), 1193–1203. Rodet, J., 1999. Tectonic network as the initial factor of karstification of the chalk limestones in the Perche hills (Orne, Normandy, France). Geodinamica Acta 12 (3–4), 259–265. Sherwood, W.C., 1989. Chloride loading in the South Fork of the Shenandoah River, Virginia, USA. Environmental Geology (Historical Archive) 14 (2), 99. Valdes, D., Dupont, J.-P., Massei, N., Laignel, B., Rodet, J., 2005. Analysis of karst hydrodynamics through comparison of dissolved and suspended solids’ transport. Comptes Rendus Geosciences 337 (15), 1365–1374. Valdes, D., Dupont, J.-P., Massei, N., Laignel, B.t., Rodet, J., 2006. Investigation of karst hydrodynamics and organization using autocorrelations and T–[Delta]C curves. Journal of Hydrology 329 (3–4), 432–443. Wang, Y., Ma, T., Luo, Z., 2001. Geostatistical and geochemical analysis of surface water leakage into groundwater on a regional scale: a case study in the Liulin karst system, northwestern China. Journal of Hydrology 246 (1–4), 223–234. Wazi, N., 1988. Le Cre ´tace ´ du Roumois (Valle ´e de l’Oison) et le tertiaire-quaternaire des re ´gions voisines de la basse valle ´e de la Seine (Haute-Normandie). Statigraphie et tectonique. Universite ´ de Rouen. Widory, D., Kloppmann, W., Chery, L., Bonnin, J., Rochdi, H., Guinamant, J.-L., 2004. Nitrate in groundwater: an isotopic multi-tracer approach. Journal of Contaminant Hydrology 72 (1– 4), 165–188. Zhang, C., Selinus, O., 1998. Statistics and GIS in environmental geochemistry – some problems and solutions. Journal of Geochemical Exploration 64 (1–3), 339–354.