Hydrogeology Journal (2014) 22: 691–703
DOI 10.1007/s10040-013-1087-8
A three-dimensional hydrogeological–geophysical model
of a multi-layered aquifer in the coastal alluvial plain
of Sarno River (southern Italy)
R. Di Maio & S. Fabbrocino & G. Forte & E. Piegari
Abstract The coastal alluvial plain of Sarno River (Campania
Region, southern Italy) is a very rich environment that has
experienced a long history of changes due to both natural
phenomena such as eustatic sea-level variations and deposition of volcanoclastic sediments, and human civilizations
who populated this area since historical times. As a result, it
is characterized by complex stratigraphic sequences and
groundwater flow systems. The architecture of the multilayered aquifer system in a sample area, located in a densely
urbanized sector at the mouth of Sarno River, was
reconstructed. Starting from the analysis of stratigraphic
log data and laboratory geotechnical measurements, the
lithostratigraphical-unit sequence was retrieved and a realistic three-dimensional (3D) model of the hydrogeological
heterogeneity was obtained. The results of a detailed 2D
electrical resistivity tomography survey were used to support
the analysis of the spatial heterogeneity of the aquifer system
in a sector characterized by lack of log data. The integration
of hydrogeological and geophysical data allowed for the
reconstruction of a 3D hydrogeophysical model of the multilayered system, which electrically characterizes and
geometrically identifies two aquifers. Finally, piezometric-level
Received: 15 May 2013 / Accepted: 22 November 2013
Published online: 19 December 2013
* Springer-Verlag Berlin Heidelberg 2013
R. Di Maio : S. Fabbrocino : E. Piegari ())
Department of Earth Sciences, Environment and Resources,
University of Naples Federico II, Naples, Italy
e-mail: esterpiegari@gmail.com
R. Di Maio
e-mail: rodimaio@unina.it
S. Fabbrocino
e-mail: silvia.fabbrocino@unina.it
G. Forte
Structural and Geotechnical Dynamics Laboratory StreGa,
University of Molise, Termoli, Italy
G. Forte
e-mail: giovanni.forte@unina.it
measurements validated the hydrogeological–geophysical
model and showed the effectiveness of the methodology.
Keywords Heterogeneity . Groundwater management .
Electrical resistivity tomography . Hydrogeophysical
modeling . Italy
Introduction
The full assessment of complex, heterogeneous and anisotropic aquifer systems is key to understanding groundwater
conditions and contaminant transport. Groundwater models
are useful tools for management and protection of water
resources, but their predictive function is often limited by a
poor characterization of hydrogeological parameters at a local
scale. A variety of structural, volcanic and depositional
processes produces a composite spatial distribution of hydraulic conductivity in alluvial aquifer systems. Groundwater flow
and solute transport simulations in similar heterogeneous
bodies of intercalated aquifers and aquitards need a large
amount of observed data (Felletti et al. 2006; Ouellon et al.
2008; Hsien-Tsung et al. 2010; Vienken and Dietrich 2011).
Note that in the following, for practical purposes, aquitards and
aquicludes among confining units are distinguished according
to Poland et al. (1972). Specifically, an aquiclude is considered
as a body of saturated but relatively impermeable material,
which has very low values of “leakance” (i.e. the ratio of
vertical conductivity to thickness) and allows negligible
interaquifer flow. An aquitard is a saturated poorly permeable
bed, whose leakance ranges from relatively low to relatively
high values (Laney and Davidson 1986).
Many tools to acquire the knowledge of lithologic and
stratigraphic features and spatial heterogeneity at different
scales are available (de Marsily et al. 2005; Galloway 2010),
but it is essential to improve the hydrofacies models including
in situ geophysical investigations that better handle the rock
strata connectivity and the geometry of aquifers.
In such a context, electrical geophysical exploration may
provide a reliable model of aquifer heterogeneity, as it is able
to identify the strata sequence in terms of geometrical and
physical parameters (Drahor et al. 2011 and references
therein). In addition, proper relationships between aquifer
electrical and hydraulic properties can be recognized in order
692
to define the groundwater potential (Kelly and Frohlich
1985; Huntley 1986; Ahmed et al. 1988; Chandra et al.
2008). Nevertheless, established standard methodologies for
the assessment of hydrodynamic parameters of complex
aquifer systems are not yet available (Linde et al. 2006; Mele
et al. 2012).
During the last few decades, different approaches have
been proposed to correlate hydrogeological and geophysical
data (Hinnel et al. 2010 and reference therein). These
approaches can be mainly divided into three categories.
The first two categories integrate geophysical and hydrogeological measurements by means of an uncoupled inverse
approach, which relies on an independent inversion of
geophysical and hydrogeological data. In this framework, it
is possible to distinguish procedures that infer the hydrogeologic model by (1) simple inversion (e.g. Cassiani et al.
1998; Hubbard et al. 1999; Tronicke and Holliger 2005;
Koch et al. 2009; Sinha et al. 2009) or (2) joint inversion
(e.g. Hyndman et al. 1994; Chen et al. 2006; Linde et al.
2006) of survey data. In both cases, although different
methods are proposed to reduce the uncertainties related to
the non-uniqueness of the inversion procedure, geophysical
and hydrogeological data are treated independently, and the
hydrogeological model is not used to constrain the geophysical interpretation. Recently, a third category of approaches
is proposed which relies on direct coupling of hydrologic
models and geophysical models during inversion (Kowalsky
et al. 2005; Ferré et al. 2009; Hinnel et al. 2010).
In this study, an uncoupled inverse approach is adopted to
obtain two three-dimensional (3D) models, respectively,
hydrogeologic and geoelectric, derived from data sets
acquired on two adjacent areas. Specifically, the geoelectrical
survey was carried out to expand the hydrogeological model
in a restricted area, where stratigraphic log measurements were
not allowed. Then, a 3D hydrogeophysical model is set up by
using the electrical resistivity inverted data as constrains for
the analysis of the spatial heterogeneity of the aquifer system.
The test area is the coastal alluvial aquifer system of the
Sarno River plain (southern Italy). Despite its extension and
complex geological history, the current stratigraphical and
hydrogeological information is heterogeneous both for
quality and spatial distribution of data. Due to the composite
hydrodynamic condition and the high human impact of this
plain area, the study is focused on the portion including the
Sarno River mouth. In the following, after a brief description
of the geological and hydrogeological setting of the selected
area, its hydrostratigraphic and geophysical models are
discussed and combined to characterize at field scale the
multi-layer aquifer.
Geological and hydrogeological features
of the test area
The test area is located at the mouth of the Sarno River plain
(Campania Region, southern Italy), which is a coastal plain
about 200 km2 in area and is bounded by Mesozoic
carbonate reliefs to the east and south, and the SommaVesuvius volcano to the north (Fig. 1). It is the southern part
Hydrogeology Journal (2014) 22: 691–703
of the peri-Tyrrhenian Campanian Plain Graben, originated
during the Plio-Pleistocene by the opening of the Tyrrhenian
Sea (Patacca et al. 1990). Its buried structure is composed of
step-faults blocks of Mesozoic carbonate units of the
Apennine chain (Ortolani and Aprile 1985; Brancaccio et
al. 1991). NW–SE and NE–SW normal faults border the
carbonate bedrock that dips towards the Somma-Vesuvio
volcano and reaches the maximum depth of 2 km below the
town of Pompei (Barberi et al. 1980; Di Maio et al. 1998;
Gasparini 1998; Zollo et al. 1996, 2001), though it outcrops
seaward as the limestone horst of Rovigliano islet, just close
to the mouth of the Sarno River (La Torre et al. 1983).
According to the geological evolution of the Campanian plain, the Sarno River plain experienced periods of
tectonic subsidence and ground movements due to the
volcanic activity and eustatic sea-level changes during the
Quaternary (Brancaccio et al. 1991; Pescatore et al. 2001;
Rolandi et al. 2003; Marturano et al. 2011). As a result, in
this area, the Quaternary sedimentary successions are
more than 2,000 m thick and their stratigraphic framework
is very complex even at basin scale. Many studies, based
on stratigraphic and micropalaeontological analyses of
boreholes drilled in the south-western sector of the Sarno
River coastal plain (Pescatore et al. 2001; Marturano et al.
2011), allowed the reconstruction of its paleoenvironmental conditions and sedimentary facies changes related to
volcanoclastic aggradation/progradation and seaward shift
of the shoreline.
At basin scale, tephra deposits of the Campanian
Volcanic Zone (Rolandi et al. 2003), namely of the
Somma-Vesuvius volcano in the last 25 ka (Santacroce
et al. 2008 and references therein), interbedded with
marine and continental ones, provide important stratigraphical and geochronological markers.
The upper part of the fill overlies an ignimbrite formation
(Campanian Ignimbrite, 39 ka) related to one of the largest
eruptions that occurred in the Mediterranean region in the
last 200 ka, which vented along regional faults and
uniformly covered the plain (Barberi et al. 1978; De Vivo
et al. 2001; Rolandi et al. 2003). The tectonic pattern and
erosion phenomena affect the toplap surface of its tufaceous
facies, the so-called Campanian Grey Tuff, at depths of 10 to
more than 30 m below sea level (b.s.l.). So that, because of
tectonic dislocation and erosion phenomena, it is missing
just at the mouth of Sarno River (Aprile et al. 2004).
In summary, Pliocene and Quaternary deposits of the
Sarno basin are both marine and continental as complex
interactions between depositional processes evolve spatially
and temporally. As demonstrated by deep boreholes, such as
the Trecase 1, 1,900 m deep (Balducci et al. 1983; Brocchini
et al. 2001), the Sarno Plain was above sea level during the
Pliocene (Brancaccio et al. 1991; Cinque et al. 1993). From
the beginning of the lower Pleistocene, subsidence phenomena occurred and caused marine ingression.
In the lower part of the late Pleistocene, the subsidence,
coupled to the volcanic activity, continued. Then, in the
upper part, the plain uplifted due to the subsidence rate
decrease and due to the last glacial regression. After the
Campanian ignimbrite eruption and the consequent
DOI 10.1007/s10040-013-1087-8
693
Fig. 1 Geological and structural sketch of the Sarno River plain (Campania Region, southern Italy)
volcanoclastic aggradation, the plain became tectonically
rather steady and fluvial down-cutting also took place for
the sea-level lowering of the last glacial regression
(Brancaccio et al. 1991; Romano et al. 1994). In the
Holocene transgression maximum, lagoon and swamp
systems have been detected more than 2 km inland from
the present shoreline (Barra et al. 1996).
As a result, significant spatial variations of permeability are observed. The groundwater flow occurs in the
pattern of permeable coarse-grained sediments. Accordingly, more overlying groundwater flows occur, though at
basin scale only one groundwater flow system was
detected due to natural hydrogeologic conditions and well
completion (Celico and Piscopo 1995; Fabbrocino et al.
2007). However, leakage phenomena among overlying
aquifers can take place and the discharge occurs into the
sea:first the river is gaining, while towards the mouth it is
losing.
3D Hydrofacies model
3D geological and hydrogeological modelling is a
composite process of learning, interpreting and visualizing
buried depositional architectures, which is constrained by
limitations of actual understanding and data availability
(Robins et al. 2005; Beven 2007). A reliable modelling
methodology has to recognize the value of different types
of data in terms of both time and space as well as to make
the existing data (including past model predictions)
Hydrogeology Journal (2014) 22: 691–703
available. In this regard, it is possible to learn about
places and to constrain predictive uncertainties by extrapolating information in sites where the data are not
available and investigation cannot be allowed (Beven
2007). Following such criteria, this report provides the
reconstruction of the hydrogeological block diagram for a
complex coastal alluvial plain by combining the most
common existing data for geological and hydrogeological
characterization with high-resolution 3D resistivity
modelling.
The sample area extends for 250,000 m2 at the Sarno
River mouth and its digital model derives from fit survey
data. The study focuses on the integration of existing
information, which consists of 14 stratigraphic logs at
depths of 3 to more than 20 m, mainly located in the SE
sector (Fig. 2), and some geotechnical parameters of
recognized alluvial, marine and pyroclastic deposits
derived from laboratory tests.
The reliable reconstruction of the aquifer model is
carried out at the scale of aquifer systems and hydrogeological complexes. The hydrostratigraphy characterization derives from the analysis of the genetic
stratigraphy rank of depositional systems and system
tracts (Catuneanu 2006), and involves hydrogeological
survey and examination of cartographic records (aerial
photo, geologic and topographic maps).
Taking into account the Holocene evolution of the
Sarno River coastal plain (see section ‘Geological and
hydrogeological features of the test area’), the interpretation
of stratigraphic logs and the identification of the depositional
DOI 10.1007/s10040-013-1087-8
694
Fig. 2 Geological map of the sample area with distribution of existing stratigraphic logs
facies arise from the description of the lithology as well as
the grain-size composition and sorting of sediments.
At reference scale, the sedimentological analysis of 14
available stratigraphic logs was focused on detectable
changes in lithology, color and texture. Then, grain size,
shape and sorting analyses were performed to identify
geologic units related to specific volcanic events and
progradation of the plain (Pescatore et al. 2001). Such a
reconstruction of lithofacies evolutive trends highlighted
relevant properties of sediments, resulting in permeability
changes as well as geometric elements constraining
hydrofacies. Figure 3, for instance, shows the hydrofacies
identification process based on the aforementioned stratigraphic correlation for the stratigraphic-log B5 (see
Fig. 2).
Table 1 reports the hydraulic conductivity, K, obtained
by falling head permeability tests of nine hydrostratigraphic units detected in the investigated subsurface.
Borehole data were organized into segments and contacts.
Each contact has been associated with a particular
horizon, and therefore to the depositional sequence
(Lemon and Jones 2003). The 3D hydrofacies model of
the examined aquifer system was obtained by coupling
hydrostratigraphic cross-sections with the main geological
constraints correlated to geomorphological history of the
plain. Figure 4 shows the hydrogeological fence diagram
that is the framework of the 3D hydrofacies model
obtained by using the Aquaveo GMS 8.0 software.
The close shoreline suggests the site should be divided
into two domains traced by the coastal onlap. Thus, beach
and marine deposits are close to the current coast line,
Hydrogeology Journal (2014) 22: 691–703
while alluvial sequences are in the inner plain as a result
of interbedding and lateral facies changes (see Figs. 2 and
4). The beach lithofacies is mainly made of well-sorted
dark yellowish and dark greyish sands from coarse to fine,
with rounded clasts of lapilli and fragments of shells. It is
representative of a typical shoreface facies and constitutes
the Marine Sands Complex (MSC), which is prevalent in
the western sector. The alluvial sequence constitutes a
composite aquifer system (see Table 1 and Fig. 4), whose
borehole-derived lithofacies were related to the widespread units (see Fig. 3) reported by Pescatore et al.
(2001). The deeper hydrogeological complex, i.e. the
Sandy Gravelly Complex (SGC), dates back to pre-Roman
and Roman time, and is characterized by a lateral facies
change from shoreface to foreshore facies, with grain-size
coarsening. The SGC consists of gravel and dark-yellow
grayish sand from fine to coarse-grained, with rounded
and subrounded clasts of lapilli, crystals and weathered
pumices. It is a marker of a regressive trend, which
permitted coastal progradation and development of river
meandering dynamics. Furthermore, in the eastern sector,
at a mean depth of 12–14 m b.s.l., a deposit constituted by
organic-rich grey mud and peat, which is representative of
a backdune or meander cut-off environment, has been
identified. The lower degree of permeability of such a
deposit characterizes the Marshy Complex (MC).
The emplacement of the pyroclastic fall deposits,
dating back to the Vesuvius eruption of AD 79, has
advanced the aggradation/progradation of the plain. They
are composed of both white and gray pumices (Luongo et
al. 2003) and are recognizable at depths varying from 8 to
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695
Fig. 3 Key stratigraphic correlation relating lithofacies to hydrofacies for the log B5 in Fig. 2. (a) Borehole stratigraphy; (b) stratigraphic
units (Pescatore et al. 2001); (c) hydrostratigraphic-log
15 m b.s.l. along the river pattern and the pre-existing
topography. This Pumices Complex (PC), about 2 m thick,
is a well-sorted gravel layer, characterized by the highest
permeability in the stratigraphic sequence.
After the fall event, a pyroclastic density current
caused the deposition of ashes from medium-to-fine
grained with accretionary lapilli (volcanic sands) that
form massive (flow) or laminated structures (surge)
(Luongo et al. 2003). These pyroclastic flows and surge
deposits allow one to detect two hydrogeological complexes: the Volcanic Ash Complex (VAC) and the Silty
Sandy Complex (SSC). The latter is interbedded between
two volcanic ash layers, which are at depths of 12 and 7 m
b.s.l., respectively.
Post AD 79 eruption deposits, representative of mixed
pyroclastic and alluvial materials, close the sedimentary
succession. They consist of ashes, sands and gravels and
Table 1 Order of magnitude of the hydraulic conductivity, K, for
the hydrofacies recognized in the investigated subsurface
ID
Hydrofacies
SCC
RC
USGC
Silty Clayey Complex
Reworked Complex
Upper Sandy Gravelly
Complex
Volcanic Ash Complex
Silty Sandy Complex
Pumices Complex
Marshy Complex
Sandy Gravelly
Complex
Marine Sands Complex
VAC
SSC
PC
MC
SGC
MSC
K (m/s)
Aquitard
Aquifer/aquitard
Aquifer
10–7
10–3–10–5
10–3
Aquiclude
Aquitard
Aquifer
Aquiclude
Aquifer
10–9
10–5
10–1
10–9
10–2–10–3
Aquifer
10–2
Hydrogeology Journal (2014) 22: 691–703
define the following hydrofacies: Silty Clayey Complex
(SCC), Reworked Silt-Sand-Gravel Complex (RC) and
Upper Sandy Gravelly Complex (SGC).
The stratigraphic and geomorphologic setting of
Quaternary deposits is transferred in a 3D aquifer model
shown in Fig. 5, whose hydrostratigraphy points out the
distribution of alluvial, marine and volcanic units and the
influence of the variation of the coastal onlap. In
particular, the representative volume of such complex
aquifer system is shown in Fig. 5a with a cut along the 1–
2 transect, which evidences the paleoriverbed, also visible
in the hydrostratigraphic cross-section along the BB′ line
(Fig. 5c). The section AA′ (Fig. 5b), instead, shows the
lateral facies change toward the marine deposits.
Figure 5 suggests that, in the eastern area, the
groundwater flow is confined and takes place mainly in
the deeper and most permeable aquifer, i.e. the SandyGravelly and the Pumices complexes, underlying the
volcanic ash layer at depth of about 14 m b.s.l. The top
of this aquifer declines toward the NW due to the path of
the buried paleoriverbed (Fig. 5a,c), which is revealed by
coarser and most permeable reworked sediments. A
shallower aquifer is present at depth, variable from 4 to
7 m b.s.l., and is represented by the Upper Sandy Gravelly
and the Reworked Silt-Sand-Gravel complexes. The poor
grain-size sorting and the discontinuity of the most
permeable layers cause this aquifer to be less productive.
In the western sector, the aquifer becomes unconfined and
unique, because the aforementioned most permeable
complexes are interbedded with the Marine Sands Complex
(Fig. 5b). In addition, it is worth noting that the buried path
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696
Fig. 4 Hydrogeological fence diagram and main geological information. The codes of the complexes are explained in Table 1
Fig. 5 a 3D hydrofacies model with a cut along the 1–2 line that shows the paleoriverbed. Key hydrostratigraphic cross-sections along the
b AA’ and c BB’ lines, showing, respectively, the lateral facies change toward the marine deposits and the buried paleoriverbed
Hydrogeology Journal (2014) 22: 691–703
DOI 10.1007/s10040-013-1087-8
697
Fig. 6 a 2D inversion of the resistivity tomography data acquired along the cyan profile shown in the plan-view map of Fig. 5. b 3D
inversion of the ERT data acquired along the profiles of Fig. 5 and shown with two cutting planes, respectively, parallel and perpendicular
to the N135W oriented profiles
of the paleoriverbed, which significantly affects the hydrostratigraphical sequence, constrains the aquifer/aquitard
distribution in the NE sector of the survey area, where log
data are missing (see inset of Fig. 5). Thus, to improve the
paleoriverbed buried pattern and to investigate the spatial
continuity of hydrofacies, which is crucial for management
and protection of water resources of this highly urbanized
costal area, a 2D electrical resistivity tomography (ERT)
survey in the northern part of the test site (see Fig. 5) was
carried out, as discussed in the following.
3D geoelectrical model
In the last few decades, increasing attention has been
devoted to applications of geophysical methods to hydrogeological studies. Hydrogeophysics, in fact, is a new
branch of applied geophysics (Hubbard and Rubin 2002;
Rubin and Hubbard 2005; Vereecken et al. 2006; Hinnel
et al. 2010) that is founded on non-invasive geophysical
measurements for deriving physical properties which can
be correlated to hydrological variables (e.g., water
content, porosity, solute concentration). Indeed, conventional sampling techniques, besides being invasive, are
generally applied at few measurement points, thus not
permitting an exhaustive description of the shallow and
deep vadose zones. Conversely, the geophysical techniques provide high-resolution images of hydrogeological
Hydrogeology Journal (2014) 22: 691–703
structures in terms of geometrical and physical quantities
also in the vadose zone (Daily et al. 1992; Cassiani and
Binley 2005). Among all suitable methods, electrical
geophysical prospecting is doubtless one of the most
prominent and used for hydrogeological purposes, by
virtue of the well-known dependence of the electrical
resistivity on hydraulic properties (Slater 2007; Di Maio
and Piegari 2011). In addition, the development of
increasingly effective 2D or 3D data acquisition techniques has allowed detailed space mapping of resistivity
values that, if monitored over time, can well describe the
spatial and temporal variability of an aquifer system
(Sandberg et al. 2002; Vanderborght et al. 2005; Ogilvy
et al. 2009).
In particular, the geoelectrical prospecting used in the
present study was aimed at constraining the hydrofacies
model in the upper part of the NE sector of the survey area
(see Fig. 5), in order to recognize also in that zone the
heterogeneous soil profile with multi-layer structures (see
previous section), and to expand the in-depth modelling.
Accordingly, a 2D resistivity tomography survey was
carried out in an area of about 200×120 m2, where
geological investigations were not allowed.
Specifically, 2D electrical resistivity tomographies were
performed along 12 profiles, five with orientation N45W and
15 m distant from each other, and seven with orientation
N135W and 30 m distant from each other (Fig. 5). Profiles
that are N45W oriented have a length varying between 68
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698
Fig. 7 a 2D inversion of the resistivity tomography data acquired along the orange profile shown in the plan-view map of Fig. 5. b 3D
inversion of the ERT data acquired along the profiles of Fig. 5 and shown with three different cuts
and 115 m; profiles that are N135W oriented have a length
varying between 140 and 185 m. The measurements were
realized by using an axial dipole-dipole electrode configuration with an inter-electrode distance of 2 or 5 m, in order to
attain a good horizontal resolution and data coverage up to
the maximum exploration depth (Loke 2004).
The apparent resistivity data inversion was performed
by using the Res2D algorithm (Loke and Barker 1996;
Loke and Dahlin 2002), which consists of a least-squares
deconvolution method based on a linear process between
acquired apparent resistivity values as a function of real
resistivities. Then, the 2D ERT data were also inverted by
using the Res3Dinv algorithm (Loke 2004) to obtain a 3D
resistivity-data distribution of the investigated volume.
Figure 6 shows the inversion results of the 2D ERT
measurements carried out along a N135W oriented profile
(Fig. 6a) and two clipped volumes of the 3D data-
inversion results (Fig. 6b). The upper cross section of
Fig. 6b, which corresponds to the selected profile, well
matches the 2D image of Fig. 6a. From the figures, a
conductive level sandwiched between two relatively highresistivity layers appears in the depth range of about 2.5–
4 m b.g.l. By considering the values that characterize this
conductive layer, it can be correlated to the less productive
shallow aquifer system identified by the hydrogeological
analysis, which is composed of the Silty Clayey and the
Upper Sandy Gravelly Complexes, and underlies a quite
dry cover soil. In fact, the non-continuity of the
conductive layer (see Fig. 6b) well describes the heterogeneity emerging by the borehole log stratigraphy;
furthermore, a decrease of the resistivity values clearly
appears at the maximum investigation depth.
Figure 7 shows the inversion results of the 2D ERT
measurements carried out along a N45W oriented profile
Fig. 8 Mean resistivity values and variation ranges for a three N45W-oriented profiles and b five N135W-oriented profiles. Black arrows
indicate associations with hydrofacies (see also Table 2 and Fig. 9)
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699
Table 2 Order of magnitude of the hydraulic conductivity and
resistivity ranges of the six recognized hydrostratigraphic units
Hydrofacies
Depth
(m)
Hydraulic
conductivity
(m/s)
Resistivity
(ohm m)
Silty Clayey Complex
Upper Sandy Gravelly
Complex
Volcanic Ash Complex,
Silty Sandy Complex
Pumices Complex
Sandy Gravelly Complex
1–5
5–10
10–7
10–3
20–75
75–20
10–15
10–9–10–5
40–10
15
>15
10–1
10–2–10–3
5–20
20–80
(Fig. 7a) and three different cuts for the whole inverted
data volume (Fig. 7b). The images show a relatively
resistive layer approximately in the first 10 m b.g.l., and a
conductive layer with resistivity values of the order of 10
ohm m, which can be ascribed to the presence of an
aquifer. Moreover, an increase of the resistivity values
approximately starting from 25 m b.g.l. could indicate the
transition to a coarser grain size. It is worth noticing that
the inter-electrode distance used for N45W oriented profiles,
i.e. 5 m, does not allow a detailed definition of the geological
strata sequence in the first 10 m of the section.
An integrated interpretation of hydrogeological
and geophysical data
The combination of the geophysical measurements and the
hydrogeological analysis showed in previous sections
allows for the characterization of the electrical behavior
of the recognized hydrofacies and for extension of the
hydrofacies model toward the NE sector of the survey
area, where hydrogeological information is lacking.
As concerns the electrical characterization of the
hydrofacies, the variation range of the resistivity values
observed for each investigation depth was calculated. As
example, Fig. 8 shows the mean values and variation
ranges of electrical resistivity for three of the N45W
oriented profiles (Fig. 8a) and five of the N135W-oriented
profiles (Fig. 8b). Looking at the behaviour of the
resistivity mean values with the depth shown in Fig. 8a,
it clearly emerges that there is a minimum ranging from 5
to 10 ohm m, identified at about 15 m b.s.l. and
representative of the electrofacies of the Pumice Complex.
In addition, the increasing resistivity trend at deeper
depths permits one to locally assess the permeability
changes due to the grain-size sorting within the Sandy
Gravelly Complex. Namely, it maps the coarse sand and
gravel layer, whose thickness is at least 10 m. Such a
feature allows for expansion of the hydrofacies model in
both lateral and vertical directions. Conversely, the
shallower portion of the hydrostratigraphic succession,
about 2.5 m thick and composed of the Silty Clayey and
the Upper Sandy Gravelly complexes, shows a relatively
strong variation of the resistivity values ranging from
about 20 to 100 ohm m. This variability is likely
attributable to a different saturation degree of the aquifer
system due to both the hydrofacies grain-size sorting and
the aquifer and aquitard intercalation. As a result, it is
expected that the Silty Clayey and the Upper Sandy
Fig. 9 Correlation between geoelectrical and hydrogeological layers. a hydrostratigraphic cross-section along the BB’ line of Fig. 5. b 3D
resistivity model with a cut plane parallel to the N135W oriented profiles
Hydrogeology Journal (2014) 22: 691–703
DOI 10.1007/s10040-013-1087-8
700
Fig. 10 3D hydrogeological–geophysical model along the 1–2 cut of Fig. 5
Gravelly complexes exhibit permeability values less than
that of the deeper layers.
In the first 2 m of depth, Fig. 8b shows a resistivity
decreasing trend (from about 400 to 500 ohm m) corresponding
to Infill and Soil, and a slight increase of the resistivity mean
values down to about 5 m b.s.l., ascribable to the Silty Clayey
Complex. Interestingly, such an increasing trend is also visible
in Fig. 8a, even if it is stretched due to the reduced resolution
related to the resistivity data-sampling step. Finally, from about
5 to 10 m b.s.l., the resistivity decreases due to the presence of
the Upper Sandy Gravelly Complex.
The knowledge of porosity and water salinity values of
the recognized hydrogeological complexes would
strengthen the proposed correlation between electrolayers
and hydrofacies. However, such values are not available
and invasive tests cannot be performed in the survey area.
Besides, laboratory and in situ measurements of these
parameters are available for the Sandy Gravelly Complex
in neighbouring sites. In particular, a water electrical
conductivity value of about 1,400 μS/cm and an average
porosity of 53 % have been retrieved. By using such a
conductivity value and the average resistivity value of 50
Fig. 11 Comparison between hydrostratigraphic setting and groundwater conditions
Hydrogeology Journal (2014) 22: 691–703
DOI 10.1007/s10040-013-1087-8
701
ohm m (see Table 2), an average porosity value of 58 % is
estimated through the empirical Archie’s law (Archie
1942). This value is in very good agreement with the
observed experimental value.
To summarize the results discussed previously, Fig. 9
relates the results coming from hydrogeological and
geophysical studies and Table 2 provides a summary of
the outlined features. Finally, for the stratigraphic framework derived from the 2D electrical resistivity survey in
the NE sector, an additional inversion of hydrogeological
data was performed. As a result, the hydrogeological
model was improved and the pathway of the paleoriverbed
was clearly defined (Fig. 10).
To validate such a hydrogeological–geophysical model
and to trial the hydrodynamic conditions of the survey
area, groundwater level measurements in 20 piezometers
were carried out. They have shown, in the eastern sector,
the shallower aquifer is dry because of widespread
overpumping, and groundwater flow can take place only
after significant rainy events.
Furthermore, groundwater flow is detected within the
deeper Sandy Gravelly Complex in the eastern sector, and
within the Marine Sands Complex in the western sector.
The water table map (Fig. 11) shows that groundwater
flows into the sea along a main NE–SW direction.
Conversely, it is noteworthy to observe the influence of
aquifer system anisotropy on groundwater flowpaths.
According to the 3D hydrofacies model, it is possible to
correlate the main flowpath to coarser sediments and most
permeable hydrofacies along the buried paleoriver channel, as well as to associate the groundwater divide with the
recognized Marshy Complex aquiclude at mean depth of
13 m b.s.l. (Fig. 11).
Conclusions
In this report, the potential of an integrated and interdisciplinary approach to the assessment of complex multilayered aquifer systems is explored. Geophysical and
hydrogeological data coming from close survey areas have
been combined to identify the architecture of a complex
system made of five electrolayers, each of them
corresponding to one or more hydrofacies. In particular,
the Silty Clayey and the Upper Sandy Gravelly complexes, which are expected to exhibit permeability values
less than that of the deeper layers; the Pumice Complex,
characterized by the lowest values of resistivity ranging
from 5 to 10 ohm m at a depth of about 15 m; a Sandy
Gravelly Complex, whose increasing trend of resistivity
values permits local assessment of the permeability
changes due to the grain-size sorting with the depth. As
concerns the groundwater flow system, a main flow was
detected within the deeper Sandy Gravelly Complex in the
eastern sector, and within the Marine Sands Complex in
the western sector, flowing into the sea along a main NE–
SW direction.
It is worth noting that the realistic reconstruction of a
3D hydrogeophysical model has provided continuous
Hydrogeology Journal (2014) 22: 691–703
information in space, beyond the availability of logs, in
a highly urbanized area, where measurements are very
often prevented by logistic conditions, and management
and protection of water resources are strongly required.
Acknowledgements Authors are grateful to Pasquale Paduano for
his very friendly collaboration. Authors wish to thank Roberto Balia
and an anonymous reviewer for their useful suggestions and
comments, which helped improve the manuscript.
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