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Estimation of recharge in mountain hard-rock aquifers based on discrete spring discharge monitoring during base-flow recession

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Estimation of aquifer recharge is key to effective groundwater management and protection. In mountain hard-rock aquifers, the average annual discharge of a spring generally reflects the vertical aquifer recharge over the spring catchment. However, the determination of average annual spring discharge requires expensive and challenging field monitoring. A power-law correlation was previously reported in the literature that would allow quantification of the average annual spring discharge starting from only a few discharge measurements in the low-flow season, in a dry summer climate. The correlation is based upon the Maillet model and was previously derived by a 10-year monitoring program of discharge from springs and streams in hard-rock aquifers composed of siliciclastic and calcareous turbidites that did not have well defined hydrogeologic boundaries. In this research, the same correlation was applied to two ophiolitic (peridotitic) hard-rock aquifers in the Northern Apennines (Northern Italy) with well-defined hydrogeologic boundaries and base-outflow springs. The correlation provided a reliable estimate of the average annual spring discharge thus confirming its effectiveness regardless of bedrock lithology. In the two aquifers studied, the measurable annual outputs (i.e. sum of average annual spring discharges) could be assumed equal to the annual inputs (i.e. vertical recharge) based on the clear-cut aquifer boundaries and a quick groundwater circulation inferable from spring water parameters. Thus, in such setting, the aforementioned correlation also provided an estimate of the annual aquifer recharge allowing the assessment of coefficients of infiltration (i.e. ratio between aquifer recharge and total precipitation) ranging between 10 and 20%.
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REPORT
Estimation of recharge in mountain hard-rock aquifers based
on discrete spring discharge monitoring during base-flow recession
Stefano Segadelli
1
&Maria Filippini
2
&Anna Monti
2
&Fulvio Celico
3
&Alessandro Gargini
2
Received: 10 July 2020 /Accepted: 30 January 2021
#The Author(s) 2021
Abstract
Estimation of aquifer recharge is key to effective groundwater management and protection. In mountain hard-rock aquifers, the
average annual discharge of a spring generally reflects the vertical aquifer recharge over the spring catchment. However, the
determination of average annual spring discharge requires expensive and challenging field monitoring. A power-law correlation
was previously reported in the literature that would allow quantification of the average annual spring discharge starting from only
a few discharge measurements in the low-flow season, in a dry summer climate. The correlation is based upon the Maillet model
and was previously derived by a 10-year monitoring program of discharge from springs and streams in hard-rock aquifers
composed of siliciclastic and calcareous turbidites that did not have well defined hydrogeologic boundaries. In this research,
the same correlation was applied to two ophiolitic (peridotitic) hard-rock aquifers in the Northern Apennines (Northern Italy)
with well-defined hydrogeologic boundariesand base-outflow springs.The correlation provideda reliable estimate of the average
annual spring discharge thus confirming its effectiveness regardless of bedrock lithology. In the two aquifers studied, the
measurable annual outputs (i.e. sum of average annual spring discharges) could be assumed equal to the annual inputs (i.e.
vertical recharge) based on the clear-cut aquifer boundaries and a quick groundwater circulation inferable from spring water
parameters. Thus, in such setting, the aforementioned correlation also provided an estimate of the annual aquifer recharge
allowing the assessment of coefficients of infiltration (i.e. ratio between aquifer recharge and total precipitation) ranging between
10 and 20%.
Keywords Fractured rocks .Italy .Groundwater recharge .Base-flow recession .Power-law correlation
Introduction
Hard rocks cover approximately the 2035% of the Earth
surface and many are utilized as important aquifers (Amiotte
Suchet et al. 2003; Gustafson and Krásný 1994). Several of
these aquifers are in mountainous areas, playing a major role
in water supply along with the aquifers in flat areas of the
planet (Hilberg 2016;Vivirolietal.2007). The quantification
of recharge in hard rock mountain aquifers is a key issue for
the management of valuable groundwater resources as well as
for the assessment of climate change impacts. Several reviews
have been published that describe the main approaches for
aquifer recharge estimation such as water balance methods,
tracer methods, numerical methods, water-table fluctuation,
river hydrograph separation, etc. (e.g. Cuthbert 2010;de
Vries and Simmers 2002; Healy 2010;Huetetal.2016;
Scanlon et al. 2002). However, many of these approaches
require a large amount of information from long and complex
field monitoring campaigns that are hardly feasible in moun-
tain catchments. Moreover, the hard rock environment pro-
vides additional challenges for recharge estimate due to the
highly heterogeneous nature of the geologic materials (e.g.
Rohde et al. 2015a; Rohde et al. 2015b;Thivyaetal.2016).
For such challenging types of aquifers, more manageable ap-
proaches would be needed requiring only a few field measure-
ments to optimize the aquifer recharge assessment.
*Maria Filippini
maria.filippini3@unibo.it
1
Geological, Seismic and Soil Service, Emilia-Romagna Region
Administration, Viale della Fiera 8, 4027 Bologna, Italy
2
Department of Biological, Geological, and Environmental Sciences,
Alma Mater Studiorum - University of Bologna, via Zamboni 67,
40126 Bologna, Italy
3
Department of Chemistry, Life Sciences and Environmental
Sustainability, University of Parma, Parco Area delle Scienze 157/A,
43124 Parma, Italy
Hydrogeology Journal
https://doi.org/10.1007/s10040-021-02317-z
Garginietal.(2008) investigated the groundwater flow
systems within sedimentary hard rock aquifers in the
Northern Apennines (Italy), composed of calcareous and
siliciclastic turbidites. It is worth noting that the term
hard rock aquiferis generally related to igneous and
metamorphic rocks (Dewandel et al. 2006,2011;
Lachassagne 2008; Lachassagne et al. 2011;Neuman
2005); however, in some circumstances, sedimentary
rocks exhibit heterogeneous and anisotropic hydraulic
conductivity distributions similar to those commonly ob-
served for hard rock units, as in the case of the calcareous
and siliciclastic turbidite formations in the Northern
Apennines (Gargini et al. 2014; Piccinini et al. 2013).
Such units behave as very transmissive aquifers in favor-
able structural conditions, as evidenced by Gargini et al.
(2006), Vincenzi et al. (2009), and Vincenzi et al. (2014)
while investigating the hydrogeological effects induced
by the drilling of a high-speed railway tunnel connecting
Bologna and Florence (Italy). Gargini et al. (2008), based
on a large database of flow rate measurements in springs
and streams collected throughout more than 10 years,
found an empirical power-law correlation between the av-
erage discharge of a spring during base-flow recession
and its average annual discharge, in a dry summer cli-
mate. The correlation is controlled by the base-flow reces-
sion coefficient according to the exponential Maillet mod-
el (Maillet 1905). Assuming that the annual average dis-
charge of a spring equals the water flow that enters the
aquifer over the spring catchment, the correlation would
allow estimating the annual recharge of the aquifer
starting from a few measurements of spring flow rates
during the base-flow recession. However, since the inves-
tigated turbiditic aquifers do not have well-defined
hydrogeologic boundaries and catchments, the proposed
relationship could not be exploited for the estimation of
aquifer recharge.
This report aims to validate the aforementioned corre-
lation in a new setting that also has convenient boundary
conditions for the estimation of aquifer recharge. To these
aims, the study identified two hard-rock aquifers with a
well-defined catchment where the whole measurable dis-
charge (i.e. the sum of spring discharges), with no loss,
could be assumed equal to the recharge of the system. The
two aquifers are ophiolitic olistolites (known as Mt.
Prinzera and Mt. Zirone), mainly composed of fractured
peridotites and fully surrounded by low-permeability units
behaving as aquitards. These are located in the western
sector of the Northern Apennines, in a climatic and struc-
tural setting analogous to that investigated by Gargini
et al. (2008). The two selected aquifers are of environ-
mental and social interest being located in a natural re-
serve area (Mt. Prinzera) and being exploited for public
water supply (Mt. Zirone).
Materials and methods
Geological and hydrogeological setting
The two study areas of Mt. Prinzera and Mt. Zirone are located
near the confluence between the Taro and Ceno streams, about
36 km SW of the town of Parma, in the western sector of the
Northern Apennines (Emilia-Romagna Region, Italy; Fig. 1).
The Northern Apennines are a typical thrust-fold chain origi-
nated from the convergence and collision between the
Eurasian and African plates after the consumption of the
paleo-Tethys oceanic crust of the Ligurian-Piedmont basin.
Some ophiolitic bodies outcrop along the chain as isolated
remnants of obducted oceanic crust. These are mostly perido-
tites, serpentinites, gabbros and basalts formed in the Middle
to Upper Jurassic (Marroni et al. 2010) that today are embod-
ied within allochthonous Ligurian silty-clayey complexes
(Abbate 1986; Bortolotti et al. 2001).
Mt. Prinzera and Mt. Zirone are ophiolitic mountainous reliefs
(olistolithes) mainly consisting of strongly serpentinized perido-
tites (Di Dio et al. 2005;Venturellietal.1997) outcropping along
an orographic culmination of the external portion of the liguride
units. The Mt. Prinzera ophiolitic structure covers an area of
about 0.9 km
2
reaching a peak elevation of 725 m above sea
level (asl); it is about 250 m thick and gently dips to the north.
The Mt. Zirone ophiolite covers an area of about 2.6 km
2
with a
maximum elevation of 707 m asl; it is 50 m thick and dips to the
northwest. The ophiolitic rock masses have a very low matrix
permeability but appear extensively fractured thus behaving as
aquifers. Hydraulic tests provided a hydraulic conductivity rang-
ing between 1.1 × 10
7
and 5.7 × 10
7
m/s for these units
(Segadelli et al. 2017a). The olistolithes of Mt. Prinzera and
Mt. Zirone are bordered and underlain by low-permeability de-
posits (Figs. 2and 3) that are predominantly characterized by
polygenic breccias made out of blocks of limestones or marly
limestones inside a silty-clayey matrix with mineral cement
(Segadelli et al. 2017a,b). It is reasonable to assume that these
lower permeability units behave as aquitards, since the fine-
grained matrix clearly dominates over the limestone blocks
(Fig. 3c). Several perennial springs are located at the contact
between the ophiolitic aquifers and the aquitard unit. These
springs represent the whole outflow of the aquifers following
the conceptual model proposed by Segadelli et al. (2017b)for
Mt. Prinzera (Fig. 4).
The climate in the Mt. Prinzera and Mt. Zirone areas is
midway between Mediterranean and oceanic, with humidity
levels typical of boreal mountain zones close to the sea
(Costantini et al. 2013; Nistor 2016). The average annualrain-
fall is about 1,000 mm/year and the seasonal rainfall distribu-
tion is that typical of the Northern Apennines witha main peak
in autumn and a secondary peak in spring (Antolini et al.
2017). The driest season is summer-early autumn followed
by a dry period of secondary importance in early winter.
Hydrogeol J
Spring survey and monitoring
A detailed field survey was carried out to identify all the pe-
rennial springs pertaining to the two investigated aquifers. The
limited extent of the aquifers favoured this activity. The sur-
veys were carried out in April 2012 and in May 2016 at Mt.
Prinzera and Mt. Zirone, respectively. Seven springs were
identified in the area of Mt. Prinzera and five at Mt. Zirone.
All the perennial springs are located at the contact between the
ophiolitic massif and the underlying aquitard units (Fig. 2).
Nine out of the total 12 springs are exploited for public supply
of drinking water. The remaining three are not exploited and
respond to the description of rheocrene springs following
Springer and Stevens (2009).
Discharge was monitored on a weekly basis in all the springs
of Mt. Prinzera between September 2012 and September 2013,
whereas the springs of the Mt. Zirone area were monitored be-
tween October 2016 and October 2017. In both cases, the mon-
itoring lasted for at least a hydrogeologic year, i.e. from the
beginning of the recharge season (corresponding to a systematic
increase of water levels and/or spring flow rates) to the end of
base-flow recession in the next calendar year. The field measure-
ments of discharge (Q) were performed following an irregular
timeframe due to logistic constraints (see Tables S1 and S2 in the
electronic supplementary material (ESM). Discharge measure-
ments were performed using the volumetric method due to the
relatively low flow rates. In the case of springs exploited for
public water supply, the time to fill a 20-L graduated bucket
was measured to obtain discharge. In the case of non-exploited
springs, flumes and weirs were used to convey all the water
inside a smaller graduated container. Measurements were repeat-
ed at least three times at each monitoring point for the sake of
accuracy. Groundwater parameters (temperature: T,electrical
conductivity at 25 °C: EC, and pH) were measured on-site by
means of a portable device (Eutech Instrument, Thermo Fisher
Scientific Inc.) concurrently with each discharge measurement.
Estimation of averaged annual spring discharge
A power-law correlation was found by Gargini et al. (2008)
between the average annual discharge of a spring from field
monitoring (Q
A
) and its average discharge during hydrologi-
cal recession in the low flow season, i.e. summer in the inves-
tigated climate (Q
S
). Such correlation was derived experimen-
tally starting from a large dataset of 11 hydrogeologic years of
discharge monitoring on more than 80 springs in hard rock
aquifers in turbiditic formations of the Northern Apennines
and is expressed as in Eq. (1):
Fig. 1 Distribution of hard-rock aquifers in the Northern Apennines,
Italy. The area of Mt. Prinzera and Mt. Zirone and the area previously
investigated by Gargini et al. (2008) are highlighted in orange. Geological
database source: Geological survey of Emilia-Romagna and Tuscany
regions in GIS vector format at a scale of 1:10000
Hydrogeol J
QA¼AQ
B
Sð1Þ
The coefficient Aand the exponent Bwere obtained from
the linear fitting on a log-log plot of field data pertaining to
springs with similar recession coefficients (α). The coefficient
αis derived from the exponential model proposed by Maillet
(1905). In particular, Gargini et al. (2008) proposed six differ-
ent couples of values for Aand Bcorresponding to different
ranges of α(classes of α, from here on; Table 1). The data
within each of the six classes of αwere aligned on a log-log
plot of Q
A
VS Q
S
with a high coefficient of correlation (R
2
)
between 0.99 and 0.97. The rationale for choosing the Maillet
model for the analysis of recession hydrographs is provided in
the following section.
Equation (1) was applied to the springs of the Mt. Prinzera
and Mt. Zirone to predict an average annual discharge (Q
AE,
where the subscript E indicates an indirect estimate of Q
A
through the equation) starting from base-flow recession mon-
itoring (Q
S
).
The actual averaged annual discharge Q
A
was deter-
mined for each spring from field data. To account for the
uneven distribution of Qmeasurements over the
hydrogeologic year, Q
A
was determined for each spring
by disaggregating the flow rates measurements in four sea-
sons (fall: from start of the hydrogeologic year to
December 31st; winter: from January 1st to March 31st;
spring: from April 1st to June 30th; summer: from July 1st
to end of the hydrogeologic year) and by averaging the
four mean seasonal values. Q
S
was determined for each
spring by averaging only the flow measurements selected
for the recession analysis (criteria for the selection are in
the next section).
The estimated annual flow rates Q
AE
were compared
to the average annual discharge from field monitoring
Q
A
. The goodness of the prediction was quantified sep-
arately for Mt. Prinzera and Mt. Zirone using the nor-
malized root mean square deviation (NRMSD), expressed
as in Eq. (2):
Fig. 2 Geological sketch maps of aMt. Prinzera and bMt. Zirone.
Legend: a: Quaternary deposits; b: ophiolite hard-rock aquifers; c: poly-
genic breccias in clay matrix (aquitard); d: Helminthoid flysch; e:
Calpionella limestones; f: thrust; g: fault (the teeth indicate the down-
wards moved side); h: tectonic contact; i: geological cross section; l:
foliation attitude; m: perennial spring; n: borehole
Hydrogeol J
Fig. 3 aThe landscape view of Mt. Prinzera western side and bMt. Zirone southeastern side
The ophiolitic hard-rock aquifers rise from the surrounding gentle slopes made up of soft rocks (clay-rich breccias); cdetail of the contact between the
ophiolitic aquifer unit and the underlying aquitard
Fig. 4 Hydrogeological conceptual model of the aMt. Prinzera and bMt. Zirone aquifer systems. The traces of the sections are in Fig. 2
Hydrogeol J
NRMSD ¼1=nn
i¼1QAE iQAi
ðÞ
2
hi
=QAmax
QAmin
Þð
ð2Þ
where Q
Amax
and Q
Amin
are the maximum and mini-
mum averaged annual flow rates from field measure-
ments, respectively, and nis the number of monitored
springs.
Analysis of spring base-flow recession using the
Maillet model
The depletion hydrograph of springs and streams is the stage
of the hydrograph along which the discharge decreases over
time. The literature has been mostly focused on the base-flow
recession, i.e. the late stage of the depletion hydrograph when
streams are fed exclusively by groundwater discharge with no
disturbances from recharge processes. In this stage, the reces-
sion behavior is expected to provide information on some
intrinsic aquifer features (e.g. Azeez et al. 2015; Tague and
Grant 2004).
One of the first studies about base-flow recession
hydrographs is that of Boussinesq (1904), who proposed a
nonlinear quadratic behavior of aquifer discharge during re-
cession. That model is an exact solution of the diffusion equa-
tion (Boussinesq 1877) that describes groundwater flow
through a porous medium. The solution is based on the
Dupuit-Forcheimer assumptions which represent the first
mathematical formulation of the ideal Dupuit aquifer
(Dupuit 1863; Troch et al. 2013).
An approximation of the exact solution provided by
Boussinesq is the linearized model proposed by Maillet
(1905). Following Maillet, the relationship between the
groundwater discharge of a spring or into a stream and time
follow the exponential decay of Eq. (3) in the absence of outer
influences such as precipitation, surface storage, groundwater
abstraction or evapotranspiration:
Q¼Q0eαtð3Þ
where Qand Q
0
are the flow rates (L
3
/T) at time tand at the
beginning of the base-flow recession stage, respectively, and
αis a time constant (T
1
) representing storage lag-time. αis
related to the time required to halve the base-flow discharge
(t
0.5
) and can be expressed as in Eq. (4):
α¼ln0:5ðÞ=t0:5
½ ð4Þ
From a mathematical viewpoint, Eq. (3) is probably the
most convenient description of base-flow recession among
existing models (Dewandel et al. 2003). However, rigorous
hydrological analyses applied mostly to streams have demon-
strated that the linearized Maillet model is inadequate to de-
scribe the whole range of groundwater discharge behaviors
during base-flow recession. Semi-logarithmic recession
hydrographs of actual rivers are generally concave, suggesting
that αis not constant but instead decreases with decreasing
groundwater discharge into the stream (Brutsaert and Nieber
1977;Moore1997; Shaw and Riha 2012; Wittenberg 1994).
When analyzing the literature about recession analysis, one
has to take into account that the recession hydrograph of a
stream can be more complex than that of a spring because
stream flow is more subject to interactions with other compo-
nents of the hydrological cycle such as interflow, precipita-
tion, evapotranspiration acting within the root zone, and river
bank filtration, or it may be influenced by the initial moisture
conditions of the watersheds (Kirchner 2009; Shaw and Riha
2012). Differently, the base-flow recession hydrograph of a
spring is expected to be a mere expression of the averaged
hydrogeological features of the discharging aquifer. Because
of that, the recession trends of nonkarstic springs are more
likely to fit simpler models such as the linearized Maillet so-
lution, compared to streams. For instance, Dewandel et al.
(2003) showed that the recession hydrographs of springs fed
by ophiolite hard rock aquifers were well reproduced either by
the Maillet or the Boussinesq models, depending on aquifer
features.
Notwithstanding the limitations associated with the Maillet
model, it was decided to use this equation to analyze base-
flow recession, for two reasons: (1) the correlation between
annual and base-flow discharge proposed by Gargini et al.
(2008), which is the object of validation in this study, was
built on that model; (2) the model allows a simple and straight-
forward analysis of recession hydrographs, which is consistent
with the deliberately simple approach that is proposed here for
recharge estimation. It is worth noting that the recession anal-
ysis is performed with the sole scope of arranging the spring
hydrographs into different classes (i.e., ranges of αvalues)
representing different typesof recession behaviors (see pre-
vious section). To this scope, a certain degree of approxima-
tion caused by linearization may be tolerable. Moreover, the
subdivision in recession classes was validated using a second
Table 1 Classes of recession coefficient αproposed by Gargini et al.
(2008) and the A and B values associated to each class
Class α[day
-1
]AB
1>3×10
2
13.0 0.99
23×10
2
to 2× 10
2
5.2 0.91
32×10
2
to 1× 10
2
2.6 0.80
41×10
2
to 6× 10
3
1.9 0.92
56×10
3
to 3× 10
3
1.3 0.93
6<3×10
3
1.2 0.78
Hydrogeol J
type of analysis: the so-called recession plot(Brutsaert and
Nieber 1977) which represents another derivation of the qua-
dratic Boussinesq model. In such analysis, the first time de-
rivative of the discharge (dQ/dt) is plotted as a function of
mean discharge (Q
m
) within the dt interval, on a log-log plot.
The relationship is expected to be linear with a variable range
of slopes. The analysis has been successfully applied in hy-
drological studies of stream recession (e.g. Kirchner 2009;
Shaw and Riha 2012). The slopes of the recession plots were
compared with the αof Maillet to verify if the same arrange-
ment in recession classes proposed by Gargini et al. (2008)
was still discernible. More details on the development of re-
cession plots are in the ESM.
For the application of the Maillet model, a time period
corresponding to base-flow recession was selected within the
two hydrogeologic years covered by the monitoring. In both
cases, the recession season was initiated on July 1st and lasted
up until the end of the hydrogeologic year, in analogy with the
recession period previously considered by Gargini et al.
(2008). The choice to fix a standardbeginning of the reces-
sion season to July 1st (regardless to the specific shape of each
hydrograph) was made to test the feasibility of proposing a
standard monitoring period for the estimation of recharge in
climate zones similar to that of the Northern Apennines. As a
first step, the recession hydrographs were handled to minimize
disturbances from significant recharge events. In particular,
only the progressively decreasing values of discharge were
considered, making sure to keep at least three measurements
for each spring. Attention was also paid to obtain a good fit of
the Qdata along an exponential trend line with R
2
> 0.90. The
Maillet coefficient αwas extracted from the equation of the
same exponential trend line.
Results and discussion
Prediction of averaged annual flow rates
A hydrogeologic year was identified between 25 October
2012 and 28 August 2013 at Mt. Prinzera and between 17
October 2016 and 7 September 2017 at Mt. Zirone. Q
A
values
in the range of 0.04 to 2.69 L/s and of 0.11 to 1.42 L/s were
determined from field measurements at Mt. Prinzera and Mt.
Zirone, respectively, whereas Q
S
values ranged between 0.01
and 0.85 L/s at Mt. Prinzera and between 0.04 and 1.30 L/s at
Mt. Zirone (Table 2). The complete data-set of Qmeasure-
mentsisintheESM together with the complete spring
hydrographs and rainfall data from preexisting meteorological
stations. Recession analysis with the Maillet model was per-
formed on each spring hydrograph (Fig. 5)todetermineαand
the corresponding A and B parameters that drive the correla-
tion between Q
A
and Q
S
.
All the seven springs fed by the Mt. Prinzera aquifer, ex-
cept for P01, had at least one out of seven measurements of Q
excluded from the recession analysis. In particular, the Qmea-
surement of 14 July showed a deviation from the recession
trend (increasing Qcompared to the previous measurement) in
the hydrographs of P02P07, most likely induced by the rain-
fall events between 11 and 14July (35 mm in total; see ESM).
For springs P02 and P07, one and two other Qvalues were
excluded from the analysis, respectively, for the same reason
as already mentioned. In spring P05, a decreasing trend of four
consecutive Qmeasurements was identified starting from 21
July; the former three values were excluded because they did
not follow a decreasing trend. In general, the recession
hydrographs of Mt. Prinzera suggest that all the springs, with
the exception of P01, are responsive to rainfall events occur-
ring during the low-flow season, likely because these are con-
nected to shallower groundwater flow systems with a lower
bulk discharge compared to spring P01.
Six measurements of Qwere performed at the five springs
of Mt. Zirone during the low-flow season. In springs Z01, Z02
and Z04, the Qmeasurements of 15 and 25 July were exclud-
ed from the recession analysis since these are higher than the
preceding Qvalue on the hydrograph. These anomalies are
likely related to the rainfall events between 11 and 14 July
(38 mm in total), and that of 24 June (10 mm). In the case of
spring Z05, the Qvalues deviating from the decreasing trend
and excluded from the analysis are that of 25 July and 8
August. The deviation of 8 August may be related to a local
rainfall not detected by the available pluviometers. Spring Z03
shows a decreasing trend of three consecutive Qmeasure-
ments starting from 25 July; the former three values on the
Table 2 Results from summer recession analysis at the springs of Mt.
Prinzera and Mt. Zirone with measured and predicted annual flow rates
(Q
A
and Q
AE
,respectively).Valuesinitalic are totals
Aquifer Spring α[day
-1
]ClassQ
S
(L/s) Q
A
(L/s) Q
AE
(L/s)
Mt. Prinzera P01 1.00×10
2
3 0.848 2.689 2.279
P02 9.00×10
3
4 0.078 0.224 0.182
P03 1.66×10
2
3 0.033 0.250 0.170
P04 2.66×10
2
2 0.024 0.172 0.177
P05 2.70×10
2
2 0.077 0.375 0.505
P06 2.50×10
3
6 0.029 0.038 0.076
P07 3.70×10
3
5 0.012 0.045 0.021
Total: 1.101 3.793 3.409
Mt. Zirone Z01 1.75×10
2
3 0.084 0.141 0.358
Z02 2.65×10
2
2 0.036 0.113 0.251
Z03 4.33×10
2
1 0.114 0.482 0.151
Z04 2.90×10
3
6 1.304 1.421 1.476
Z05 7.60×10
3
4 0.075 0.150 0.175
Total: 1.612 2.306 2.411
Hydrogeol J
hydrograph were not considered since they do not follow a
decreasing trend. In general, the recession hydrographs of the
springs of Mt. Zirone appear less smooth compared to Mt.
Prinzera. This is also reflected by the lower degree of correla-
tion of the Qmeasurements on the semi-log plots, with Z04
and Z05 showing a R
2
of 0.89 and 0.81, respectively, margin-
ally below the fixed threshold of 0.90. This may be due to a
higher reactivity to rainfall events in the Mt. Zirone aquifer
compared to Mt. Prinzera, possibly driven by some intrinsic
features of the aquifer, e.g. smaller aquifer basin and/or higher
permeability, shallower and/or faster recharge pathways.
Alternatively, the less frequent and more abundant rainfall
events of the summer 2017 (Mt. Zirone monitoring) may have
caused more significant deviations of Qfrom the decreasing
recession trend, compared to summer 2013 (Mt. Prinzera
monitoring). In particular, 13 days of rainfall were registered
out of 69 with an average of 14 mm/day during the summer of
the hydrogeologic year 20162017, whereas during the sum-
mer of year 20122013, rainfall events occurred on 17 out of
58 days with an average of 6 mm/day. Nevertheless, such
interannual variability was considered as an opportunity to
verify the effectiveness of the proposed method in different
meteorological conditions.
The Maillet coefficient αranges between 2.7 × 10
2
and
3.0 × 10
3
days
1
in the springs of Mt. Prinzera and between
4.3 × 10
2
and 3.0 × 10
3
days
1
in the springs of Mt. Zirone.
In Table 2, each spring is ranked according to the classes of α
identified by Gargini et al. (2008). The coefficient αof each
Fig. 5 Analysis of the baseflow recession hydrographs of the springs of Mt.Prinzera and Mt. Zironeusing the Maillet model. The blue dots bordered in
black are that selected for the analysis
Hydrogeol J
spring was compared with the slope of the recession plot (S)of
the same spring, showing a good linear correlation between
the two on a log-log plot with R
2
of 0.87 (Fig. 6). The com-
parison suggests that the classes of αproposed by Gargini
et al. (2008) are still discernible when considering the slope
of a recession plot. Because of this observation, the Maillet
model is considered to be a proper tool for identifying classes
of recession behavior in the type of springs that are investigat-
ed within this research.
The values of Q
AE
range between 0.02 and 2.28 L/s at Mt.
Prinzera and between 0.15 and 1.48 L/s at Mt. Zirone. A
comparison between Q
A
and Q
AE
is shown in Fig. 7.Inthe
case of Mt. Prinzera, the NRMSD between Q
A
and Q
AE
is
6.3%, suggesting an overall good prediction. P06 and P07
are the springs where Q
A
and Q
AE
show the greatest differ-
ences compared to absolute values of averaged annual dis-
charge. It is worth noting that these are the springs with the
lowest averaged annual flow rates in the Mt. Prinzera area, in
the order of 1 × 10
2
L/s, and the Qmeasurements in the field
were likely affected by a higher relative error compared to the
other springs. At Mt. Zirone, Q
A
and Q
AE
show larger differ-
ences between each other compared to the springs of Mt.
Prinzera, with an NRMSD of 14.5%. The noisier summer
hydrographs typically observed in the Mt. Zirone springs
along with the smaller number of available Qmeasurements
compared to Mt. Prinzera may have lead to higher uncer-
tainties in the Q
AE
prediction. In the case of Mt. Zirone, a
continuous monitoring of flow rates (or a higher frequency
of discontinuous measurements) may have helped increase
the accuracy of Q
S
estimates and the consequent prediction
of Q
AE
.
The sum of Q
A
in the springs of Mt. Prinzera is equal to
3.79 L/s, whereas the sum of Q
AE
is 3.41 L/s, with a small
difference between the two of 0.38 L/s. In the case of Mt.
Zirone, the sum of Q
A
and Q
AE
is respectively 2.31 and
2.41 L/s, with a difference of 0.11 L/s.
Estimation of aquifer recharge
Since the monitored springs of Mt. Prinzera and Mt. Zirone
are the discharge outlets of a well-delimited aquifer system,
the sum of averaged annual discharges of the two groups of
springs over their catchment area corresponds to the recharge
(Rfrom now on) of the aquifer, assuming a steady-state
condition over the hydrogeologic year. Such a condition is
plausible in the presence of short and relatively quick ground-
water flow paths from the recharge area to the discharge
points. Short and quick flow paths were inferred in the two
Fig. 6 Comparison between the coefficient αof Maillet and the slope S
of the recession plot. The recession classesare identified with different
symbol shapes. The springs of Mt. Prinzera and Mt. Zirone are depicted
with red and yellow symbols, respectively
Fig. 7 Comparison between measured and predicted averaged annual
flow rates (Q
A
and Q
AE
, respectively) at the springs of Mt. Prinzera and
Mt. Zirone
Hydrogeol J
aquifers based on the temperature and electrical conductivity
of spring water (see data of Tand EC in the ESM). In detail,
the average annual water temperature ranges between 10.3
and 12.5 °C at the springs of Mt. Prinzera and between 10.4
and 12.5 °C at the springs of Mt. Zirone, showing values very
similar or slightly lower than the average annual air tempera-
ture measured at the selected meteorological stations (12.0 °C
in hydrogeologic year 20122013 and 12.5 °C in 20162017,
respectively for Mt. Prinzera and Mt. Zirone). Shallow
groundwater temperature is expected to be 1 to 2 °C higher
than the average annual air temperature (Anderson 2005;
Benz et al. 2017). If the temperature of groundwater
discharging from springs is similar to air, it likely means that
the temperature signal of the recharging water is preserved
down to the discharge points, which can be explained assum-
ing short and shallow flow paths through the aquifer. The
average annual EC of spring water ranges between 281 and
474 μS/cm at Mt. Prinzera and between 218 and 522 μS/cm at
Mt. Zirone. Such values are in the low range of EC previously
observed in literature for groundwater in ophiolitic aquifers
(typically up to 2,000 μS/cm; e.g. Abdalla et al. 2016;
Dewandel et al. 2005; Güler et al. 2017), suggesting a short
groundwaterrock interaction time. In particular, EC values
<850 μS/cm are representative of quick shallow groundwater
circulation following Dewandel et al. (2005).
For the estimation of R, a total catchment area of 771,478
m
2
was considered for Mt. Prinzera and of 534,000 m
2
for Mt.
Zirone (i.e. the extent of the ophiolitic outcrops), whereas the
monitored hydrogeologic years lasted for 307 and 325 days,
respectively. Rvalues of 130 and 117 mm throughout the
hydrogeologic year was estimated for the Mt. Prinzera from
Q
A
and Q
AE
, respectively, whereas at Mt. Zirone Rvalues of
121 and 127 mm were derived from Q
A
and Q
AE
,respective-
ly. In both settings, estimation of Rfrom Q
A
or Q
AE
shows
small differences (13 mm at Mt. Prinzera, corresponding to
the 10.6% of averaged R, and 6 mm for Mt. Zirone, equal to
4.5% of averaged R).
The values of Rare consistent with that estimated from an
annual water budget in the two aquifers (R
wb
;seeESM), when
assuming a much higher infiltration potential at Mt. Zirone
compared to Mt. Prinzera. Such higher infiltration is justified
by a more pronounced stress-release condition (testified by
rock slope deformations and fractures with larger aperture
and higher persistence) and a higher percent of bedrock out-
crop at Mt. Zirone compared to Mt. Prinzera, as discussed in
section S6 of the ESM.
A coefficient of infiltration (C) was estimated for the two
aquifers of Mt. Prinzera and Mt. Zirone corresponding to the
ratio between Rthroughout the monitored hydrogeologic
years (derived by Q
A
or Q
AE
) and the precipitation over the
aquifer catchment during the same time span (P, equal to
1,011 and 632 mm, from Mt. Prinzera and Mt. Zirone,
respectively; see ESM). The estimated Cvalues are 0.13 or
0.12 at Mt. Prinzera, and 0.19 or 0.20 at Mt. Zirone, starting
from Q
A
or Q
AE
, respectively. The higher Cvalues detected
for Mt. Zirone compared to Mt. Prinzera are consistent with
the observed higher reactivity to rainfall events for Mt. Zirone,
suggesting a higher hydraulic conductivity or the occurrence
of faster or preferential recharge pathways compared to Mt.
Prinzera. The hypothesis is also consistent with the formerly
inferred higher infiltration potential compared to Mt. Prinzera.
The values of Cestimated for Mt. Prinzera and Mt. Zirone are
similar to that experimentally derived for Northern Apennine
turbiditic aquifers by various authors, ranging between 0.13
and 0.17 (Gargini et al. 2014; Piccinini et al. 2013;Vincenzi
et al. 2014). Such similarity in terms of hydrodynamic prop-
erties also enhances the idea that the turbiditic units in the
Northern Apennines behave as hard rock aquifers as much
as peridotitic ophiolites.
Major shortcomings of the proposed method for
aquifer recharge estimation
Spring discharge distribution along the hydrogeologic year
The proposed correlation between Q
A
and Q
S
was observed
and validated on spring hydrographs typical of fractured aqui-
fers without significantheterogeneities at the catchment scale,
in a Mediterranean climate. In such settings, the spring
hydrographs are most typically characterized by an overall
high discharge period with several peaks during fall, winter,
and early spring, followed by a generalized decrease of dis-
charge down to base-flow recession in late-spring and sum-
mer. The methodology described in detail in section Analysis
of spring base-flow recession using the Maillet modelis tai-
lored over this type of discharge pattern. A different spring
discharge distribution, e.g. with several maxima and base-
flow recessions per hydrogeologic year, may be expected in
different climates and/or in aquifers with highly heteroge-
neous properties at the scale of the catchment (e.g. karst aqui-
fers). Further investigations are needed to assess whether the
proposed method could be employed on spring discharge
hydrographs different than that described in the preceding.
Shape of the base-flow recession hydrograph
The proposed correlation between Q
A
and Q
S
is driven by the
Maillet model that describes an exponential decay of dis-
charge during the base flow recession. Any deviation from
the exponential decay pattern, e.g. discharge peaks caused
by significant recharge events during the low flow season,
may hamper the identification of a Maillet coefficient αrep-
resentative of the spring behavior thus decreasing the reliabil-
ity of the annual discharge estimate. For example, the relative-
ly poor fit between Q
A
and Q
AE
observed at Mt. Zirone is
likely attributable to the noisy recession hydrographs that
Hydrogeol J
challenged the identification of α, as widely discussed in sec-
tion Prediction of averaged annual flow rates. In the occur-
rence of springs highly reactive to single recharge events, the
issue of noisy hydrographs may be partly mitigated by in-
creasing the frequency of discharge measurements so that
any transitory deviation from the recession trend could be
identified and conveniently managed.
Assumption of steady-state flow at the scale
of the hydrogeologic year
The proposed approach for aquifer recharge estimation
grounds on the assumption of a steady-state condition be-
tween aquifer recharge and spring discharge over the
hydrogeologic year. Such a condition can be considered
broadly valid in relatively small catchments where the main
groundwater flow paths are rather quick, which is often the
case of mountain hard-rock aquifers composed of fractured
permeable materials of limited extent and thickness laying
over an impermeable bedrock. In the case of larger aquifers
where longer residence times must be considered, the correla-
tion between Q
A
and Q
S
cannot be exploited for the estimation
of aquifer recharge.
Conclusions
The empirical correlation proposed by Gargini et al. (2008)
between the average annual discharge of a spring and its aver-
age discharge during base-flow recession was applied to two
ophiolitic aquifer systems with well-defined hydrogeologic
boundaries and well-identified discharge outlets (springs) at
the aquifer-aquitard boundaries. The method provided a reli-
able estimate of average annual discharges starting from few
field measurements in the low flow season, thus confirming the
validity of the correlation for hard rock aquifers in a dry sum-
mer climate, regardless to bedrock lithology. The adequacy of
the Maillet coefficient αto discriminate among recession be-
haviors of springs was tested through a comparison between α
and the slope of the so-called recession plots. The compari-
son proved that the different discharge behaviors inferred using
αare still discernible when analyzing the spring recession
hydrographs with a model different than that of Maillet.
Since the two investigated aquifers are closesystems
with quick groundwater circulation inferable from tempera-
ture and electrical conductivity of the spring water, the aver-
age annual discharge of springs was assumed equal to the
annual aquifer recharge over the spring catchment and used
to estimate coefficients of infiltration for the aquifers which
turned out to be consistent with that of other fractured aquifers
in the same area.
The proposed correlation would significantly reduce the
time and logistic efforts for aquifer recharge estimate in
mountain areas, thus supporting the application of groundwa-
ter budgets and the assessment of climate change effects on
the groundwater resource.
Notwithstanding the overall good predictions obtained at
the Mt. Prinzera and Mt. Zirone aquifers, the proposedmethod
is still affected by a few shortcomings that should be carefully
considered for a broader applicability, i.e. distribution of
spring discharge over the hydrogeologic year, need for an
undisturbedbase-flow recession hydrograph, and the annu-
al steady-state assumption. Further tests are needed to verify
the reliability of the proposed correlation in different hardrock
settings, either in similar climate zones or in regions with
different seasonal variations along the hydrogeologic year
(e.g. in Alpine-like settings where the low flow season is in
winter).
Supplementary Information The online version contains supplementary
material available at https://doi.org/10.1007/s10040-021-02317-z.
Acknowledgements We acknowledge the two anonymous reviewers and
the editor for providing insightful suggestions that improved the quality
of the manuscript.
Funding Open access funding provided by Alma Mater Studiorum -
Università di Bologna within the CRUI-CARE Agreement.
Open Access This article is licensed under a Creative Commons
Attribution 4.0 International License, which permits use, sharing, adap-
tation, distribution and reproduction in any mediumor format, as long as
you give appropriate credit to the original author(s) and the source, pro-
vide a link to the CreativeCommons licence, and indicate if changes were
made. The images or other third party material in this article are included
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licence, visit http://creativecommons.org/licenses/by/4.0/.
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Hydrogeol J
... Quantifying spring discharge, particularly its temporal variations, provides valuable information on both ecological requirements and changes to driving factors that control spring flow. For example, spring discharge rates have been used to estimate groundwater recharge (e.g., Segadelli et al., 2021), the baseflow contribution of springs to streams (e.g., Fournier et al., 1976;Fournier, 1989;Friedman and Norton, 2007), geothermal heat flux (e.g., Fournier et al., 1976;Mariner et al., 1990), and lag times between recharge and changes in spring discharge (e.g., Manga, 1999;Celico et al., 2006). Additionally, knowledge of spring discharge rates provide insight into aquifer characteristics (e.g., permeabilities, vertical fluxes), which are useful for constraining hydrogeological models (e.g., Manga, 1997;Saar and Manga, 2004;Martínez-Santos et al., 2014). ...
... The simplest form of direct flow measurements are timed volumetric measurements where the spring discharge is calculated from the time taken to fill a container of known volume (e.g., Gentry and Burbey, 2004;White et al., 2016;Segadelli et al., 2021). Despite the apparent simplicity of this technique, its application requires a localised discharge point, and can be problematic for springs with diffuse discharge. ...
Article
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Springs sustain groundwater-dependent ecosystems and provide freshwater for human use. Springs often occur because faults modify groundwater flow pathways leading to discharge from aquifers with sufficiently high pressure. This study reviews the key characteristics and physical processes, field investigation techniques, modelling approaches and management strategies for fault-controlled spring systems. Field investigation techniques suitable for quantifying spring discharge and fault characteristics are often restricted by high values of spring ecosystems, requiring mainly non-invasive techniques. Numerical models of fault-controlled spring systems can be divided into local-scale, process-based models that allow the damage zone and fault core to be distinguished, and regional-scale models that usually adopt highly simplified representations of both the fault and the spring. Water resources management relating to fault-controlled spring systems often involves ad hoc applications of trigger levels, even though more sophisticated management strategies are available. Major gaps in the understanding of fault-controlled spring systems create substantial risks of degradation from human activities, arising from limited data and process understanding, and simplified representations in models. Thus, further studies are needed to improve the understanding of hydrogeological processes, including through detailed field studies, physics-based modelling, and by quantifying the effects of groundwater withdrawals on spring discharge.
... In particular, obducted ophiolites exhumed in many Alpine-Himalayan-type orogenic chains usually occur as lithoid blocks of various dimensions contained within argillaceous mélange-type units due to subduction dynamics and mountain building processes [1][2][3][4]. Notably, this multiscale block-in-matrix arrangement strongly impacts the internal and external structural-stratigraphic architecture influencing slope stability, geological hazard, and surficial and groundwater flow [5][6][7]. In this framework, mountain lakes associated with small-scale catchment areas developed atop such ophiolite bodies with a clear structural control, given their close association with topographic lineaments [1,8,9]. ...
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Sedimentary systems developed in small (<1 km2) mountain lacustrine basins represent high-resolution geological archives, able to record subtle climatic and tectonic signatures over historical times. The studied example from the Mt. Ragola ophiolitic massif in the Northern Apennines (Italy) allowed us to better understand the role of the different (neo)tectonic and climatic events on the development and distribution of large landslides and lakes/peat bogs during the last 10 kyrs. Implementing a multidisciplinary approach that includes detailed acquisition of bedrock, geomorphological, topographic, and geophysical data, we detected and mapped ridge splitting, trenches, closed depressions, double ridges, and counterscarps. These morphostructures are interpreted as relevant factors influencing the distribution of sediments in historical times by shifting the position of the local equilibrium point (i.e., erosion vs. deposition) and have been correlated to a combination of climatic (i.e., increased flood events) and tectonic (i.e., spatial–temporal clustering of seismic shocks) forcing, starting from the demise of the Little Ice Age in the mid-19th century to the present-day situation. This approach allowed us to better describe the current changes in the hydrologic cycle, reaching beyond the limits of historical instrumental data. Furthermore, allowing the recognition and dating of recent tectonic vs. gravitational deformations, it also constitutes an integrative method for assessing the local geological hazard.
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Springs represent relevant habitats which support high levels of biodiversity and productivity, providing refugia to both plants and animals together with essential ecosystem services. However, springs are often overlooked or even destroyed by human activity. Locating, inventorying, and monitoring springs is, therefore, becoming of increasing importance. This study aims at developing a multidisciplinary approach to detect ephemeral springs, which can only be discovered by hydrogeological surveys when discharge occurs. We suggest potential cooperation between hydrogeologists and botanists based on the use of a plant species as an indicator of the occurrence of ephemeral springs fed by ophiolitic perched groundwater aquifers. In this study, the grass Molinia arundinacea was used as a bioindicator, observed in periods when there was no discharge and whose occurrence on ophiolite bodies was revealed by previous studies in the northern Apennines (Italy). A total of twenty ophiolitic bodies were explored and grassland stands including Molinia populations were discovered in 86 springs (15 reported for the first time). Detailed geomorphological and hydrogeological sampling was also performed in ten springs, recording the occupancy area, cover and functional traits of Molinia at two permanent and eight ephemeral springs and along their streambeds. Molinia not only colonised the spring outlets, but also occurred along the streambeds fed by ephemeral springs, with a higher occupancy area where the rocky outcrops were covered by detrital deposits and at the base of the morphological incision. Additionally, the cover of Molina populations was correlated with the average water discharge, with the highest functional trait values found in locations with high soil moisture. Results confirmed that while Molinia performs best on permanently moist soils, it is also able to grow on soils with a fluctuating water-table or even in dry conditions, thus representing an excellent indicator of springs fed by temporary perched aquifers.
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A few hydrogeological studies have been carried out worldwide in peridotite aquifer systems, despite their wide distribution. The ophiolites are one of the main groundwater reservoir within the northern Apennines (Italy). This paper suggests the graphical solution to set the hydrogeological map of heterogeneous, multi-layered ophiolitic aquifers mapped on large scale (1:1600). The site investigation area is an ophiolite outcrop of the External Ligurian of the northern Apennines: the Mountain Prinzera rock complex area (44°38′30″N, 10°5′E; Parma Province, Emilia-Romagna Region). The hydrogeological characteristics of the tested aquifer system do not allow setting a hydrogeological map by applying usual graphical approaches. The hydrogeological map in such complex aquifer systems will show the classic hydrogeological data but must put in evidence above all (i) the main heterogeneities of the system, from the hydraulic point of view and (ii) the modifications of groundwater scenarios and pathways over time. The hydrogeological database of Mt Prinzera aquifer was managed in ESRI ArcGIS 10.0 software.
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The aim of this study was to investigate natural and anthropogenic processes governing the chemical composition of alkaline groundwater within a fractured rock (ophiolitic mélange) aquifer underlying a seasonally inhabited headwater area in the Aladağlar Range (Adana, Turkey). In this aquifer, spatiotemporal patterns of groundwater flow and chemistry were investigated during dry (October 2011) and wet (May 2012) seasons utilizing 25 shallow hand-dug wells. In addition, representative samples of snow, rock, and soil were collected and analyzed to constrain the PHREEQC inverse geochemical models used for simulating water-rock interaction (WRI) processes. Hydrochemistry of the aquifer shows a strong interseasonal variability where Mg–HCO 3 and Mg–Ca–HCO 3 water types are prevalent, reflecting the influence of ophiolitic and carbonate rocks on local groundwater chemistry. R-mode factor analysis of hydrochemical data hints at geochemical processes taking place in the groundwater system, that is, WRI involving Ca- and Si-bearing phases; WRI involving amorphous oxyhydroxides and clay minerals; WRI involving Mg-bearing phases; and atmospheric/anthropogenic inputs. Results from the PHREEQC modeling suggested that hydrogeochemical evolution is governed by weathering of primary minerals (calcite, chrysotile, forsterite, and chromite), precipitation of secondary minerals (dolomite, quartz, clinochlore, and Fe/Cr oxides), atmospheric/anthropogenic inputs (halite), and seasonal dilution from recharge.
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Only meters below our feet, shallow aquifers serve as sustainable energy source and provide freshwater storage and ecological habitats. All of these aspects are crucially impacted by the thermal regime of the subsurface. Due to the limited accessibility of aquifers however, temperature measurements are scarce. Most commonly, shallow groundwater temperatures are approximated by adding an offset to annual mean surface air temperatures. Yet, the value of this offset is not well defined, often arbitrarily set, and rarely validated. Here, we propose the usage of satellite-derived land surface temperatures instead of surface air temperatures. 2 548 measurement points in 29 countries are compiled, revealing characteristic trends in the offset between shallow groundwater temperatures and land surface temperatures. Here it is shown that evapotranspiration and snow cover impact on this offset globally, through latent heat flow and insulation. Considering these two processes only, global shallow groundwater temperatures are estimated in a resolution of approximately 1 km × 1 km. When comparing these estimated groundwater temperatures with measured ones a coefficient of determination of 0.95 and a root mean square error of 1.4 K is found.
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The main aim of this study is the experimental analysis of the hydrogeological behaviour of the Mt. Prinzera ultramafic massif in the northern Apennines, Italy. The analyzed multidisciplinary database has been acquired through: (i) Geologic and structural survey; (ii) Geomorphologic survey; (iii) Hydrogeological monitoring; (iv) Physico-chemical analyses; (v) Isotopic analyses. The ultramafic medium is made of several lithological units, tectonically overlapped. Between them, a low-permeability, discontinuous unit has been identified. This unit behaves as an aquitard and causes a perched groundwater to temporary flow within the upper medium, close to the surface. This perched groundwater flows out along several structurally-controlled depressions, and then several high-altitude temporary springs can be observed during recharge, together with several perennial basal (i.e. low-altitude) springs, caused by the compartmentalisation of the system due to high-angle tectonic discontinuities. http://dx.doi.org/10.1002/hyp.11090
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The current study employs geochemical and isotopic tools to understand hydrochemical and recharge processes characterizing ophiolite aquifer in North Oman in conjunction with the Hajar Super Group (HSG) aquifer. A total of 57 samples were analyzed for major ions and stable isotopes 2H and 18O. The geochemical composition of groundwater indicates that water–rock interaction and mixing are the main processes controlling groundwater chemistry. Groundwater in the HSG is characterized by carbonate minerals dissolution contrary to the groundwater in the ophiolites where silicates dissolution dominates. This results in differences in the groundwater chemical composition in the two systems. Isotopic characteristics of precipitation collected during the study period indicate two main moisture sources from the Indian Ocean and the Mediterranean Sea. Groundwater δ2H and δ18O values suggest two recharge sources to the ophiolite aquifer: lateral flow from the HSG and direct infiltration. Recharge from direct infiltration in the highlands, which is depleted in δ2H and δ18O, retains the same isotopic signature of precipitation, whereas that in the low land substantially reflects an evaporation effect.
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The Cretaceous Chalk aquifer is the most important in the UK for the provision of water to public supply and agriculture. The Chalk has both matrix and fracture porosity and is thus best considered as a dual porosity aquifer system. Although the matrix porosity is large, typically around 0.35 in the study area of East Yorkshire, UK (ESI, 2010), pore diameters are typically very small, and the water contained in them is virtually immobile. The high permeability fracture network is responsible for the ability of water to drain; spatial variations in fracture network properties mean conventional approaches to aquifer characterization such as borehole pumping tests are of limited utility. Hence this study attempts to better understand the flow system and characterise aquifer properties from the recession response seen at springs during the spring/summer period when recharge is minimal. This approach has the advantage that spring hydrographs represent the sum of the response from entire catchments. This paper reports numerical modeling for simulating aquifer and spring responses during hydrological recession. Firstly, available geological and hydrogeological information for the study area was used to develop hydrogeological conceptual models. Four different numerical models have been constructed representing four possible scenarios that could represent the aquifer in the selected area. These are: single reservoir aquifer, double reservoir aquifer, single reservoir aquifer with highly permeable vertical zone intersecting the spring location and single reservoir aquifer containing tunnel shaped highly permeable zone at the spring elevation respectively. The sensitivity of spring recession response to various external and internal parameter values was investigated, to understand relations between spring recession, hydrological inputs (recharge) and aquifer structure. Spring hydrographs from the real aquifer were compared with the hydrographs generated from models, in order to estimate aquifer properties. The work aims to identify the utility of spring hydrographs in eliciting aquifer permeability structure, as well as identifying the conceptual scenario which best represents the Chalk Aquifer in East Yorkshire, UK.
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Extensive in-depth research is required for the implementation of natural tracer approaches to hydrogeological investigation to be feasible in mountainous regions. This review considers the application of hydrochemical and biotic parameters in mountain regions over the past few decades with particular reference to the Austrian Alps, as an example for alpine-type mountain belts. A brief introduction to Austria’s hydrogeological arrangement is given to show the significance of fractured hard-rock aquifers for hydrogeological science as well as for water supply purposes. A literature search showed that research concerning fractured hard-rock aquifers in Austria is clearly underrepresented to date, especially when taking the abundance of this aquifer type and the significance of this topic into consideration. The application of abiotic natural tracers (hydrochemical and isotope parameters) is discussed generally and by means of examples from the Austrian Alps. The potential of biotic tracers (microbiota and meiofauna) is elucidated. It is shown that the meiofauna approach to investigating fractured aquifers has not yet been applied in the reviewed region, nor worldwide. Two examples of new approaches in mountainous fractured aquifers are introduced: (1) use of CO2 partial pressure and calcite saturation of spring water to reconstruct catchments and flow dynamics (abiotic approach), and, (2) consideration of hard-rock aquifers as habitats to reconstruct aquifer conditions (biotic approach).
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Stable isotopes of H and O are the integral parts of water molecule and serve as ideal tracers to understand the recharge processes in groundwater. Hence, a study has been conducted in hard rock aquifers of Madurai District of Tamilnadu to identify the recharge processes using stable isotopes. A total of 54 groundwater samples were collected representing the entire district from various lithounits during post monsoon. Samples were analysed for pH, EC, Ca2+, Mg2+, Na+, K+, Cl− HCO3−, SO42−, PO43−, H4SiO4, F−, δ18O and δD. Cl− and HCO3− were the dominant ions in groundwater samples. Average values of Cl− and HCO3− ranged from 247 and 244 mg/L in fissile hornblende biotite gneiss, 262 and 268 mg/L in Charnockite, 75 and 185 mg/L in quartzite, 323 and 305 mg/L in granite, 524 and 253 mg/L in floodplain alluvium rock types. Geochemical signatures of groundwater were used to identify the chemical processes that control hydrogeochemistry. Interpretation of δ18O and δD indicates recharge from the meteoric water in charnockite, quartzite, granite and some samples of fissile hornblende biotite gneiss. It is also inferred that recharge take place from evaporated water in floodplain alluvium and fissile hornblende biotite gneiss.
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The spatial distribution of precipitation, temperature and climate indices has been represented in the Emilia-Romagna region with an aim to characterize its climate. The Johansson Continentality Index, the Kerner Oceanity Index, the De Martonne Aridity Index and the Pinna Combinative Index are the climate indices used in the present report based on data from 21 meteorological stations located in Emilia-Romagna and its surroundings. The analysed climate data are from the 1961–1990 period. Monthly precipitation and temperature diagrams from the Borgo Panigale station were computed for use in agricultural fields, hydrological sciences and climatology applications. Based on the findings of the climate analysis, the spatial variation of climate indices was estimated using the Kriging ordinary function, available in ArcGIS 10.2.2 environment.