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water
Article
Observations and Prediction of Recovered Quality of
Desalinated Seawater in the Strategic ASR Project in
Liwa, Abu Dhabi
Pieter J. Stuyfzand 1, 2, *, Ebel Smidt 3,4, Koen G. Zuurbier 1, Niels Hartog 1,5
and Mohamed A. Dawoud 6
1KWR Watercycle Research Institute, 3430 BB Nieuwegein, The Netherlands;
koen.zuurbier@kwrwater.nl (K.G.Z.); niels.hartog@kwrwater.nl (N.H.)
2Faculty of Civil Engineering and Geosciences, Delft University of Technology, 2628 CN Delft,
The Netherlands
3Waterfocus, 3981 EB Bunnik, The Netherlands; ebel.smidt@waterfocus.nu or esmidt@sgmediation.nl
4SG Consultancy and Mediation Ltd, 5221 GB Engelen, The Netherlands
5Faculty of Geosciences, Utrecht University, 3508 TA Utrecht, The Netherlands
6Environment Agency Abu Dhabi, PO Box 45553, Al Mamoura Building (A), Muroor Road, Abu Dhabi,
United Arab Emirates; mdawoud@ead.ae
*Correspondence: pieter.stuyfzand@kwrwater.nl; Tel.: +31-6-10945021
Academic Editor: Maria Filomena Camões
Received: 14 January 2017; Accepted: 21 February 2017; Published: 1 March 2017
Abstract:
To be able to overcome water shortages, Abu Dhabi Emirate started an Aquifer Storage and
Recovery (ASR) project with desalinated seawater (DSW) as source water near Liwa. It is the largest
DSW-ASR project in the world (stored volume ~10 Mm
3
/year), and should recover potable water
for direct use. DSW is infiltrated into a desert dune sand aquifer using “sand-covered gravel-bed”
recharge basins. In this study, we evaluate the hydrogeological and hydrogeochemical stratification
of the (sub)oxic target aquifer, and water quality changes of DSW during trial infiltration runs.
We predict water quality changes of DSW after 824 d of infiltration, during 90 d of intensive recovery
(67% recovered) without storage (scenario A), as well as after 10 years of storage (scenario B, with
significant bubble drift). Monitoring of preceding trials revealed a lack of redox reactions; little
carbonate dissolution and Ca/Na exchange; much SiO
2
dissolution; a strong mobilization of natural
AsO
43−
, B, Ba, F, CrO
42−
, Mo, Sr and V from the (sub)oxic aquifer; and immobilization of PO
4
, Al, Cu,
Fe and Ni from DSW. The Easy-Leacher model was applied in forward and reverse mode including
lateral bubble drift, to predict water quality of the recovered water. We show that hydrogeochemical
modeling of a complex ASR-system can be relatively easy and straightforward, if aquifer reactivity is
low and redox reactions can be ignored. The pilot observations and modeling results demonstrate
that in scenario A recovered water quality still complies with Abu Dhabi’s drinking water standards
(even up to 85% recovery). For scenario B, however, the recovery efficiency declines to 60% after
which various drinking water standards are exceeded, especially the one for chromium.
Keywords:
Aquifer Storage and Recovery (ASR); hydrochemistry; desalinated seawater; chromate;
trace elements; transport modeling; break-through curve; Abu Dhabi; recovery efficiency
1. Introduction
Water scarcity has driven many countries in arid zones, such as the Middle East and Abu Dhabi
in particular, to desalinate large volumes of seawater for fresh water supply [
1
]. Episodic problems
with seawater quality due to, e.g., harmful algae blooms [
2
,
3
] and oil spills, energy supply and fear of
Water 2017,9, 177; doi:10.3390/w9030177 www.mdpi.com/journal/water
Water 2017,9, 177 2 of 25
war or terrorism have nurtured the urgent need to store desalinated seawater in the underground for
later use in case of a calamity [4–7].
In 2001, Abu Dhabi started its pioneer projects for developing strategic fresh water resources to
face any emergency condition using the Aquifer Storage and Recovery (ASR) technique by infiltrating
the surplus of desalinated water into the groundwater aquifer system. One of these projects is the
strategic fresh water reserve project at Liwa. The project passed with success through the phases of
first a feasibility study and subsequently a pilot study in 2003–2004 [
8
]. In this pilot, desalinated water
was infiltrated in a dune sand aquifer system using injection wells as well as an underground recharge
basin. The basin performed better than the ASR wells, and was therefore selected for implementation
in the construction phase.
Construction of the full ASR plant started in 2009, and was finalized in Winter 2016. Large scale
infiltration started in May 2015. The project aim is to infiltrate 26,500 m
3
/d (=9.7 Mm
3
/year) of
desalinated water with Total Dissolved Solids (TDS) < 250 ppm for 824 d, in order to be able to cover
an emergency water demand for 90 d with a recovery rate of 170,280 m
3
/d (=15.5 Mm
3
/90 d) and a
TDS of ~400 ppm.
After extensive studies on the ASR recovery efficiency (the part of injected water that can be
recovered with a satisfying quality), impact on groundwater tables and salinity distribution, and
quality of the water to be recovered [
8
–
12
], questions persisted about a potential water quality
deterioration during recovery after a prolonged storage period, with emphasis on critical Cr(VI)
behavior. This related to the planned omission of a post-treatment of the recovered water, which
was to be distributed directly without any treatment, as drinking water to Abu Dhabi City, trusting
that the UAE drinking water standards [
13
] would not be exceeded. It was feared, however, in a late
stage, that post-treatment would be needed requiring a costly facility, for two reasons. Firstly, the
native groundwater in the project area contains elevated concentrations of, among others, TDS, Cl,
SO
4
, F, Na and Cr (as CrO
42−
), exceeding the standards, suggesting that their mobilization would
deteriorate water quality during prolonged storage. Secondly, water stored in ASR targeted aquifers
generally displays significant quality changes due to redox reactions, cation exchange, desorption and
dissolution of mineral phases [14–22].
In order to assess the impact of aquifer storage on the recovered water quality, we first investigated
the hydrogeological, geochemical and hydrochemical stratification of the targeted aquifer system,
based on available data [
8
–
12
]. We conducted a sampling campaign in the period of 3–7 August 2014 to
check potential bias in the existing hydrochemical data set, and to obtain data on chromium speciation
(Cr(III) versus Cr(VI)). Finally, we predicted the future quality of the recovered DSW after 27 months
of infiltration, during 90 d of intensive recovery without storage, as well as after 10 years of storage
(with significant lateral bubble migration).
This paper is based on two extensive reports [
23
,
24
]. It shows the peculiar characteristics of an
eolian-fluvial sand (stone) aquifer system in a desert environment, the unique water quality changes
during an ASR pilot including a six-year storage phase, and a particular modeling approach. In this
approach, observations on retardation and leaching are combined with a strong schematization of the
complex ASR system, flow, and processes.
2. Materials and Methods
2.1. Field Site and Liwa ASR System
The project area (Figures 1–3) is situated in a remote dune sand area ~150 km southwest of
Abu Dhabi City, some 25 km north of the Liwa Crescent (Al Qafa area). Its hydrological position is on
or close to the phreatic groundwater divide of one of the few fresh groundwater reserves (Figure 2).
The altitude of land surface varies between 120 and 160 m ASL (Above Sea Level).
The pilot area is ~15 km to the east of the final Liwa ASR plant (Figure 3). The plant is composed of
three underground basins A–C (Figure 3), each with 105 surrounding recovery wells, and 57 monitoring
Water 2017,9, 177 3 of 25
wells in total. The circular recharge basins A, B and C, 50 m in diameter, are composed of a flat
gravel-body covered by geo-textile and a sand layer on top, fed by horizontal reverse drains.
The ASR plant is thus not a normal ASR system, which is exclusively composed of wells performing
two tasks: infiltrate and recover [20].
2.2. The Pilot
The first operation run of the pilot started on 1 October 2003 and lasted until December 2004.
DSW was infiltrated via a series of 5 ASR wells (not discussed further) and a recharge basin recovery
scheme consisting of a covered gravel-body with reverse drains in it, 4 recovery wells and tens of
observation wells around. DSW was infiltrated via the basin for 250 d at ~250 m
3
/h, and after 48 d
of storage part of the stored volume was recovered in 70 d at ~250 m
3
/h. Intensive monitoring of
water quality yielded important insights in the ambient hydrochemical stratification and water quality
changes during infiltration, stand-still and recovery [8].
A second infiltration run via the basin took place in 2008, but water quality monitoring was not
undertaken and DSW was not pumped out. This offered the possibility to sample, in August 2014,
6-year-old DSW from the aquifer.
Water 2017, 9, 177 3 of 25
The ASR plant is thus not a normal ASR system, which is exclusively composed of wells
performing two tasks: infiltrate and recover [20].
2.2. The Pilot
The first operation run of the pilot started on 1 October 2003 and lasted until December 2004.
DSW was infiltrated via a series of 5 ASR wells (not discussed further) and a recharge basin recovery
scheme consisting of a covered gravel-body with reverse drains in it, 4 recovery wells and tens of
observation wells around. DSW was infiltrated via the basin for 250 d at ~250 m
3
/h, and after 48 d of
storage part of the stored volume was recovered in 70 d at ~250 m
3
/h. Intensive monitoring of water
quality yielded important insights in the ambient hydrochemical stratification and water quality
changes during infiltration, stand-still and recovery [8].
A second infiltration run via the basin took place in 2008, but water quality monitoring was not
undertaken and DSW was not pumped out. This offered the possibility to sample, in August 2014, 6-
year-old DSW from the aquifer.
Figure 1. Location of the Liwa Strategic Water Storage and Recovery (SWSR) Project: the blue dot on
the red line. From GTZ-Dornier (with permission): [10].
Figure 2. Cross section along red line in Figure 1, showing groundwater salinity distribution and
position of groundwater divide where SWSR project. From GTZ-Dornier (with permission): [10].
Figure 1.
Location of the Liwa Strategic Water Storage and Recovery (SWSR) Project: the blue dot on
the red line. From GTZ-Dornier (with permission): [10].
Water 2017, 9, 177 3 of 25
The ASR plant is thus not a normal ASR system, which is exclusively composed of wells
performing two tasks: infiltrate and recover [20].
2.2. The Pilot
The first operation run of the pilot started on 1 October 2003 and lasted until December 2004.
DSW was infiltrated via a series of 5 ASR wells (not discussed further) and a recharge basin recovery
scheme consisting of a covered gravel-body with reverse drains in it, 4 recovery wells and tens of
observation wells around. DSW was infiltrated via the basin for 250 d at ~250 m
3
/h, and after 48 d of
storage part of the stored volume was recovered in 70 d at ~250 m
3
/h. Intensive monitoring of water
quality yielded important insights in the ambient hydrochemical stratification and water quality
changes during infiltration, stand-still and recovery [8].
A second infiltration run via the basin took place in 2008, but water quality monitoring was not
undertaken and DSW was not pumped out. This offered the possibility to sample, in August 2014, 6-
year-old DSW from the aquifer.
Figure 1. Location of the Liwa Strategic Water Storage and Recovery (SWSR) Project: the blue dot on
the red line. From GTZ-Dornier (with permission): [10].
Figure 2. Cross section along red line in Figure 1, showing groundwater salinity distribution and
position of groundwater divide where SWSR project. From GTZ-Dornier (with permission): [10].
Figure 2.
Cross section along red line in Figure 1, showing groundwater salinity distribution and
position of groundwater divide where SWSR project. From GTZ-Dornier (with permission): [10].
Water 2017,9, 177 4 of 25
Water 2017, 9, 177 4 of 25
Figure 3. Detailed location map, showing the ASR pilot area and Liwa’s SWSR well field clusters A,
B and C, each surrounding a large circular underground recharge basin. Slightly modified from: GTZ-
Dornier (with permission) [9].
2.3. Quantitative Description of the Break-through Curve
The first infiltration run of the pilot yielded valuable insight into the break-through curve (BTC)
of nearly all main constituents and trace elements. These observed BTCs are characterized by 3
parameters: pore volume, retardation or leach factor and (semi)permanent concentration change
(Figure 4).
The dimensionless parameter called “pore volume” (PV) forms the time axis of water quality
observations and model predictions:
=
(1)
where t
INF
= total infiltration period [d]; and t
50
= the observed 50% breakthrough time of conservative
tracer or the calculated travel time via Equation (4).
One PV means that the whole aquifer, from infiltration point to the monitoring or recovery well,
has been flushed with the infiltration water exactly one time. Retardation factors R or leach factors L
can then be simply deduced from concentration plots against PVs (Figure 4).
Sorbing and oxidizing solutes as well as desorbing and dissolving solutes are retarded during
aquifer passage compared with conservative solutes. In the latter case, raised concentrations drop to
the influent level long after passage of the conservative chloride front. These delays are quantified
for solute i by, respectively, the well-known retardation factor R
i
, and the less well known leach factor
L
i
[25]:
=
=1+1
(2)
=
=1+1
=1+
1
(3)
Figure 3.
Detailed location map, showing the ASR pilot area and Liwa’s SWSR well field clusters
A, B and C, each surrounding a large circular underground recharge basin. Slightly modified from:
GTZ-Dornier (with permission) [9].
2.3. Quantitative Description of the Break-through Curve
The first infiltration run of the pilot yielded valuable insight into the break-through curve
(BTC) of nearly all main constituents and trace elements. These observed BTCs are characterized by
3 parameters: pore volume, retardation or leach factor and (semi)permanent concentration change
(Figure 4).
The dimensionless parameter called “pore volume” (PV) forms the time axis of water quality
observations and model predictions:
PV =tINF
t50
(1)
where t
INF
= total infiltration period [d]; and t
50
= the observed 50% breakthrough time of conservative
tracer or the calculated travel time via Equation (4).
One PV means that the whole aquifer, from infiltration point to the monitoring or recovery well,
has been flushed with the infiltration water exactly one time. Retardation factors R or leach factors L
can then be simply deduced from concentration plots against PVs (Figure 4).
Sorbing and oxidizing solutes as well as desorbing and dissolving solutes are retarded during
aquifer passage compared with conservative solutes. In the latter case, raised concentrations drop to
the influent level long after passage of the conservative chloride front. These delays are quantified
for solute iby, respectively, the well-known retardation factor R
i
, and the less well known leach
factor Li[25]:
Ri=ti
t50
=1+ρS(1−n)Kd
n(2)
Li=ti
t50
=1+ρS(1−n)(solid)
n(reac)rR
=1+ρS(1−n)(solid)
n(prod)rP
(3)
Water 2017,9, 177 5 of 25
where t
i
= time required for
≥
90% break-through (R
i
) or
≥
90% leaching (L
i
) or till equilibrium is
attained with the infiltration water [days];
ρs
= density of solids of porous medium [kg/L]; n= porosity
[L/L]; K
d
= distribution coefficient (slope of the linear portion of the adsorption isotherm) [L/kg];
(solid) = content of reactive phase in aquifer [mmol/kg dry weight]; (reac) = concentration of reactant in
flushing fluid [mmol/L]; (prod) = concentration of reaction product in fluid during leaching [mmol/L];
r
R
= reaction coefficient, i.e., the number of mmoles of solid phase which is leached by 1 mmole of
reactant [-]; and rP= reaction coefficient related to (prod).
For practical reasons, t
i
is set at
≥
90% not at 100%. If for some reason, the BTC shows a partial
breakthrough due to a prolonged phase of continued partial immobilization or mobilization, so the
additional parameter
∆
C is needed to describe the BTC (Figure 4). Equations (2) and (3) hold for a
stationary retardation or leaching process, with a homogeneously distributed reactive phase in the
aquifer. Of course, (reac) or (prod) should have no other sinks or sources, unless these can be properly
accounted for.
Water 2017, 9, 177 5 of 25
where t
i
= time required for ≥90% break-through (R
i
) or ≥90% leaching (L
i
) or till equilibrium is
attained with the infiltration water [days]; ρ
s
= density of solids of porous medium [kg/L]; n = porosity
[L/L]; K
d
= distribution coefficient (slope of the linear portion of the adsorption isotherm) [L/kg]; (solid)
= content of reactive phase in aquifer [mmol/kg dry weight]; (reac) = concentration of reactant in
flushing fluid [mmol/L]; (prod) = concentration of reaction product in fluid during leaching [mmol/L];
r
R
= reaction coefficient, i.e., the number of mmoles of solid phase which is leached by 1 mmole of
reactant [-]; and r
P
= reaction coefficient related to (prod).
For practical reasons, t
i
is set at ≥90% not at 100%. If for some reason, the BTC shows a partial
breakthrough due to a prolonged phase of continued partial immobilization or mobilization, so the
additional parameter ΔC is needed to describe the BTC (Figure 4). Equations (2) and (3) hold for a
stationary retardation or leaching process, with a homogeneously distributed reactive phase in the
aquifer. Of course, (reac) or (prod) should have no other sinks or sources, unless these can be properly
accounted for.
(A) (B)
Figure 4. Characterization of the breakthrough of a compound dissolved in fluid B (concentration C
B
),
which displaces fluid A (concentration C
A
), in terms of travel time (t
50
) and 90% break-through or
leach times (t
i
; t
i
3, t
i
4 = ti for curve 3 and 4, respectively), the dimensionless parameter PV (pore
volumes flushed) and the (semi)permanent concentration change (ΔC), the maximum concentration
(C
max
) or minimum concentration (C
min
) after full break-through or leaching. Line 1 = conservative
tracer (R = L = 1) without dispersion; Curve 2 = as 1, however, with dispersion; Curve 3 = compound
retarded by sorption or leaching (R = L = 4); Curve 4 = compound retarded by ad- or desorption (R =
L = 5), with continued removal c.q. addition. (A) (C
B
> C
A
); and (B) (C
B
< C
A
).
2.4. Lithological and Geochemical Stratification
The aquifer system on well fields A, B and C could be schematized into a succession of 14 (sub)
horizontal layers in between ground surface and 40 m below sea level [23], based on all drilling logs
(>372), geophysical logs (including the eccentered wireline NMR logging of permeability and
porosity), pumping tests, infiltration pilot tests and fluid flow logging, as presented by [9–12]. For
modeling purposes, the 14 layers were aggregated into 6 main aquifer layers (a–f in Figure 5), of
which the very low permeability aquitard f needs less consideration.
Figure 4.
Characterization of the breakthrough of a compound dissolved in fluid B (concentration C
B
),
which displaces fluid A (concentration C
A
), in terms of travel time (t
50
) and 90% break-through or leach
times (t
i
;t
i
3, t
i
4 = ti for curve 3 and 4, respectively), the dimensionless parameter PV (pore volumes
flushed) and the (semi)permanent concentration change (
∆
C), the maximum concentration (C
max
)
or minimum concentration (C
min
) after full break-through or leaching. Line 1 = conservative tracer
(R = L = 1) without dispersion; Curve 2 = as 1, however, with dispersion; Curve 3 = compound retarded
by sorption or leaching (R = L = 4); Curve 4 = compound retarded by ad- or desorption (R = L = 5),
with continued removal c.q. addition. (A) (CB> CA); and (B) (CB< CA).
2.4. Lithological and Geochemical Stratification
The aquifer system on well fields A, B and C could be schematized into a succession of 14 (sub)
horizontal layers in between ground surface and 40 m below sea level [
23
], based on all drilling logs
(>372), geophysical logs (including the eccentered wireline NMR logging of permeability and porosity),
pumping tests, infiltration pilot tests and fluid flow logging, as presented by [
9
–
12
]. For modeling
purposes, the 14 layers were aggregated into 6 main aquifer layers (a–f in Figure 5), of which the very
low permeability aquitard f needs less consideration.
Water 2017,9, 177 6 of 25
Water 2017, 9, 177 6 of 25
Figure 5. Schematic of each ASR well field (A, B or C) in the Strategic Water Storage and Recovery
project in Liwa, with the planned ASR cycling scheme for each well field. Q1–Q7 = annular circle
numbers 1–7 with 15 recovery wells each, surrounding the central infiltration basin. 1 = buried basin;
2 = unsaturated flow of infiltrated DSW; 3 = groundwater table during infiltration; 4 = groundwater
table prior to recharge. a–f = aggregation of layers 1–14. d = aquitard 1, f = aquitard 2. Each well is
supposed to pump from aquifer layers a, b and c in proportion to their transmissivity.
The mean geochemical composition of layers a–f was calculated from the geochemical data of 4
deep core drillings, one in each well field and one in the middle of well fields A, B and C. The data
were derived from [12], containing the following information: Sample description with photographs,
petrographic analysis and mineralogical counting by petrological photomicroscopic examination of
a thin section impregnated with fluorescent resin, XRD analysis, porosimetric analysis, chemical
analysis of main constituents (including LOI and Acid Solubility), chemical analysis of heavy metals
(probably in nitric acid; no details given), and particle size distribution (by sieving).
The digital data of all 41 samples were used to calculate mean values for aquifer layers a–f, and
to quantify the content of selected minerals by petrochemical calculations [23]. Petrochemical
calculations were needed to correct specific data for water losses (loss on ignition), to calculate the
cation exchange capacity (CEC) and to derive the mineral content from data on elements that are
present in more than one mineral.
2.5. Hydrochemical Analyses in Period 2003–2013
Samples were taken from practically all recovery and monitoring wells, in both the pilot area
and well fields A, B and C. The analyses include data on gases (O2, residual Cl2), turbidity, color,
temperature, pH, EC, ORP (Oxidation Reduction Potential, Eh), main anions (Cl, SO4, S, HCO3, CO3,
NO3, NO2, PO4, and F), main cations (Na, K, Ca, Mg, NH4, Fe, and Mn), SiO2, TOC (Total Organic
Carbon), CN, selected trace elements (Ag, Al, As, B, Ba, Br, Cd, Cr, Cu, Hg, Mo, Ni, Pb, Sb, Se, Sr, V
and Zn), and the stable isotopes 2H and 18O. Most samples were filtered in the field, and all
concentrations (TOC excluded) refer to total dissolved concentrations, thus without (further)
speciation. Microbial parameters and organic micropollutants were analyzed but showed negligible
concentration levels.
Samples of the ambient groundwater were taken in the pilot area in 2003, and within and around
well fields A, B and C in 2011–2013. Analytical data of DSW samples prior to infiltration, during and
after aquifer passage were exclusively available from the pilot. All data (obtained from [9–12] and
Q1 Q2 Kh
m/d
2
dune sand
TDS
3v
500
600
bsand(stone)
700
900
sand(stone)
1,200
dmud(stone) 1
2,000
5,500 esand(stone) with
mud(stone)
12,500 mg/L
fdolomite + gypsum 0.5
500
Buried basi n Q3 Q4 Q5 Q6 Q7
AQUIFER 1
130
120
110
4
140 1
Altitude [m ASL]
100 a
90 30
80
2070 c
60
10
50
5
AQUIFER 2
40
30
20
10
0
-10
250
-20
0 25 50 75 100 125 150 175 200 225
Radial d istance from center o f buried basin [m]
TDS =
100 mg/L
Total Infiltration Mm
3
/period 8.736
Infiltration period days 824
Scen. A: no storage year 0
Scen. B : with storage year 10
Total Recovery Mm
3
/period 5.854
Recovery period days 90
Recovery Efficiency % 67.0
Figure 5.
Schematic of each ASR well field (A, B or C) in the Strategic Water Storage and Recovery
project in Liwa, with the planned ASR cycling scheme for each well field. Q1–Q7 = annular circle
numbers 1–7 with 15 recovery wells each, surrounding the central infiltration basin. 1 = buried basin;
2 = unsaturated flow of infiltrated DSW; 3 = groundwater table during infiltration; 4 = groundwater
table prior to recharge. a–f = aggregation of layers 1–14. d = aquitard 1, f = aquitard 2. Each well is
supposed to pump from aquifer layers a, b and c in proportion to their transmissivity.
The mean geochemical composition of layers a–f was calculated from the geochemical data of
4 deep core drillings, one in each well field and one in the middle of well fields A, B and C. The data
were derived from [12], containing the following information: Sample description with photographs,
petrographic analysis and mineralogical counting by petrological photomicroscopic examination of a
thin section impregnated with fluorescent resin, XRD analysis, porosimetric analysis, chemical analysis
of main constituents (including LOI and Acid Solubility), chemical analysis of heavy metals (probably
in nitric acid; no details given), and particle size distribution (by sieving).
The digital data of all 41 samples were used to calculate mean values for aquifer layers a–f, and to
quantify the content of selected minerals by petrochemical calculations [
23
]. Petrochemical calculations
were needed to correct specific data for water losses (loss on ignition), to calculate the cation exchange
capacity (CEC) and to derive the mineral content from data on elements that are present in more than
one mineral.
2.5. Hydrochemical Analyses in Period 2003–2013
Samples were taken from practically all recovery and monitoring wells, in both the pilot area
and well fields A, B and C. The analyses include data on gases (O
2
, residual Cl
2
), turbidity, color,
temperature, pH, EC, ORP (Oxidation Reduction Potential, Eh), main anions (Cl, SO4, S, HCO3, CO3,
NO
3
, NO
2
, PO
4
, and F), main cations (Na, K, Ca, Mg, NH
4
, Fe, and Mn), SiO
2
, TOC (Total Organic
Carbon), CN, selected trace elements (Ag, Al, As, B, Ba, Br, Cd, Cr, Cu, Hg, Mo, Ni, Pb, Sb, Se, Sr, V and
Zn), and the stable isotopes
2
H and
18
O. Most samples were filtered in the field, and all concentrations
(TOC excluded) refer to total dissolved concentrations, thus without (further) speciation. Microbial
parameters and organic micropollutants were analyzed but showed negligible concentration levels.
Samples of the ambient groundwater were taken in the pilot area in 2003, and within and around
well fields A, B and C in 2011–2013. Analytical data of DSW samples prior to infiltration, during and
Water 2017,9, 177 7 of 25
after aquifer passage were exclusively available from the pilot. All data (obtained from [
9
–
12
] and from
data files supplied by Dr. G. Koziorowski (GTZ International Services) were controlled, elaborated
and stored with Hydrogeochemcal.xlsx [26].
2.6. Monitoring Campaign in August 2014
In the period of 3–7 August 2014 a sampling campaign was conducted to take 31 samples from
divergent observation wells that had been sampled earlier and from DSW, in order to: (i) check
potential bias in the existing hydrochemical data set of well fields A, B and C; and (ii) obtain data on
chromium speciation: Cr(III) versus Cr(VI).
Important aspects that were tackled with great care, are: sufficient well purging based on purged
volume and stable field parameters, sampling without applying vacuum and excluding atmospheric
exposition, reducing exposure to sunlight and wind, flow regulation of the pump, field measurements
(EC, pH, temp, O
2
), filtration of water over a 0.45
µ
m membrane, dedicated sample preservation for
specific parameter groups, cooling, nearly daily shipment to the Netherlands, and rapid analysis in the
certified Vitens Laboratory (Leeuwarden). The quality of the analysis was validated using HGC 2.0 to
exclude potential impact of errors.
2.7. Predictions by EL Modeling
Two models were constructed, an Excel based Easy-Leacher (EL) model [
25
] and a PHREEQC-2 [
27
]
flowtube model.
PHREEQC-2 was applied to model more in detail the behavior of chromate and arsenate along a
small number of flowlines during infiltration phase. PHREEQC-2 and EL produced nearly identical
results for chromate and arsenate behavior during infiltration, justifying the application of the simpler
EL model. Further details about the PHREEQC-2 modeling and its results are given by [
24
] and not
considered here further.
EL simplifies 3D groundwater flow into a 2D set of maximum 50 flow tubes through a maximum
of 10 horizontal aquifer layers. The travel times are either derived from a hydrological model, or
calculated analytically. Chemical transport is calculated on the basis of pore volumes (dimensionless
time scale), retardation and leach factors (superimposed on the pore volumes) based on either mass
balances or field observations, CaCO
3
equilibrium (if relevant), redox reactions (if relevant), and expert
rules on among others redox reaction kinetics.
EL was given the task to do the all-round water quality modeling during all ASR phases (infiltration,
storage with bubble drift, and recovery), and to combine the output of a relatively high number of
flowlines into a mixed output as generated by a well field.
In EL, the whole ASR system was schematized by one representative recharge basin (the average
of basins A–C), 5 aquifer layers (of which the upper layers a, b and c are most important) and 7 flowlines
within each aquifer layer departing from the basin towards one recovery well in each of the 7 well
rings at 75–225 m radius (Figure 5).
The expansion of the DSW bubble in each aquifer layer and the travel times along each flowline
were calculated by assuming first vertical flow down to each aquifer layer and then horizontal radial
flow, so that:
tN=nNπr2T
QIN Kh,N
+tV(4)
where: t
N
= 50% break-through time (t
50
) in layer N [d]; n
N
= porosity of layer N [-]; r= radial distance
from the basin center [m]; T= transmissivity of the aquifer [m
2
/d]; Q
IN
= mean infiltration rate
[m
3
/d]; K
h,N
= horizontal hydraulic conductivity of layer N [m/d]; and t
V
= vertical travel time [d] as
determined by a 3D hydrological model [8].
This simplification creates some distortion during the first 30 d, but these are of minor importance
on the long run of 824 d of infiltration. With Equation (4), the travel time was calculated from recharge
basin to its 7 surrounding rings of recovery wells at the distances specified in Figure 6. It is deduced
Water 2017,9, 177 8 of 25
that in theory all wells, also those in the outermost ring will pump DSW after 824 d of infiltration.
In layers D and E, probably little DSW will be present.
Water 2017, 9, 177 8 of 25
Figure 6. Calculated travel times (tN) to the 7 well rings around each recharge basin during infiltration,
in aquifer layers a–e, and the number of pore volumes (PV) after 824 d of nonstop infiltration. PV =
824/tN. Orange cells have PV < 1, indicating that DSW did not arrive during the recharge period.
During 10 years of storage, the infiltrated DSW bubble is predicted to move laterally down the
regional hydraulic gradient, with the following velocity (vB,N), assuming an equal gradient in each layer:
, =, ∆
∆ (5)
where ΔH/ΔX = mean regional hydraulic gradient in the aquifer at well fields A, B and C during
storage phase [m/m].
Vertical bubble drift by buoyancy has been ignored in accordance with FEFLOW model
predictions [9]. The water quality evolution during injection phase was calculated for each flowline
where it crossed its destination well (node point), and also for the “fictive”, mixed sample taken from
all 35 node points, in proportion to: (i) the preset pumping regime (the inner wells pumping more
than the outer wells); and (ii) the transmissivity of each main contributing aquifer layer (a–c). This
mixed sample thus represents the output from the whole well field, when pumping out a negligible
amount of water without disturbing the continuous DSW bubble expansion.
EL in forward mode assumes the following: (1) input quality (DSW) is constant; (2) retardation
factors, leach factors and the (semi)permanent concentration changes are derived from observations
during the pilot; (3) redox reactions are absent as observed in the pilot; (4) reactive minerals such as
calcite, dolomite and silicates are not depleted; and (5) reaction kinetics do not play an important role.
The recovery phase was modeled by moving backward in the time series that displays the
quality evolution of this “imaginary”, mixed (averaged) water sample. Contrary to the infiltration
phase, this “imaginary”, mixed sample now becomes the true output of the well field during recovery
phase, showing after some time an increasing instead of decreasing contribution of native
groundwater. This is in harmony with theory and the predictions by [9,11].
As during the 90 d of recovery 67% of the infiltrated water volume will be pumped out, the way
back in the expansion time series needs to be as long as 0.67 × 824 = 552 d (= ΔtBACK-1). This way, water
quality at the start of recovery, without storage phase, will be the water that flushed each of the 7
well rings prior to pumping (on day 824), and this water only needs to be mixed in proportion to the
pumping rates of each well ring (Figure 6). At the end of pumping (after 90 d) we obtain about the
same water as predicted to surround the wells on day 824 − 552 = 272. Water compositions in between
can be calculated by just following the predicted water quality from 824 to 272 d back in time. In
order to plot this water quality evolution during 90 d of recovery, the expanded time scale (from 90
to 552 d) needs to be compressed back again to 90 d, by multiplying it with 90/552, and to mirror it
from backward into forward mode (Figure 7).
Figure 6.
Calculated travel times (t
N
) to the 7 well rings around each recharge basin during infiltration,
in aquifer layers a–e, and the number of pore volumes (PV) after 824 d of nonstop infiltration.
PV = 824/t
N
. Orange cells have PV < 1, indicating that DSW did not arrive during the recharge period.
During 10 years of storage, the infiltrated DSW bubble is predicted to move laterally down
the regional hydraulic gradient, with the following velocity (v
B,N
), assuming an equal gradient in
each layer:
vB,N=Kh,N∆H
nN∆X(5)
where
∆
H/
∆
X= mean regional hydraulic gradient in the aquifer at well fields A, B and C during
storage phase [m/m].
Vertical bubble drift by buoyancy has been ignored in accordance with FEFLOW model
predictions [
9
]. The water quality evolution during injection phase was calculated for each flowline
where it crossed its destination well (node point), and also for the “fictive”, mixed sample taken from
all 35 node points, in proportion to: (i) the preset pumping regime (the inner wells pumping more than
the outer wells); and (ii) the transmissivity of each main contributing aquifer layer (a–c). This mixed
sample thus represents the output from the whole well field, when pumping out a negligible amount
of water without disturbing the continuous DSW bubble expansion.
EL in forward mode assumes the following: (1) input quality (DSW) is constant; (2) retardation
factors, leach factors and the (semi)permanent concentration changes are derived from observations
during the pilot; (3) redox reactions are absent as observed in the pilot; (4) reactive minerals such as
calcite, dolomite and silicates are not depleted; and (5) reaction kinetics do not play an important role.
The recovery phase was modeled by moving backward in the time series that displays the quality
evolution of this “imaginary”, mixed (averaged) water sample. Contrary to the infiltration phase, this
“imaginary”, mixed sample now becomes the true output of the well field during recovery phase,
showing after some time an increasing instead of decreasing contribution of native groundwater.
This is in harmony with theory and the predictions by [9,11].
As during the 90 d of recovery 67% of the infiltrated water volume will be pumped out, the way
back in the expansion time series needs to be as long as 0.67
×
824 = 552 d (=
∆
t
BACK-1
). This way,
water quality at the start of recovery, without storage phase, will be the water that flushed each of the
7 well rings prior to pumping (on day 824), and this water only needs to be mixed in proportion to
the pumping rates of each well ring (Figure 6). At the end of pumping (after 90 d) we obtain about
the same water as predicted to surround the wells on day 824
−
552 = 272. Water compositions in
Water 2017,9, 177 9 of 25
between can be calculated by just following the predicted water quality from 824 to 272 d back in time.
In order to plot this water quality evolution during 90 d of recovery, the expanded time scale (from 90
to 552 d) needs to be compressed back again to 90 d, by multiplying it with 90/552, and to mirror it
from backward into forward mode (Figure 7).
In the case of a 10-year storage phase, lateral bubble drift can be taken into account by first
extending the backward period of 552 d (
∆
t
BACK-1
) with the period (=
∆
t
BACK-2
) that would be needed
to get the retrograded bubble face back on its position at 552 d without bubble drift, and then resetting
the time scale to 90 d by multiplying it with 90/(552 +
∆
t
BACK-2
), and mirror it from backward into
forward mode (Figures 7and 8).
The calculation of
∆
t
BACK-2
is then as indicated in the realistic example elaborated in Figure 8.
In order to simplify the calculations, the weighted average value of
∆
t
BACK-2
is taken, being 174 d in
the example of Figure 6. Addition of
∆
t
BACK-2
= 552 yields a total set-back time of 726 d. This means
that the quality of the water recovered after 90 d of pumping, is to be looked up in the quality output
list on day 824 −726 = 98, in case of bubble drift during 10 years of storage.
How this example with resulting time shifts works out in the %DSW and TDS concentration of
the water recovered, is shown in Figure 7. The underlying calculations were performed in EL, and
match the predictions by [9] quite well.
EL in backward mode assumes that: (a) the forward evolution is reversed at 6 times higher speed;
(b) the 6 times higher recovery rate does not provoke serious upconings (as shown by 3D modeling
results [9]; and (c) during storage and recovery no further reactions with the aquifer are taking place.
Fluxes in the different aquifer layers, from the recharge basin towards the recovery wells and
beyond them, were set equal to their contribution to the aquifer’s transmissivity.
Model calibration was done on: (1) available data from the pilot study in 2003–2004 when DSW
was infiltrated via a recharge basin; and (2) groundwater quality as observed in the same pilot area in
August 2014, after about 6 years of storage in the local aquifer system (since a second recharge run
in 2008).
Water 2017, 9, 177 9 of 25
In the case of a 10-year storage phase, lateral bubble drift can be taken into account by first
extending the backward period of 552 d (Δt
BACK-1
) with the period (=Δt
BACK-2
) that would be needed to
get the retrograded bubble face back on its position at 552 d without bubble drift, and then resetting
the time scale to 90 d by multiplying it with 90/(552 + Δt
BACK-2
), and mirror it from backward into
forward mode (Figures 7 and 8).
The calculation of Δt
BACK-2
is then as indicated in the realistic example elaborated in Figure 8. In
order to simplify the calculations, the weighted average value of Δt
BACK-2
is taken, being 174 d in the
example of Figure 6. Addition of Δt
BACK-2
= 552 yields a total set-back time of 726 d. This means that
the quality of the water recovered after 90 d of pumping, is to be looked up in the quality output list
on day 824 − 726 = 98, in case of bubble drift during 10 years of storage.
How this example with resulting time shifts works out in the %DSW and TDS concentration of
the water recovered, is shown in Figure 7. The underlying calculations were performed in EL, and
match the predictions by [9] quite well.
EL in backward mode assumes that: (a) the forward evolution is reversed at 6 times higher
speed; (b) the 6 times higher recovery rate does not provoke serious upconings (as shown by 3D
modeling results [9]; and (c) during storage and recovery no further reactions with the aquifer are
taking place.
Fluxes in the different aquifer layers, from the recharge basin towards the recovery wells and
beyond them, were set equal to their contribution to the aquifer’s transmissivity.
Model calibration was done on: (1) available data from the pilot study in 2003–2004 when DSW
was infiltrated via a recharge basin; and (2) groundwater quality as observed in the same pilot area
in August 2014, after about 6 years of storage in the local aquifer system (since a second recharge run
in 2008).
Figure 7. Explanation to how the predicted “fictive” mixed water quality at the recovery wells during
824 d of infiltration is used in backward mode, for predicting water quality during 90 d of recovery,
without or with bubble drift effects. The forward EL prediction is reversed and its time axis
compressed.
Figure 7.
Explanation to how the predicted “fictive” mixed water quality at the recovery wells during
824 d of infiltration is used in backward mode, for predicting water quality during 90 d of recovery,
without or with bubble drift effects. The forward EL prediction is reversed and its time axis compressed.
Water 2017,9, 177 10 of 25
Water 2017, 9, 177 10 of 25
Figure 8. Calculated horizontal bubble drift (ΔXB) as function of aquifer layer and storage time, for
the Liwa aquifer system, and its impact on the set-back time ΔtBACK-2. Together with the set-back time
due to recovery (ΔtBACK-1), a total set-back time of 726 d is obtained. Further explanation can be found
in the text and in the list of abbreviations (end of paper).
3. Results of Hydrogeological, Geochemical and Hydrochemical Stratification Analysis
3.1. Hydrogeology
The hydrogeological schematization is presented in Figure 5. It shows an upper aquifer with
transmissivity 768 m2/d, formed by layers a–c, which consist of reddish to yellowish brown, eolian
sand(stone) of Quaternary age. It is unsaturated in its upper 30 m, and consists there mostly of
uncemented or weakly cemented sand. From the groundwater table downwards to the aquifer base
at 62 m ASL, an alternation is observed of semi-consolidated and weakly to moderately cemented
sands and sandstone.
Aquitard 1 and Aquifer 2, between 62 m ASL and 14 m BSL, likely correspond to the Pleistocene
Medinat Zayed formation, consisting of mainly eolian and some fluvial and lacustrine deposits [11].
It is composed of yellowish brown to red brown to gray calcarenaceous sandstone with intercalations
of siltstone, mudstone, marl and thin sand lenses.
Aquitard 2, at the base of the considered aquifer complex, is composed of a Neogene formation [11],
consisting of light gray to white calcarenite, limestone and dolomite with interbeds of white to
pinkish gypsum, marl, and chalk.
3.2. Geochemistry
The mean geochemical stratification (Table 1) follows more or less the hydrogeological
subdivision (Figure 5). The interpreted data reveal the presence of the following reactive phases in
the aquifer system, with their main potential interaction with water within brackets: Bulk Organic
Material (denitrification, sorption), clay minerals (sorption), iron (hydr)oxide coatings of sand grains
(source of Fe and oxyanions like chromate, vanadate and arsenate), calcite and dolomite (or dolomitic
limestone; source of Ca, Mg, Sr and HCO3), feldspars (source of Na, Ca and SiO2), gypsum (source of
Ca, Sr and SO4), pyroxene (source of oxyanions like chromate, vanadate and arsenate), and
(fluoro)apatite (source of Ca, PO4 and F). Gypsum and dolomite were concentrated in aquitard 2 (at
the base), feldspar and iron (hydr)oxides in aquifer 1 (the top).
The eolian sand is typically coated with iron (hydr)oxide, and more or less cemented mainly by
calcite. The iron hydroxide coatings are considered to be the main (but genetically the secondary)
source of oxyanions like chromate [Cr(VI)], vanadate, molybdate, selenate, arsenate and phosphate.
These negatively charged ions are (chemi)sorbed to these positively charged coatings, and may
desorb from it under specific conditions.
Figure 8.
Calculated horizontal bubble drift (
∆
X
B
) as function of aquifer layer and storage time, for the
Liwa aquifer system, and its impact on the set-back time
∆
t
BACK-2
. Together with the set-back time due
to recovery (
∆
t
BACK-1
), a total set-back time of 726 d is obtained. Further explanation can be found in
the text and in the list of abbreviations (end of paper).
3. Results of Hydrogeological, Geochemical and Hydrochemical Stratification Analysis
3.1. Hydrogeology
The hydrogeological schematization is presented in Figure 5. It shows an upper aquifer with
transmissivity 768 m
2
/d, formed by layers a–c, which consist of reddish to yellowish brown, eolian
sand(stone) of Quaternary age. It is unsaturated in its upper 30 m, and consists there mostly of
uncemented or weakly cemented sand. From the groundwater table downwards to the aquifer base at
62 m ASL, an alternation is observed of semi-consolidated and weakly to moderately cemented sands
and sandstone.
Aquitard 1 and Aquifer 2, between 62 m ASL and 14 m BSL, likely correspond to the Pleistocene
Medinat Zayed formation, consisting of mainly eolian and some fluvial and lacustrine deposits [
11
].
It is composed of yellowish brown to red brown to gray calcarenaceous sandstone with intercalations
of siltstone, mudstone, marl and thin sand lenses.
Aquitard 2, at the base of the considered aquifer complex, is composed of a Neogene formation [
11
],
consisting of light gray to white calcarenite, limestone and dolomite with interbeds of white to pinkish
gypsum, marl, and chalk.
3.2. Geochemistry
The mean geochemical stratification (Table 1) follows more or less the hydrogeological subdivision
(Figure 5). The interpreted data reveal the presence of the following reactive phases in the aquifer
system, with their main potential interaction with water within brackets: Bulk Organic Material
(denitrification, sorption), clay minerals (sorption), iron (hydr)oxide coatings of sand grains (source of
Fe and oxyanions like chromate, vanadate and arsenate), calcite and dolomite (or dolomitic limestone;
source of Ca, Mg, Sr and HCO
3
), feldspars (source of Na, Ca and SiO
2
), gypsum (source of Ca, Sr and
SO
4
), pyroxene (source of oxyanions like chromate, vanadate and arsenate), and (fluoro)apatite (source
of Ca, PO
4
and F). Gypsum and dolomite were concentrated in aquitard 2 (at the base), feldspar and
iron (hydr)oxides in aquifer 1 (the top).
The eolian sand is typically coated with iron (hydr)oxide, and more or less cemented mainly by
calcite. The iron hydroxide coatings are considered to be the main (but genetically the secondary)
source of oxyanions like chromate [Cr(VI)], vanadate, molybdate, selenate, arsenate and phosphate.
Water 2017,9, 177 11 of 25
These negatively charged ions are (chemi)sorbed to these positively charged coatings, and may desorb
from it under specific conditions.
Another mineral frequently mentioned by [
12
], in concentrations of
≤
1%, is pyroxene. Pyroxenes
are of particular interest due to their potential contribution to Cr. Their composition is as follows:
XY(Si,Al)
2
O
6
with X representing Ca, Na, Fe(II), Mg and more rarely Zn, Mn and lithium, and Y
representing Cr, Al, Fe(III), Mg, Mn, Sc, Ti and V. There is indeed a good positive correlation between
Cr, Al, Fe, Ni, Ti, V and Zn [
23
], indicating that pyroxenes could be a significant primary source of Cr.
No mention was made of the occurrence of olivine, another mineral typical of ophiolites, which [
28
]
suspect as being the primary source of Cr in Abu Dhabi’s groundwater. This mineral has a high
weathering thus low resistance potential, and has possibly therefore not been found.
3.3. Chemistry of Native Groundwater
The strong vertical zonation of water qualities in the aquifer system is mainly linked to a
rising salinity (TDS) with depth (Figure 5). The latter is dictated by the presence of shallow “fresh”
groundwater on top of deep seated brackish to saline paleowater [
11
]. The “fresh” groundwater, with
a low Cl/Br ratio and high stable isotope content, is considered to be derived from local precipitation
during relatively warm and humid climatic conditions with high evaporation losses, without significant
contributions from evaporite dissolution [
11
,
29
]. The brackish to saline paleowater, with a high Cl/Br
ratio and low stable isotope content, is considered to be derived from rainwater that dissolved
evaporitic rock during relatively cold climatic conditions with less evaporation losses [11,29].
The following parameters follow the salinity (TDS) increase with depth: EC, Cl, SO
4
, NO
3
, Na,
Fe, Mn, Al, B, Br, Cr, Cr(VI), Mo, Ni, Sr and Cl/Br ratio, whereas HCO
3
, Ba and Ca/Mg ratio decline
with depth (Table 2). All groundwater is (sub)oxic (containing little O
2
and much NO
3
), more or
less in equilibrium with calcite and dolomite (as expected on the basis of geochemistry), slightly
undersaturated with respect to barite, and (strongly) undersaturated with respect to fluorite and
gypsum (base of layer e excluded where near equilibrium with gypsum).
The current mean-annual rainfall of 40–60 mm/year [
30
] would be sufficient to sustain natural
recharge by local precipitation at a rate of ~7.6 [
11
] or 11 mm/year [
8
]. Tritium data on samples taken
close to the groundwater table, stable isotope data, fluoro-chlorinated hydrocarbons and reaction
patterns of the groundwater table to recharge events confirm that recharge of groundwater is actually
taking place [8].
Between well fields A, B and C some differences exist [
23
]. Well field B is the most saline at all
depth levels. Well field C is the least saline and most homogeneous of all. Well field A forms an
intermediate, and is therefore taken as a representative for the whole plant.
Water 2017,9, 177 12 of 25
Table 1. Simplified geochemical stratification as derived from [23]. BOM = bulk organic material; CEC = Cation Exchange Capacity.
Layer
No.
Top m
ASL
Base m
ASL
Quartz Calcite Dolomite Feldspar Clay Min. Others BOM Gypsum Apatite
mg/kg pH-H2OCEC
meq/kg
% d.w.
A 140 96 67.8 10.3 4.0 10.6 4.0 1.3 1.9 <0.1 0 8.10 61.3
B 96 80 83.0 2.9 2.3 9.2 1.5 1.7 0.5 <0.1 123 8.12 19.0
C 80 62 71.8 6.2 2.5 10.6 1.6 1.7 0.9 <0.1 154 8.18 28.1
D 62 56 47.0 19.9 18.3 6.0 18.2 1.3 0.5 <0.1 956 8.00 136.7
E 56 −14 54.6 13.9 12.8 5.4 17.1 1.6 1.6 0.1 83 7.89 146.6
F−14 <−40 0.9 16.6 80.1 0.0 0.2 6.9 1.8 2.7 0 7.90 31.5
Water 2017,9, 177 13 of 25
Table 2.
Simplified chemical stratification of the native groundwater, averaged over both pilot and ABC
plant areas. Aquifer 1 = layers a–c; Aquitard 1 = layer d; Aquifer 2 = layer e. Abu Dhabi drinking water
standards according to [
13
], WHO guidelines according to [
31
], both with red numbers for parameters
considered at risk during ASR recovery. All samples showed: Ag < 1, Be < 0.1, Pb < 5 µg/L.
Sample
Layer # Figure 5a b c d e-Top e-Base Abu Dh.
Drinking w.
Standard
WHO
2011
Guidelines
Depth m ASL 140 96 80 62 56 35
96 80 62 56 35 −14
General
O2mg/L 0.9 2.0 2.2 2.3 2.5 0.0 >2
Temp. ◦C 34.0 34.1 34.5 34.5 34.8 31.0
EC 20 ◦CµS/cm 969 1180 2132 4095 5650 17,647 1600
TDS mg/L 682 803 1545 2957 4042 13,288 1000
pH lab 7.83 8.25 8.09 7.92 7.94 7.40 7−9.2
Main constituents
Cl
mg/L
187 233 396 978 1506 5500 250
SO4147 152 397 702 844 3137 250
HCO381 101 154 148 144 39 >60
NO325.0 30.8 37.4 41.7 42.6 96.0 50 50
PO40.022 0.034 0.029 0.028 0.030 0.015 2.2
F 1.29 1.50 3.61 3.29 2.39 0.75 1.5 1.5
Na 141 209 466 877 1204 3238 150
K 12.9 11.7 11.5 15.8 18.5 83.7 12
Ca 41.7 26.2 29.8 107.3 174.8 821.0 80
Mg 10.7 7.0 11.2 41.1 67.0 340.0 30
Fe 0.005 0.023 0.022 0.012 0.019 <0.44 0.2
Mn 0.004 0.008 0.008 0.020 0.037 0.030 0.4
NH40.015 0.025 0.019 0.015 0.015 0.035 0.5
SiO226.2 23.1 28.4 27.8 23.6 14.3
DOC 0.3 1.0 0.6 1.5 2.6 5.3 1
Trace elements
Al
µg/L
3 19 19 19 23 <290 200
As 2.1 11.4 9.6 6.0 4.7 <10 10 10
B 605 774 1113 1330 1421 1340 2400 2400
Ba 40 38 31 33 36 23 700 700
Br 579 668 788 762 767 301
Cd 0.08 0.05 0.05 0.06 0.08 <10 3 3
Co 0.06 0.08 0.07 0.44 0.82
Cr-tot 52 87 115 129 123 <286 50 50
Cr(VI) 48 85 108 119 117
Cu 0.3 0.7 0.9 0.3 0.3 <1 1000 2000
Hg 0.02 0.23 0.13 0.02 0.04 6 6
Mo 6 11 39 47 39 <10
Ni 0.5 2.5 1.6 1.0 1.6 70 70
Sb <1 2.2 1.2 <1 <1 20 20
Se 3.2 3.2 3.3 4.1 5.2 17.0 40 40
Sr 3485 2846 7381 8486 6573 1700
Ti <0.5 <0.5 <0.5 0.6 0.7
U 0.6 0.7 3.0 3.1 3.1 30
V 29 77 95 71 49 <10
Zn 3 16 7 2 2 <50 5000
Ratio’s
Cl/Br
mg/L-basis
323 348 503 1284 1963 18297
Ca/Sr 12.0 9.2 4.0 12.6 26.6 482.9
Ca/Mg 3.9 3.8 2.7 2.6 2.6 2.4
Mineral Sat.
Barite
Saturation
Index
−0.12 −0.13 −0.14 −0.16 −0.20 −0.50
Calcite −0.06 0.15 0.13 0.10 0.13 −0.15
Dolomite −0.26 0.18 0.30 0.29 0.39 −0.15
Fluorite −0.82 −0.95 −0.29 −0.37 −0.68 −0.82
Gypsum −1.72 −1.96 −1.70 −1.42 −1.43 −0.02
TIC mmol/L 1.38 1.71 2.59 2.51 2.43 0.68
Water 2017,9, 177 14 of 25
4. Results of Sampling Campaign in August 2014
The sampling campaign of 3–7 August 7 2014 revealed [
23
] that there was only limited bias in the
2003–2013 hydrochemical data set of well fields A, B and C, and that practically all (>95%) of dissolved
Cr consists indeed of Cr(VI).
The following bias was deduced for the large data set 2003–2013: O
2
concentrations for all
monitoring wells were too high due to oxygenation, and suspended fines raised the concentrations of
PO
4
, Fe, Mn, NH
4
, Al, and possibly also Zn in many samples. In addition, the minimum detection
limits (MDLs) could be lowered for Cd, Hg, Ni, and Sb. All hydrochemical data presented here have
been corrected for the demonstrated bias, where possible.
5. Results of Pilot
The available monitoring data at the pilot in 2003–2004 and 2014 (some of which are in Table 3)
reveal among others the following quality changes of DSW in the aquifer:
•
There are hardly any changes of O
2
, Cl, SO
4
, HCO
3
, TIC, NO
3
and NH
4
, even after six years of
storage. This indicates that redox reactions were practically nonexistent, and carbonates (calcite
and dolomite) hardly dissolved or precipitated.
•
A small TDS increase (20–30 mg/L) by dissolution of mainly SiO
2
, K and possibly Mg. Carbonate
dissolution was noticed only where a very strong Ca/Na exchange was taking place (see next point).
•
Ca/Na exchange in which Ca concentrations declined and Na increased was observed. This
was especially important for samples close to the DSW intrusion front and typical for fresh
water intrusion.
•
Mobilization of the trace elements As, B, Ba, F, Cr, Sr and V from the aquifer, through desorption
and/or mineral dissolution was observed. The strongest and most persistent increase is noticed
for Sr, which does not exactly match Ca behavior, so that another mineral could be the source. Of
the trace elements mentioned, Ba shows the smallest mobilization, whereas As, F and Cr show a
significant leaching by DSW, which is also important from a drinking water quality perspective.
•
Immobilization of PO
4
, Al, Cu, Fe and Ni during aquifer passage was mainly by sorption of PO
4
,
Cu and Ni, and filtration of suspended colloidal particles of Al and Fe.
•
Calculated mineral saturation indices show that the infiltrated water is more or less in equilibrium
with calcite and dolomite as expected. The values for gypsum, barite and fluorite indicate a
strong undersaturation.
These changes were subsequently plotted against dimensionless time parameter PV (Equation (1)),
as shown for a selection of constituents in Figure 9. The resulting patterns were translated into leaching
and retardation factors and semi-permanent concentration changes (Table 4). These observations
assisted in fine-tuning the EL model, which is partly based on both calculated and observed values of
L, R and DC.
Water 2017,9, 177 15 of 25
Table 3.
Overview of water quality at the pilot basin recharge scheme in 2003–2004 and in August 2014.
The samples taken in 2014 refer to a second recharge trial in 2008 at the same pilot plant, and therefore
represent DSW after six years of aquifer storage. DSW infiltrated in 2008 (not shown here) deviates
only slightly from DSW sampled in 2014.
Loc Unit
First Pilot 2003-4 Second Pilot 2008 (2014)
RB-01 DSW RB-01 RB-02 OB-01A OB-07B DSW OB-01A OB-07B
Ambient Input Recovery Wells Obs. Wells Input Obs. Wells
Space & time
Top screen m ASL 93 121 93 91 104 100 121 104 100
Base screen m ASL 75 121 75 73 95 91 121 95 91
Radial distance m 83 0.0 83 30 44 90 0 44 90
t50 d 0.0 11 50 0 11 50
PVs - 0.0 0.0 >3 >10 6.3 1.4 0.0 50.0 10.0
Digital date year 2003.70
2004.21
2004.35
2004.57 2003.94
2003.94
2014.59
2014.60 2014.60
Main composition
O2mg/L 4.9 7.2 8.0 7.2 6.8 7.2
EC 20 ◦C, lab µS/cm 1313 397 487 432 413 512 123 134 142
Temperature ◦C 31.0 35.0 31.0 31.0 31.0 31.0 35.0 36.4 35.8
pH-Lab - 8.94 7.90 9.11 7.69 8.57 8.50 8.11 8.43 8.90
Na mg/L 266.0 45.7 107.0 57.2 46.3 104.0 4.1 7.4 25.9
K mg/L 6.1 1.6 2.7 8.1 10.4 7.8 <0.1 2.9 5.7
Ca mg/L 7.3 22.3 1.8 21.0 17.3 8.4 20.2 12.2 4.6
Mg mg/L 2.5 5.3 0.5 3.9 6.2 4.9 0.4 5.0 1.7
Fe mg/L 0.130 0.255 0.050 0.150 0.080 0.683 0.012 0.005 0.005
Mn mg/L 0.040 0.008 0.050 <0.01 0.020 0.008 0.003 0.003 0.003
NH4mg NH4/L <0.1 <0.1 <0.1 <0.1 <0.1 <0.03 <0.03 <0.03
SiO2mg SiO2/L 27.3 2.1 24.0 24.0 18.2 4.6 <1 15.2 20.0
Cl mg/L 216.0 80.8 80.3 78.0 83.1 89.5 5.0 10.0 11.0
SO4mg/L 162.0 11.7 10.7 10.8 13.4 22.0 1.0 <2 2.0
HCO3mg/L 152 60 123 104 62 139 66 66 59
TIC mmol/L 2.64 1.01 2.16 1.78 1.04 2.33 1.11 1.11 1.01
NO3mg NO3/L 23.5 <0.5 0.0 0.0 <0.5 <0.5 <1 <1 <1
NO2mg NO2/L 0.01 <0.01 <0.01 0.004 <0.01 <0.01 <0.01
PO4-total mg PO4/L 0.21 0.06 0.02
PO4-ortho mg PO4/L 0.021 0.062 0.021 0.358 0.060 <0.03 <0.03
F mg/L 2.10 0.05 0.20 0.10 0.10 3.51 <0.05 0.06 0.26
DOC mg/L 8.4 <0.5 <0.5 <0.5
Trace elements
Al µg/L 180 248 510 200 80 535 51 13 13
As µg/L 11.0 0.0 <3 <0.5 2.2 8.4
Bµg/L 850 29 58 52 52 17 56 55
Ba µg/L 13 5 30 6 16 20 2 12 3
Br µg/L 570 20 301 301 140 161 186
Cr µg/L 95.0 2.5 17.0 15.0 13.0 <0.5 12.9 7.4
Cu µg/L 5.0 20.3 2.0 4.0 <2 <2 16.4 <0.5 <0.5
Mo µg/L 10.0 <3 <3 <3 <3 <3 <1 <1 <1
Ni µg/L 3.0 9.5 <3 <3 <3 <3 4.3 <1 <1
Se µg/L <2 <2 3.0 3.0 <2 <0.5 <0.5 <0.5
Sr µg/L 1200 50 200 1600 1300 278 16 1000 274
Vµg/L 66 1.5 140 36 17 <0.5 12 64
Zn µg/L 10 81 59 98 4 5 3 <2 <2
Mineral
saturation
SI-B Barite −0.5 −1.8 −1.0 −1.7 −1.2 −0.9 −2.6 −2.4 −2.7
SI-C Calcite 0.5 −0.2 0.1 −0.3 0.3 0.2 0.0 0.2 0.0
Si-D Dolomite 0.9 −0.6 0.0 −0.9 0.5 0.6 −1.2 0.4 0.0
SI-G Gypsum −2.4 −2.9 −4.0 −2.9 −2.9 −3.1 −3.2 −4.1 −4.2
SI-B Barite −0.5 −1.8 −1.0 −1.7 −1.2 −0.9 −2.6 −2.4 −2.7
SI-F Fluorite −1.1 −3.7 −3.6 −3.1 −3.2 −0.5 −4.3 −3.8 −2.9
Water 2017,9, 177 16 of 25
Water 2017, 9, x 16 of 25
Water 2017, 9, 177; doi:10.3390/w9030177 www.mdpi.com/journal/water
Figure 9. Concentration of selected constituents during and long after breakthrough of DSW in aquifer layers A, B, C and E in the pilot basin recharge scheme, with best
fitting lines for all data points or for the data of 2003–2004 and 2014, separately. Mean concentrations in DSW in 2003 and 2014 and in native groundwater of the 2–4 aquifer
layers (in legend, within brackets) are indicated. The three encircled observation points in the plot were sampled in August 2014 (after six-year storage), the others were
sampled in 2003–2004. Note that samples with >3 pore volumes consist of 100% DSW!
Figure 9.
Concentration of selected constituents during and long after breakthrough of DSW in aquifer layers A, B, C and E in the pilot basin recharge scheme, with
best fitting lines for all data points or for the data of 2003–2004 and 2014, separately. Mean concentrations in DSW in 2003 and 2014 and in native groundwater of the
2–4 aquifer layers (in legend, within brackets) are indicated. The three encircled observation points in the plot were sampled in August 2014 (after six-year storage),
the others were sampled in 2003–2004. Note that samples with >3 pore volumes consist of 100% DSW!
Water 2017,9, 177 17 of 25
The plots in Figure 9show the observed concentration trends for selected constituents as function
of the dimensionless time parameter “pore volume” (PV). The following classification of elements
with similar behavior can be made on the basis of their concentration/PV-plot.
•Ca, Mg and Sr
(Ca and Mg shown in Figure 9) concentrations start low and with increasing PVs
rise to an asymptotic value. All 2014 data plot below those of 2003–2004, which is partly explained
by the lower DSW input in 2008. Only Ca and Mg show an initial concentration below DSW input,
which is probably linked to Na exchange, with Ca developing an asymptotic value at or below
DSW input. Contrary, Mg and Sr approach an asymptotic value little (Mg) or far (Sr) above DSW
input. Obviously, Mg and even more so Sr are dissolved from the aquifer, and Ca is not. Sources
of Mg and Sr could be dolomite and/or silicate minerals.
•SiO2, K and V
concentrations (SiO
2
and K shown in Figure 9) decline in an exponential way,
but relatively slowly compared to the next group, and the low concentration asymptote is also
relatively high and in most cases far above DSW input. This suggests that these elements are
initially desorbed and that later on they could be dissolving from the aquifer, possibly from quartz
(SiO
2
), K-feldspar (K and SiO
2
) or for instance pyroxenes (SiO
2
and V). A long storage time yields
much higher concentrations for SiO
2
, pointing at slow dissolution kinetics. Vanadium is likely
present as VO43−, which could desorb from iron (hydr)oxide coatings.
•Na, As, B, Cr, F and Mo
(Na and Cr shown in Figure 9) concentrations also decline in an
exponential way, but much more rapidly than the previous group. The low concentration
asymptote is relatively high and in any case significantly above DSW input, especially for As, B
and Cr. The asymptote approaches DSW input better for Na, F and Mo. This suggests that all these
elements are very rapidly desorbed and that later on especially As, B and Cr could be steadily
dissolving from the aquifer matrix. Except for Na and B (as H
3
BO
3
), this group is composed of
anions, As as AsO
43−
, Cr as CrO
42−
, F as F
−
and Mo as MoO
42−
. The source mineral of chromate
and vanadate could be pyroxenes [23].
•Al, Fe and Ni
concentrations (Al shown in Figure 9) decline in an exponential way, approximately
as rapidly as the previous group. Their concentration seems to be dictated by colloidal particles
that become initially mobilized. On the one hand, lack of filtration may have contributed to this.
On the other hand, it is well known [
32
], that clay minerals in aquifers tend to be mobilized by
deflocculation when the sodium adsorption ratio (SAR) of the infiltration water and of the native
groundwater is high, their salinity low, the clay mineral content high, and the dominant type of
clay minerals unfavorable (smectite > illite > kaolinite). The SAR value of the native groundwater
seems to be more important than the one of the infiltration water. With SAR values of ~20, the risk
of mechanical clogging of the aquifer when the particles strand in the pore necks is relatively
high. This risk is estimated higher in aquifer layer C than in A and B because SAR of native
groundwater is higher and permeability is lower.
In Table 4, the estimated retardation (R) or leach factors (L) as derived from the PV-plots (Figure 9)
are listed, together with the estimated (semi)permanent concentration increase (DC).
Water 2017,9, 177 18 of 25
Table 4.
Interpretation of water quality observations at the pilot, in terms of retardation factor (R),
Leach factor (L) and (semi)permanent concentration change after break-through (∆C).
Parameter L R ∆C [mg/L] Parameter L R ∆C [ug/L]
2003-4 2014 2003-4 2014
Na 1.5–2 – 3 3.5 F 1.5–2 – 0.2 0.04
K 20 – 3 3 Al 1.5 – −130 −39
Ca – 3.5 0 −8 As 3 – 1 2
Mg – 3 3.3 4.5 B 2 – 10 30
Fe 2 – 0 0 Ba – – 10 10
SiO22–4 – 0.6 14.5 Cr 1.5–2 – 10 13
Cl 1 – 0 0 Mo 1.5 – 0 0
SO41 – 0 0 Ni 1.5 – -8 −4
HCO31 – 0 0 Sr – 3.5 1600 984
NO31 – 0 0 V 5 – 10 11
PO4-O – – −0.04 −0.05 Zn – – −60 −1.5
It can be concluded that those parameters that could cause problems with drinking water
standards (Table 2), such as EC, TDS, Na, Cl, SO
4
, F, As and Cr, are swiftly leached out from the
aquifer, namely most of them within 1–3 PVs. The leach factor for Cr corresponds well with the
chromate retardation factor as observed in a column dosage experiment [
33
], and with observations
elsewhere [34,35].
The (semi)permanent concentration increases can, in general, be attributed to mineral dissolution
or prolonged desorption from low permeability but high concentration pockets within the aquifer.
The significant Ca decrease and Mg increase during the six-year storage period could point at
dedolomitization, in which possibly also Sr2+ is involved:
(Y+Z)Ca2++CaXMgYSrZCO3↔CaCO3+Y Mg2++Z Sr2+(6)
where X+Y+Z= 1, possibly with Mg = 0.38 and Sr = 0.02.
The relatively strong increase for SiO
2
during the six-year storage period could at least partly
be explained by quartz dissolution at the relatively high water temperatures (35
◦
C). The following
relation by [
36
] can be used to predict quartz solubility at temperatures 0–200
◦
C, yielding 14.3 mg/L
at 35 ◦C:
SiO2=104.83−1132
tem p+273.15 (7)
6. Results of Predicting the Quality of Recovered Water
6.1. Model Settings
The SWSR ASR system was modeled for just one of three recharge basins, assuming this to be
representative for all three basins. The applied hydrogeological and geochemical stratification of the
aquifer system into five layers follows the information given in Section 3. The low TDS DSW was
selected as constant input to the recharge basin. Its quality is shown in Table 3.
The travel times to all recovery wells (condensed into one well per ring) and flux contributions
from each aquifer layer to the well discharge, were calculated as indicated in Section 2.7.
The combination of travel times leads to the so-called response curve of the whole well field. This is
defined as the cumulative frequency distribution of underground travel times from the recharge basin
to the wells during infiltration. The resulting response curve is shown in Figure 10.
Water quality changes in the recharge basin were completely ignored, because of exclosure from
both sunlight and direct atmospheric contact, the high quality of DSW and the expected ultralow
concentration of suspended solids. The formation of bottom muds in the basin was excluded. The complete
lack of redox reactions necessitated the setting of the reactivity of bulk organic material at zero.
Water 2017,9, 177 19 of 25
Water 2017, 9, 177 19 of 25
concentration of suspended solids. The formation of bottom muds in the basin was excluded. The
complete lack of redox reactions necessitated the setting of the reactivity of bulk organic material at zero.
Figure 10. The cumulative frequency distribution of travel times from the recharge basin to the
schematized seven recovery wells around it. Flowlines in aquifer layers D and E are excluded because
of their very low contribution (together 0.42%).
6.2. Quality Evolution during Nonstop Infiltration
If the infiltration via one of the recharge basins of the SWSR facility would last for 100 years
without interruption, and the recovery wells would periodically pump out a water sample during
this period varying between 0.1 and 100 years, then the abstracted water quality would be as
predicted in Table 5. This table also shows the quality of DSW prior to infiltration and of native
groundwater as abstracted by all ABC recovery wells.
Many things can be concluded from this table, because the recovered water quality also covers
those moments that are representative for the 90 d recovery with or without drift. That aspect follows
in Section 6.3.
Here, it is concluded that continued flushing leads to an initially fast and then slow elution of
native groundwater, a significant leaching of the trace elements As, B, Ba, Cr, F and Sr, and a slow
breakthrough of Cu, Ni and Zn which show higher concentration levels in DSW than in native
groundwater. For selected elements, the breakthrough or leaching curves have been plotted in Figure 11.
The bulk of changes clearly happens during the first year when the native groundwater is displaced.
The predicted water quality after 0.27 year is also representative of water quality after 90 d
recovery following 10 years of lateral drift after 824 d of DSW infiltration. The quality after 0.74 year
is as the one after 0.27 year, but without lateral drift (thus, with direct recovery). The quality after
2.26 years is the water that is recovered on the first day after 824 d of DSW infiltration.
Figure 11. With EL calculated concentration trends of selected main constituents and trace elements
in groundwater that flowed past all recovery wells during nonstop infiltration via a recharge basin.
Figure 10.
The cumulative frequency distribution of travel times from the recharge basin to the schematized
seven recovery wells around it. Flowlines in aquifer layers D and E are excluded because of their very
low contribution (together 0.42%).
6.2. Quality Evolution during Nonstop Infiltration
If the infiltration via one of the recharge basins of the SWSR facility would last for 100 years
without interruption, and the recovery wells would periodically pump out a water sample during this
period varying between 0.1 and 100 years, then the abstracted water quality would be as predicted in
Table 5. This table also shows the quality of DSW prior to infiltration and of native groundwater as
abstracted by all ABC recovery wells.
Many things can be concluded from this table, because the recovered water quality also covers
those moments that are representative for the 90 d recovery with or without drift. That aspect follows
in Section 6.3.
Here, it is concluded that continued flushing leads to an initially fast and then slow elution
of native groundwater, a significant leaching of the trace elements As, B, Ba, Cr, F and Sr, and a
slow breakthrough of Cu, Ni and Zn which show higher concentration levels in DSW than in native
groundwater. For selected elements, the breakthrough or leaching curves have been plotted in Figure 11.
The bulk of changes clearly happens during the first year when the native groundwater is displaced.
The predicted water quality after 0.27 year is also representative of water quality after 90 d
recovery following 10 years of lateral drift after 824 d of DSW infiltration. The quality after 0.74 year
is as the one after 0.27 year, but without lateral drift (thus, with direct recovery). The quality after
2.26 years is the water that is recovered on the first day after 824 d of DSW infiltration.
Water 2017, 9, 177 19 of 25
concentration of suspended solids. The formation of bottom muds in the basin was excluded. The
complete lack of redox reactions necessitated the setting of the reactivity of bulk organic material at zero.
Figure 10. The cumulative frequency distribution of travel times from the recharge basin to the
schematized seven recovery wells around it. Flowlines in aquifer layers D and E are excluded because
of their very low contribution (together 0.42%).
6.2. Quality Evolution during Nonstop Infiltration
If the infiltration via one of the recharge basins of the SWSR facility would last for 100 years
without interruption, and the recovery wells would periodically pump out a water sample during
this period varying between 0.1 and 100 years, then the abstracted water quality would be as
predicted in Table 5. This table also shows the quality of DSW prior to infiltration and of native
groundwater as abstracted by all ABC recovery wells.
Many things can be concluded from this table, because the recovered water quality also covers
those moments that are representative for the 90 d recovery with or without drift. That aspect follows
in Section 6.3.
Here, it is concluded that continued flushing leads to an initially fast and then slow elution of
native groundwater, a significant leaching of the trace elements As, B, Ba, Cr, F and Sr, and a slow
breakthrough of Cu, Ni and Zn which show higher concentration levels in DSW than in native
groundwater. For selected elements, the breakthrough or leaching curves have been plotted in Figure 11.
The bulk of changes clearly happens during the first year when the native groundwater is displaced.
The predicted water quality after 0.27 year is also representative of water quality after 90 d
recovery following 10 years of lateral drift after 824 d of DSW infiltration. The quality after 0.74 year
is as the one after 0.27 year, but without lateral drift (thus, with direct recovery). The quality after
2.26 years is the water that is recovered on the first day after 824 d of DSW infiltration.
Figure 11. With EL calculated concentration trends of selected main constituents and trace elements
in groundwater that flowed past all recovery wells during nonstop infiltration via a recharge basin.
Figure 11.
With EL calculated concentration trends of selected main constituents and trace elements in
groundwater that flowed past all recovery wells during nonstop infiltration via a recharge basin.
Water 2017,9, 177 20 of 25
Table 5.
Overview of water quality in the SWSR ASR scheme, showing input DSW (Desalinated
Seawater), mean native groundwater (when sampled by all wells) and groundwater as if it were
periodically sampled after 0.1 to 100 years during nonstop DSW infiltration.
Sample
Parameter Unit
Native RECOVERED WATER ‘SAMPLED’ AFTER Input Abu Dh.
Drink. w.
Standard
WHO
Guide-Lines
Measured 0.1 0.27 0.74 2.26 10 100 DSW
at ABC Year Year Year Year Year Year 2014
General
EC 20 ◦Cµ
S/cm
1411 1304 829 295 199 184 170 123 1600
Temp. ◦C 34.2 34.2 34.4 34.8 35.0 35.0 35.0 35.0
pH 8.13 8.13 8.20 8.35 8.44 8.44 8.45 8.10 7–9.2
O2
mg/L
1.9 2.5 4.5 6.7 7.1 7.1 7.1 7.2 >2
CH4
mg/L
0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
DOC
mg/L
0.8 0.8 0.6 0.4 0.3 0.3 0.3 0.3 1
SI-calcite 0.19 0.15 0.00 −
0.30
−
0.19
0.18 0.33 0.00
Main constituents
Cl
mg/L
287.0 261.6 154.5 36.5 15.4 11.5 7.8 5.0 250
SO4
mg/L
235.0 217.8 130.7 28.0 8.3 5.9 3.6 1.0 250
HCO3
mg/L
116 112 93 71 67 67 67 66 >60
NO3
mg/L
32.3 29.0 16.3 3.1 0.8 0.7 0.6 0.3 50 50
PO4
mg/L
0.03 0.03 0.03 0.03 0.05 0.16 0.21 0.21 2.2
Na
mg/L
295.0 273.2 170.4 53.3 28.0 13.1 7.2 4.1 150
K
mg/L
12.4 11.1 6.8 2.0 0.7 0.3 0.2 0.1 12
Ca
mg/L
31.5 28.7 17.9 6.3 6.4 15.4 20.6 20.2 80
Mg
mg/L
9.5 8.8 5.7 2.2 2.1 2.6 0.7 0.4 30
NH4
mg/L
0.02 0.02 0.02 0.02 0.01 0.00 0.00 0.02 0.5
Fe
mg/L
0.02 0.02 0.02 0.02 0.02 0.01 0.00 0.012 0.2
Mn
mg/L
0.01 0.00 0.00 0.00 0.00 0.00 0.00 0.003 0.4
SiO2
mg/L
25.2 25.2 25.2 25.2 23.0 14.4 14.4 0.5
Trace elements
As µg/L 11.2 11.2 11.2 9.9 4.9 2.0 1.9 0.3 10 10
Bµg/L 884 884 736 311 65 48 44 17 2400 2400
Ba µg/L 46 46 46 46 46 31 14 2 700 700
Cr µg/L 104.0 103.7 70.7 28.3 13.2 13.0 12.6 0.30 50 50
Cu µg/L 0.7 0.7 0.7 0.7 2.4 11.9 16.2 16.4 1000 2000
Fµg/L 2190 2113 1667 895 173 101 92 30 1.5 1.5
Ni µg/L 2.0 2.0 2.0 2.0 2.2 3.4 4.3 4.3 70 70
Sr µg/L 4397 4397 4397 4397 4397 2889 228 16
Vµg/L 87 87 83 54 16 11 11 0.3
Zn µg/L 12.0 11.6 11.6 11.6 11.6 5.4 3.0 3.0 5000
6.3. Quality Evolution during Recovery
The standard EL output list had to be elaborated, as indicated in Figure 7, in order to depict
the water quality evolution during the 90 d of recovery (with or without 10 years standstill before).
The result is shown for selected elements (Na, Cl, NO
3
, As, Cr and F), TDS and the contribution of
DSW in Figure 12, and for many more water quality parameters in Table 5.
It is concluded that TDS and the concentration of most dissolved constituents slowly rise, while the
percentage of DSW slowly decreases during progressive recovery. The main reason of this worsening
water quality is the admixing of native groundwater. Without a preceding 10-year storage phase and
thus practically without bubble drift, recovered water quality complies with the UAE drinking water
standards (Table 2), with only As approximating the maximum permissible concentration near the end.
Ten years of storage with bubble drift have a more negative impact on water quality, as expected.
This becomes manifest only halfway during the 90 d recovery phase (Figure 12), and starts to become
critical in between 80 and 90 d, especially regarding Na, As, Cr and F. These constituents are predicted
to exceed the drinking water MPCs: Na 170 (MPC 150 mg/L), As 11.2 (MPC 10 ug/L), Cr 70.7 (MPC
50 ug/L) and F 1.67 (MPC 1.5 mg/L).
Water 2017,9, 177 21 of 25
Water 2017, 9, 177 21 of 25
worsening water quality is the admixing of native groundwater. Without a preceding 10-year storage
phase and thus practically without bubble drift, recovered water quality complies with the UAE
drinking water standards (Table 2), with only As approximating the maximum permissible
concentration near the end.
Ten years of storage with bubble drift have a more negative impact on water quality, as expected.
This becomes manifest only halfway during the 90 d recovery phase (Figure 12), and starts to become
critical in between 80 and 90 d, especially regarding Na, As, Cr and F. These constituents are
predicted to exceed the drinking water MPCs: Na 170 (MPC 150 mg/L), As 11.2 (MPC 10 ug/L), Cr
70.7 (MPC 50 ug/L) and F 1.67 (MPC 1.5 mg/L).
Figure 12. With EL calculated concentration trends of selected elements dissolved in groundwater
that is recovered from the DSW basin infiltration system after 824 d of recharge, without bubble drift
(no storage phase) and with bubble drift (with 10 years of standstill prior to recovery). MPC =
Maximum Permissible Concentration by Abu Dhabi’s drinking water standard.
7. Discussion
The relatively simple modeling approach as presented in Section 2.7 and applied in Section 6,
strongly relies on: (i) observations done during trials in the pilot area; and (ii) reversibility of the
predicted water quality evolution during forward (infiltration) mode. This means that complications
due to shorter or longer detention times in the aquifer (during storage and recovery) or due to
processes like biofouling of the basin proximal zone should not occur.
Figure 12.
With EL calculated concentration trends of selected elements dissolved in groundwater
that is recovered from the DSW basin infiltration system after 824 d of recharge, without bubble drift
(no storage phase) and with bubble drift (with 10 years of standstill prior to recovery). MPC = Maximum
Permissible Concentration by Abu Dhabi’s drinking water standard.
7. Discussion
The relatively simple modeling approach as presented in Section 2.7 and applied in Section 6,
strongly relies on: (i) observations done during trials in the pilot area; and (ii) reversibility of the
predicted water quality evolution during forward (infiltration) mode. This means that complications
due to shorter or longer detention times in the aquifer (during storage and recovery) or due to processes
like biofouling of the basin proximal zone should not occur.
Problematic deviations from our predictions could arise, when the relatively high recovery rate
(six times higher than the infiltration rate) would provoke serious upconing of brackish to saline
groundwater from Aquifer 2, or when pockets of lower permeability in aquifer 1 would deliver more
of their interstitial, low quality groundwater. A more dedicated spatial model, in which density
effects and reactive transport (e.g., [
19
]) are combined, is needed to assess the potential impact of
these processes.
There are other important questions still to answer, probably necessitating column studies and
prolonged field monitoring during operation. The first question is: Which mineral sources could be
responsible for the remarkable, semipermanent background mobilization of especially Cr, V, As and Sr,
and how can this mobilization be mitigated? The second is whether clay minerals will deflocculate
upon flushing of the target aquifer, and thereby clog it. There are weak signs that this might have
happened to a minor degree during the pilot. The risk of clay mobilization will be higher during the
Water 2017,9, 177 22 of 25
operational phase, because still lower TDS infiltration water (DSW) will be used, and the ABC area
contains some higher salinity subareas than the pilot area.
8. Conclusions
In this paper, we present the peculiar characteristics of an eolian-fluvial, (sub)oxic, calcareous
sand(stone) aquifer system in a desert environment, the unique water quality changes during an ASR
pilot including a six-year storage phase, and a relatively simple modeling approach to rapidly predict
water quality of the recovered water, which is to be distributed without treatment.
In the applied Easy-Leacher model, pilot observations on retardation, leaching and (semi)permanent
concentration changes are combined with a strong schematization of the complex basin–ASR system,
groundwater flow (including bubble drift) and hydrogeochemical processes.
The hydrogeochemical simplifications are justified by the low reactivity of the aquifer, which is
explained by the very low solute content of desalinated seawater (DSW), the infiltration of (sub)oxic
DSW into an already (sub)oxic aquifer (thus, preventing redox reactions), a rapid leaching and, at high
pH (7.8–8.5), high mobility of the problematic trace elements Cr (>95% as CrO
42−
), B (as H
3
BO
3
), F,
Mo (as MoO42−), and V (as VO43−).
The pilot observations and modeling results demonstrate that recovered water is most likely
complying with Abu Dhabi’s drinking water standards in both studied ASR scenarios. Without
preceding 10-year storage (and thus hardly any drift, but with replacement of native groundwater),
recovered water quality is expected to comply with the drinking water standards after 824 d of
infiltration, even beyond the 67% recovered in 90 d (up to ~85% recovery). The same conclusions
also hold for the modeled scenario with 10-year storage (and thus significant bubble drift), however
not for 90 but for 80 d. This means that the recovery efficiency will drop from ~85 to 60%. After
80 d (60% recovered), MPC exceedances are then expected for: Na (20 above 150 mg/L), As (1 above
10
µ
g/L), Cr (21 above 50
µ
g/L) and F (0.2 above 1.5 mg/L). The main reason for their exceedances is
the admixing of native groundwater.
This prediction has contributed to the implementation of some adaptations to the current ASR
scheme operational since May 2015. The injection rate was raised by 20%, and during storage 568 m
3
/d
will be infiltrated continuously during any storage period. By adjusting pumping schemes based on
real time monitoring, the recovery efficiency can probably be maintained at about 80%.
If drinking water standards would become more strict, as is currently discussed in the Netherlands
regarding As (from 10 to 1
µ
g/L) and CrO
42−
(from 50 to 0.3
µ
g/L; [
37
]), then Abu Dhabi’s drinking
water standards will be exceeded in all modeled cases. This may be acceptable, however, during a
short emergency situation after a calamity.
Potential risks of upconing of brackish/saline deep, native groundwater, aquifer clogging by clay
mobilization and basin clogging were not addressed, and may necessitate further research.
Acknowledgments:
This study was funded by the Environment Agency of Abu Dhabi (EAD). Figures 1–3were
kindly provided by GTZ-Dornier. George Koziorowski (GTZ) is acknowledged for sharing some of his water
quality data and for valuable discussions. Anonymous reviewers helped to improve the text.
Author Contributions:
Pieter J. Stuyfzand evaluated all existing data, developed and applied the ASR model for
predicting future recovered water quality, and wrote the paper. Koen G. Zuurbier conducted the field campaign
in 2014. Niels Hartog performed the PHREEQC-2 modeling. Ebel Smidt and Mohammed A. Dawoud formulated
the framework for this research and guided all steps in conducting this research, contributed by supplying
information and edited texts.
Conflicts of Interest: The authors declare no conflict of interest.
Water 2017,9, 177 23 of 25
Abbreviations
The following abbreviations are used in this manuscript:
∆C(semi)permanent concentration change
∆H/∆Xmean regional hydraulic gradient in aquifer [-]
∆tBACK-1 setback time without horizontal bubble drift [d]
ρsdensity of solids of porous medium [kg/L]
ASL above sea level
ASR Aquifer Storage and Recovery
BOM bulk organic material in aquifer
BSL below sea level
BTC break through curve
CEC cation exchange capacity
DSW desalinated seawater
Kddistribution coefficient [L/kg]
Kh,N horizontal hydraulic conductivity of layer N [m/d]
Li leach factor for compound i
MPC maximum permissible concentration
MSL mean sea level
nporosity [L/L]
nNporosity of layer N [-]
ORP oxidation reduction potential
(prod) concentration of reaction product in fluid during leaching [mmol/L]
PV pore volume
QIN mean infiltration rate [m3/d]
rradial distance from the basin center [m]
r552,N radial distance in aquifer layer N, to ASR well after 552 d recovery
(reac) concentration of reactant in flushing fluid [mmol/L]
Riretardation factor for compound i
rPreaction coefficient related to (prod) [-].
rRreaction coefficient related to (reac) [-]
(solid) content of reactive phase in aquifer [mmol/kg dry weight]
Ttransmissivity of the aquifer [m2/d]
t50 observed 50% breakthrough time of conservative tracer or calculated travel time
TDS total dissolved solids
titime for ≥90% break-through (Ri) or ≥90% leaching (Li) or till equilibrium [days]
tINF total infiltration period [d]
tN50% break-through time in layer N [d]
TOC total organic carbon
tVvertical travel time [d]
vB,N horizontal bubble drift in layer N [m/d]
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