ArticlePDF Available

Abstract and Figures

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 Mm³/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 SiO2 dissolution; a strong mobilization of natural AsO4³⁻, B, Ba, F, CrO4²⁻, Mo, Sr and V from the (sub)oxic aquifer; and immobilization of PO4, 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.
Content may be subject to copyright.
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 [47].
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 [1422].
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 13) 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(1n)Kd
n(2)
Li=ti
t50
=1+ρS(1n)(solid)
n(reac)rR
=1+ρS(1n)(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,NH
nNX(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
F14 <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 79.2
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++CaXMgYSrZCO3CaCO3+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=104.831132
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 13were
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]
References
1.
Saif, O. The Future Outlook of Desalination in the Gulf: Challenges & Opportunities Faced by Qatar & the
UAE. 2012. Available online: http://inweh.unu.edu/wp-content/uploads/2015/05/The-Future-Outlook-
of-Desalination-in-the-Gulf1.pdf (accessed on 2 January 2017).
2.
Al Shehhi, M.R.; Gherboudj, I.; Ghedira, H. An overview of historical harmful algae blooms outbreaks in the
Arabian Seas. Mar. Pollut. Bull. 2014,86, 314–324. [CrossRef] [PubMed]
3.
Do Rosário Gomes, H.; Goes, J.L.; Matondkar, S.G.P.; Buskey, E.J.; Basu, S.; Parab, S.; Thoppil, P. Massive
outbreaks of Noctiluca scintillans blooms in the Arabian Sea due to spread of hypoxia. Nat. Commun.
2014
,5.
[CrossRef] [PubMed]
Water 2017,9, 177 24 of 25
4.
Missimer, T.M.; Sinha, S.; Ghaffour, N. Strategic Aquifer Storage and Recovery of Desalinated Water to
Achieve Water Security in the GCC/MENA Region. Int. J. Environ. Sustain.
2012
,1, 87–99. Available
online: https://www.sciencetarget.com/Journal/index.php/IJES/article/viewFile/93/26 (accessed on
2 January 2017). [CrossRef]
5.
Hutchinson, C.B. Simulation of Aquifer Storage Recovery of Excess Desalinated Seawater; U.S. Geological Survey
Open-File Report 98-410; USGS: Al Ain area, Abu Dhabi Emirate, 1998. Available online: https://pubs.usgs.
gov/of/1998/0410/report.pdf (accessed on 2 January 2017).
6.
Pyne, R.D.G.; Howard, J.B. Desalination/aquifer storage recovery (DASR): A cost effective combination for
Corpus Christi, Texas. Desalination 2004,165, 363–367. [CrossRef]
7.
Dawoud, M.A.; Sallam, O.M. Sustainable Groundwater Resources Management in Arid Regions: Abu Dhabi
Case Study; Environmental Agency Abu Dhabi Report; Environmental Agency Abu Dhabi: Abu Dhabi,
United Arab Emirates, 2010.
8.
German Technical Cooperation Agency. Combined Artificial Recharge and Utilisation of the Groundwater
Resource in the Greater Liwa Area (Western Region of the Emirate of Abu Dhabi); Pilot Project Final Technical
Report; Deutsche Gesellschaft für Technische Zusammenarbeit (GTZ) GmbH in Co-operation with Dornier
Consulting (DCo) GmbH: Bonn, Germany, 2005.
9.
German Technical Cooperation Agency. Detailed Design Groundwater Modelling Final Report; Consultancy
Services for Artificial Recharge and Utilisation of the Groundwater Resource in the Liwa Area, Consultancy
Contract No. G 4877; Deutsche Gesellschaft für Technische Zusammenarbeit (GTZ) GmbH in Co-operation
with Dornier Consulting (DCo) GmbH: Bonn, Germany, 2009.
10.
German Technical Cooperation Agency. Detailed Design Drilling, Construction and Testing of Recovery and
Monitoring Wells Draft Report; Consultancy Services for Artificial Recharge and Utilisation of the Groundwater
Resource in the Liwa Area, Consultancy Contract No. G 4877; Deutsche Gesellschaft für Technische
Zusammenarbeit (GTZ) GmbH in Co-operation with Dornier Consulting (DCo) GmbH: Bonn, Germany,
2009; p. 56.
11.
Earth Link & Advanced Resources Development. Hydrogeological Study and Numerical Groundwater Simulation;
Construction Phase Strategic Water Storage and Recovery Project in Liwa Abu Dhabi—United Arab Emirates;
Quarterly Report #6 Hydrogeological Structure and Groundwater Flow & Transport Model of the SWSR
Region; Earth Link and Advanced Resources Development Sarl: Amaret Chalhoub, Lebanon, 2013.
12.
Al Futtaim Exova LLC. Test Report of Core Samples; 4 Reports on Respectively Well No: MW 01C, MW11C,
MW21 and MW42; Al Futtaim Exova LLC, Lab: Dubai, United Arab Emirates, 2011–2012.
13.
Water Quality Regulations 2013-Final Draft Consultation; Regulation and Supervision Bureau Abu Dhabi: Abu
Dhabi, United Arab Emirates, 2013.
14.
Stuyfzand, P.J. Quality changes upon injection into anoxic aquifers in the Netherlands: Evaluation of
11 experiments. In Artificial Recharge of Groundwater, Proceedings of the 3rd International Symposium on
Artificial Recharge, Amsterdam, The Netherlands, 21–25 September 1998; Peters, J.H., Ed.; Balkema: Amsterdam,
The Netherlands, 1998; pp. 283–291.
15.
Stuyfzand, P.J.; Timmer, H. Deep Well Injection at the Langerak and Nieuwegein sites in the Netherlands:
Chemical Reactions and Their Modeling; Kiwa-SWE 99.006; KWR Watercycle Research Institute: Nieuwegein,
The Netherlands, 1999; 44p.
16.
Stuyfzand, P.J. Pyrite oxidation and side-reactions upon deep well injection. WRI-10. In Proceedings of
the 10th International Symposium on Water Rock Interaction, Villasimius, Italy, 10–15 June 2001; Volume 2,
pp. 1151–1154.
17.
Prommer, H.; Stuyfzand, P.J. Identification of temperature-dependent water quality changes during a deep
well injection experiment in a pyritic aquifer. Environ. Sci. Technol.
2005
,39, 2200–2209. [CrossRef] [PubMed]
18.
Antoniou, E.A.; van Breukelen, B.M.; Putters, B.; Stuyfzand, P.J. Hydrogeochemical patterns, processes and
mass transfers during aquifer storage & recovery (ASR) in an anoxic sandy aquifer. Appl. Geochem.
2012
,27,
2435–2452.
19.
Zuurbier, K.G.; Hartog, N.; Stuyfzand, P.J. Reactive transport impacts on recovered freshwater quality during
multiple partially penetrating wells (MPPW-)ASR in a brackish heterogeneous aquifer. Appl. Geochem.
2016
,
71, 35–47. [CrossRef]
20.
Pyne, R.D.G. Aquifer Storage Recovery—A Guide to Groundwater Recharge through Wells; ASR Systems LLC:
Gainesville, FL, USA, 2005.
Water 2017,9, 177 25 of 25
21.
Price, R.E.; Pichler, T. Abundance and mineralogical association of arsenic in the Suwannee Limestone
(Florida): Implications for arsenic release during water-rock interaction. Chem. Geol.
2006
,228, 44–56.
[CrossRef]
22.
Wallis, I.; Prommer, H.; Simmons, C.T.; Post, V.; Stuyfzand, P.J. Evaluation of Conceptual and Numerical
Models for Arsenic Mobilization and Attenuation during Managed Aquifer Recharge. Environ. Sci. Technol.
2010,44, 5035–5041. [CrossRef] [PubMed]
23.
Stuyfzand, P.J.; Smidt, E.; Zuurbier, K.G. Baseline Hydrogeochemistry of the Strategic Water Storage and Recovery
Project in Liwa, Abu Dhabi; KWR-Report KWR2014.073; KWR Watercycle Research Institute: Nieuwegein,
The Netherlands, 2014.
24.
Stuyfzand, P.J.; Hartog, N.; Smidt, E. Prediction of Recovered Water Quality of the Strategic ASR Project in Liwa,
Abu Dhabi; KWR-Report KWR2015.003; KWR Watercycle Research Institute: Nieuwegein, The Netherlands, 2014.
25.
Stuyfzand, P.J. Simple models for reactive transport of pollutants and main constituents during artificial
recharge and bank filtration. In Artificial Recharge of Groundwater, Proceedings of the 3rd Internatioanl
Symposium on Artificial Recharge, Amsterdam, The Netherlands, 21–25 September 1998; Peters, J.H., Ed.; Balkema:
Amsterdam, The Netherlands, 1998; pp. 427–434.
26.
Stuyfzand, P.J. Hydrogeochemcal (HGC 2.1), for Storage, Management, Control, Correction and Interpretation of
Water Quality Data in Excel (R) Spread Sheet; KWR-Report BTO2012.244(s); Updated in 2016 December; KWR
Watercycle Research Institute: Nieuwegein, The Netherlands, 2016; 92p.
27.
Parkhurst, D.L.; Appelo, C.A.J. User’s Guide to PHREEQC (Version 2): A Computer Program for Speciation,
Batch-Reaction, One-Dimensional Transport, and Inverse Geochemical Calculations; Water-Resources Investigations
Report 99-4259.; Open-File Reports Section (Distributor); U.S. Geological Survey: Reston, VA, USA;
Earth Science Information Center: Denver, CO, USA, 1999.
28.
Wood, W.W.; Clark, D.; Imes, J.L.; Councell, T.B. Eolian Transport of Geogenic Hexavalent Chromium to
Ground Water. Ground Water 2010,48, 19–29. [CrossRef] [PubMed]
29.
Wood, W.W.; Imes, J.L. Dating of Holocene groundwater recharge in the Rub al Khali of Abu Dhabi:
Constraints on global climate-change models. In Water Resources Perspectives: Evaluation, Management
and Policy; Developments in Water Science 50; Alsharhan, A.S., Wood, W.W., Eds.; Elsevier: Amsterdam,
The Netherlands, 2003; pp. 379–385.
30.
Bottomley, N. Recent climate in Abu Dhabi. In Desert Ecology of Abu Dhabi; Osborne, P.E., Ed.; Pisces
Publications: Newbury, UK, 1996; pp. 36–49.
31.
World Health Organization. Guidelines for Drinking-Water Quality, 4th ed.; World Health Organization:
Geneva, Switzerland, 2011; Available online: http://apps.who.int/iris/bitstream/10665/44584/1/
9789241548151_eng.pdf (accessed on 15 February 2017).
32.
Scheuerman, R.F.; Bergersen, B.M. Injection-water salinity, formation pretreatment, and well operations
fluid-selection guidelines. J. Pet. Technol. 1990,42, 836–845. [CrossRef]
33.
Al-Rahman, W.; Maraqa, M. Laboratory investigation of transport and treatment of chromium in
groundwater at liwa district, Abu Dhabi. In Proceedings of the 1st International Conference on Natural
Resources Engineering & Technology, Putrajaya, Malaysia, 24–25 July 2006; pp. 338–345.
34.
Yolcubal, ˙
I.; Akyol, N.H. Retention and Transport of Hexavalent Chromium in Calcareous Karst Soils. Turk. J.
Earth Sci. 2007,16, 363–379.
35.
Richard, F.C.; Bourg, A.C.M. Aqueous geochemistry of chromium: A review. Water Res.
1991
,25, 807–816.
[CrossRef]
36.
Siever, R. Silica solubility, 0–200
C., and the diagenesis of siliceous sediments. J. Geol.
1992
,70, 127–150.
[CrossRef]
37.
Ahmad, A.; Kools, S.; Schriks, M.; Stuyfzand, P.J.; Hofs, B. Arsenic and Chromium Concentrations and Their
Speciation in Groundwater Resources and Drinking Water Supply in The Netherlands; KWR Report BTO 2015.017;
KWR Watercycle Research Institute: Nieuwegein, The Netherlands, 2015.
©
2017 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access
article distributed under the terms and conditions of the Creative Commons Attribution
(CC BY) license (http://creativecommons.org/licenses/by/4.0/).
... Also, to avoid failure in the water supply during any emergency situation, the subsurface storage, which is the world's largest artificial recharge, was started in the year 2015 using Strategic Aquifer Storage and Recovery (SASR) structure at the dune surface. The efficiency was investigated by a pilot study during the years 2003-2004 and 2008-2014 and by developing a small-scale model [26,27]. A recent review by Parimalarenganayaki (2020) [28] on the efficiency of various artificial recharge methods in arid regions reported that the subsurface storage at a suitable aquifer medium is beneficial because of the neglected effect of evaporation. ...
... However, the aquifer is in the dune surface holding a freshwater lens of palaeo origin which is one of the promising factors for the site suitability to store a freshwater of nonconventional origin. The pilot study conducted by Schlumberger Water Services (2011), forward and reversed chemical models developed by [27] confirmed that the recovery range could be between 60-88%. Especially in the latter study, it was also reported the occurrence of native groundwater mixing during the period of storage. ...
... The quality of desalinated water in the year 2014 is given in Table 4 and shows that the salinity is not beyond 0.25 gL −1 . Table 4. Desalinated water quality in the year 2014 [27]. The regional influence in the groundwater head is noticed up to a distance of 5 km on all the sides symmetrically due to the presence of flat and gentle topography and groundwater gradient. ...
Article
Full-text available
In Abu Dhabi, one of the most arid regions in the world, in recent decades, desalinated water has been identified as a prime solution in solving the water demand issues. In this study, a three-dimensional coupled density-dependent flow and solute transport model was set up in order to study the effect of the artificial recharge using desalinated water and the influence of nonconventional water with a salt concentration in the range 0.1–2 g/L The results confirm that this region demands the adoption of a more rational use of irrigation water or additional usage of desalinated water and recycled water together with optimizing groundwater pumping at locations that are vulnerable to further quality degradation and depletion. The long-term storage of desalinated freshwater with a maximum radial distance of 653 m in the dune surface is ensured with the formation of the transition zone, and change in the groundwater head up to 5 km. The maximum recovery obtained by immediate recovery is 70%. The study expresses the long-term feasibility of desalinated freshwater storage and the need for further management practices in quantifying the contribution of desalinated and recycled water for agriculture activities which might have improved groundwater quality and increased hydraulic head at some locations.
... Hydrological characteristics and additional components were considered for the suitability assessment for ASR site from previous information on ASR criteria's published by several authors (Pyne, 1995;Hutchinson, 1998;Brown et al., 2005;Dillon et al., 2006;Vacher et al., 2006;Misut and Voss, 2007;Ward et al., 2007;Woody, 2008;Minsley et al., 2009;Missimer and Maliva, 2010;Zuurbier et al., 2013;Rambags et al., 2013;Stuyfzand et al., 2017), each study has its own criteria/ranges and a score were assigned based on its suitability that will help in the assessment of the suitable sites for ASR system and disqualifying the sites that doesn't match the suitability assessment (Gibson et al., 2018;Imig et al., 2020). Fifteen criteria were selected and combined to develop criteria list. ...
... Two types of aquifers can be present in the proposed site depending on the bounding geological layers. Both confined and unconfined aquifers can be suitable for ASR systems (Dillon et al., 2006) but other hydrological criteria will help in the optimum ASR site selection (Stuyfzand et al., 2017). Heterogeneity in aquifer's hydraulic properties and gradient would result in ASR system failure if not studied carefully to ensure the movement of the injected water (Missimer and Maliva, 2010). ...
Article
Full-text available
Identification of selection criteria is a crucial initial step in aquifer storage and recovery (ASR) projects. The lack of knowledge of suitable sites hydrological and geological characteristics could be limiting factors in the application of ASR technology. A total of 20 sites were evaluated in the eastern district of Abu Dhabi emirate, using available data at each site, based on 15 different criteria. The study area is an agricultural intense region, where groundwater is extensively used for irrigation. The developed framework is proven to be useful in terms of ASR planning. The framework is based on weighting factors assigned to each hydrogeological and additional characteristic based on its relative importance in the ASR site selection. The developed scoring scheme is used with the 20 sites to assess the possibility of finding a suitable site for potential ASR with promising aquifer performance. The total score was used to develop final ASR suitability maps. The highest score of 142 out of 160 (89% ASR suitability) was achieved in Al Khrair site followed by Al Dhahir with 138 out of 160 (86%), Al Shuwaib with 136 out of 160 (85%) and Al Bateen with 126 out of 160 (79%). The sites located at the eastern part of the study area had the highes scores. The score is decreased at the sites located at the western and southern parts of the study area, with the lowest score of 107 out of 160 at Abu Huraibah. The characterization of sites should be mainly based on the availability of pumping stations in the vicinity of the study area, that will be helpful in the future implementation of the ASR project. The detailed hydrogeological and operational data of the studied sites helped in the ASR assessment.
... Abu Dhabi then became home to the world's largest ASR initiative (see Box 8.7), using desalinated water to recharge a desert dune sand aquifer near the Liwa oasis. The water stored here can be recovered under emergency conditions (Stuyfzand et al., 2017). In Oman, Saudi Arabia and the UAE, check dams built on riverbeds to divert runoff and recharge aquifers remain the most commonly practiced MAR approach in the region. ...
... Source: Stuyfzand et al. (2017). ...
Chapter
Full-text available
Climate change strongly influences freshwater supply and demand globally. Warming of ~1°C over the last half century globally has directly impacted the supply of freshwater through the amplification of precipitation extremes, more frequent and pronounced floods and droughts, increasing evapotranspiration rates, rising sea levels, and changing precipitation and meltwater regimes. Groundwater, the world’s largest distributed store of freshwater, is naturally well placed to play a vital role in enabling societies to adapt to intermittent and sustained water shortages caused by climate change. It is also essential to satisfy the increased demand for water in order to realize many of the United Nations’ Sustainable Development Goals (SDGs), including no. 2 (zero hunger), 6 (water for all) and 13 (climate action). Aquifers transmitting and storing groundwater can also contribute to climate change mitigation through the use of geothermal energy to reduce CO2 emissions, as well as the capture and storage of emitted CO2. This chapter reviews the latest understanding of the impacts of climate change on groundwater quantity and quality as well as the opportunities, risks and challenges posed by the development of aquifers for climate change adaptation and mitigation.
... These merits would be valuable to meet water requirements during demand periods. Stuyfzand, Smidt, Zuurbier, Hartog, and Dawoud (2017) reported the ASR wells' ability to recover more than 0.17 Mm 3 /day for three months in the Liwa desert, UAE. These quantities of water met the regional water needs during emergency periods. ...
Conference Paper
Full-text available
Even though managed aquifer recharge (MAR) helped effectively in increasing aquifer storage and improving groundwater quality in many arid regions worldwide, its feasibility remains an open question in Qatar. Qatar is a hyper-arid country with minimal natural water resources, high per-capita water consumption, and over-exploited aquifers—the only water source for agriculture. During the last two decades, the country had a significant increase in population and urbanization, which posed extra stress to the aquifers. This paper discusses MAR feasibility and highlights possible factors for aquifer management and sustainability in Qatar. Outcomes showed that, among MAR methods, the aquifer storage and recovery (ASR) could help augment Qatar aquifers if technical and socioeconomic aspects were guaranteed. Considering 2016 as an example, injecting the unutilized treated sewage effluent (TSE; estimated by ~500 million m3 in 2017) in aquifers can strike a balance in Qatar’s water system if a recovery rate of 30% was achieved in the ASR wells. Under future projections of population and consumption increase, abstraction from aquifers will rise significantly through the 21st century, which requires looking for alternative water resources. The analysis also revealed unclear measurements for aquifers abstraction. Using smart water meters to measure abstraction quantities is, therefore, a dire need.
... For example, UAE operates the largest desalinated seawater plant globally with a stored volume of~10 Mm 3 /year. It is expected to recover potable water for direct use (Stuyfzand et al., 2017). The full project was completed in 2017 and includes~300 injection wells to store 26 Mm 3 of supply of desalinated water which is sufficient to supply the Abu Dhabi Emirates with emergency water for three months (Dawoud, 2020). ...
Chapter
Full-text available
Freshwater scarcity in the Middle East and North Africa (MENA) is increasingly exacerbated by rapid population growth demands and climate change and currently impacts ~0.6 billion people in the region. In this chapter, we revisited the trends in terrestrial water storage (TWS) over the last 18 years between 2002 and 2020 using observations of the Gravity Recovery and Climate Experiment and its Follow On (GRACE-FO) missions. We evaluated the interdecadal TWS trends in the MENA region against the variability of climate-driven TWS between 1901 and 2020 derived from GRACE, GRACE-FO, and natural simulation of the global WaterGAP hydrological model. Climate-driven TWS represents TWS anomalies that are only forced by non-anthropogenic stressors and vary from annual cycle to centennial variations. These TWS patterns were derived using the cyclostationary empirical orthogonal functions method over grid and MENA’s polygon scales. The interdecadal trend of TWS in the MENA region shows that the entire MENA region lost about ~760 Gigaton (Gt) between 2002 and 2020, equivalent to ~2.6x the annual rate of ice loss from Greenland or ~ 2 mm of global sea-level increase. Depletion is more severe in the Middle East (e.g., Iran, Saudi Arabia) than in North Africa, except for Tunisia. Current GRACE-GRACE (FO) TWS depletion trends in MENA exceed past climate variability magnitude by at least a factor of 50 (considering GRACE period only), especially in northern Saudi Arabia, southern and eastern Iran, western Iraq, Egypt, Libya, and Algeria. These regions are characterized by a hyper-arid climate, an absence of groundwater recharge, overexploitation of surface water and groundwater resources. Sustainable surface and groundwater management is more urgent than ever to meet increasing demands. Interpreting GRACE trends relative to the magnitude and variability of climate-driven interannual and interdecadal variations helps to evaluate the reliability and forecast skills of current TWS trends and highlights the role of the anthropogenic activity in draining MENA’s water resources.
... In the UAE, MAR wells were constructed in the Liwa desert to recover more than 170,280 m 3 daily for three months, which fulfils the regional water needs during emergency periods. The Shuweihat desalination plant is the source of water at a rate of approximately 9.7 mm 3 /year (Stuyfzand et al., 2017). Additionally, MAR has increased aquifer storability by a significant 33% in southern Iran (Yaraghi et al., 2019) and by 51% in northeast Tunisia (Zammouri and Feki, 2005). ...
Article
Full-text available
The recent sharp increase in Qatar population and urbanisation have exerted more pressure on the country's limited water resources. Many studies have recommended managed aquifer recharge (MAR) to improve groundwater quality and enhance water security. However, MAR appropriateness and feasibility in Qatar remain unexplored. This study establishes key MAR development indicators in Qatar considering current technical and socioeconomic factors. Results show that coupling the rainwater harvesting (RWH) and aquifer storage and recovery (ASR) is the optimum scenario for aquifer management and sustainability. In addition to resources augmentation, RWH will contribute to flash flood prevention, which adversely affects the environment. In contrast, the in-channel modification and spreading methods can reduce up to 80% of the water available for recharge. Further work includes considering climate change impacts and uncertainty in MAR design for karst aquifers. A recovery rate up to 25% might be recorded in ASR karstic heterogeneous sites.
Article
Full-text available
In Menashe Streams managed aquifer recharge (MAR) site (Israel) desalinated seawater (DSW) is recharged since 2015, alongside ephemeral stream flows. This study quantifies the uncertainty of predictions of the mixing of these two water sources in the aquifer. Mixing estimations are based on the significant difference in the content of stable water isotopes between the water sources. Uncertainties driven from aquifer heterogeneity and climate variability are compared. We use realistic flow and isotope‐transport models in a multiple‐realization stochastic approach considering space and time for the two drivers of uncertainty. Predictive uncertainty is evaluated via comparison of the temporal coefficient of variation of four realization ensembles. Results show that the impact of subsurface structure uncertainty on the predictions is small, compared to the uncertainty resulting from variability related to future hydrometeorological conditions. A generalized conclusion from this result is the difficulty to make long‐term predictions of the mixing ratios, regardless of the level of certainty in the subsurface structure interpretation, when one source of recharge water has significant annual fluctuations. Implication on prediction of magnesium concentration is demonstrated as an example for prediction uncertainty of concentration of a solute of interest in one of the MAR sources. Furthermore, we show that considering a single source MAR site, uncertainty in mixing of the MAR water and native groundwater in wells upgradient of the recharge location is higher than prediction uncertainty in wells located downgradient. Insights are also drawn regarding the change in uncertainty with distance from the recharge pond of the DSW.
Research
Full-text available
The global population is growing at a meteoric rate and the urbanization rate has spiked; thus, putting pressure on water and other resources need to support the rapid growth. The increased demand for water due to the ballooning global population puts pressure on conventional freshwater sources and increased the demand for alternative fresh water sources such as desalination. Countries with major fresh water insecurity challenges such as Africa and the Middle East have the highest concentration of desalination plants. Although desalination is critical in such countries, it has negative environmental implications raising sustainability concerns in desalination supply chains activities right from production to packing, logistics, consumption and disposal of water containers. Poor disposal of desalination wastes and by-products on land and into the seas adversely affect marine ecosystems, marine life and pollutes the soil. The review shows that desalination is widely researched especially technologies used and environmental impacts. However, the sustainability concept is desalination is an emerging issue. Additionally, the intersection between desalination and supply chain sustainability is meagre or non-existence. The connection between desalination and supply chain sustainability should be explored further considering that poor disposal of desalination effluents and lack of integrated desalination wastes management practices in Abu Dhabi and other cities raises sustainability concerns. More research on desalination sustainability and supply chain sustainability aspects such as circular and LARG supply chains is needed.
Article
Full-text available
The study critically reviews the application, management and challenges of managed aquifer recharge (MAR) in the Middle East and North Africa (MENA) region through a survey of 142 studies. The survey reveals the objectives and methods of MAR in the region. It also shows the technical and socioeconomic challenges that significantly cause MAR failure in MENA countries. The article concludes by presenting a framework to evaluate MAR feasibility and it provides recommendations and guidance for future studies and MAR designs in the MENA region, which is facing the impact of climate change.
Article
Full-text available
Aquifer storage and recovery systems using multiple partially penetrating wells (MPPW-ASR) can form a viable solution to the problem of freshwater buoyancy when using brackish aquifers for freshwater storage. This study presents the result of a series of laboratory experiments that aimed at visualizing the shape of freshwater bodies injected into a brackish aquifer and determining the effect on the recovery efficiency (RE) of several MPPW-ASR operational variables. A model aquifer was built in a Plexiglas tank using glass beads and water was injected and abstracted through point and vertical wells, which were operated in various combinations. Numerical models were used to support the interpretation of the time-lapse photographs, and showed that three-dimensional flow effects had to be considered for a correct interpretation of the visible dye patterns. Upward migration of both fresh (during injection) and brackish water (during recovery) along the vertical wells was observed, indicating that the role of well infrastructure as conduits is a critical design criterion for real-world systems. Gravitational instabilities formed when freshwater did not extend all the way to the top of the aquifer, and this negatively impacted the RE by causing greater mixing. The positive freshwater buoyancy led to freshwater bodies that became narrower with depth, and the formation of thin, elongated buffer zones along the aquifer top in multicycle experiments. Up-coning below abstraction wells resulted in lower RE values, reinforcing the potential of scavenger wells to enhance MPPW-ASR system performance.
Article
Full-text available
Population growth, lack of ground-storage in major metropolitan centers, and a variety of security issues cause the need to develop large storage capacities to meet potable water supply needs during emergency conditions in the GCC/MENA region. Because of the arid nature of the region and the very large storage capacities required, conventional ground-storage and surface reservoirs are not economically feasible to meet strategic storage requirements, but must be used to manage distribution system daily demand fluctuation and short-term emergency needs (fire flow). Aquifer storage and recovery (ASR) is an economic and viable technical solution to meet the critical need for strategic long-term storage. ASR systems that can potentially store billions of cubic meters of desalinated water can be economically developed. These systems need to be sited at strategic locations, such as near water treatment facilities, adjacent to major pipelines conveying post-treated desalinated water to municipal population centers or near to pumping stations associated with municipal high water use centers. Great consideration must also be given not only to the strategic positioning of the ASR reservoirs, but also to the hydrogeology of the aquifers in which the systems would be developed. Not all locations and aquifer systems can successfully support a mega-scale ASR system.
Article
Full-text available
In the last decade, the northern Arabian Sea has witnessed a radical shift in the composition of winter phytoplankton blooms, which previously comprised mainly of diatoms, the unicellular, siliceous photosynthetic organisms favoured by nutrient-enriched waters from convective mixing. These trophically important diatom blooms have been replaced by widespread blooms of a large, green dinoflagellate, Noctiluca scintillans, which combines carbon fixation from its chlorophyll-containing endosymbiont with ingestion of prey. Here, we report that these massive outbreaks of N. scintillans during winter are being facilitated by an unprecedented influx of oxygen deficient waters into the euphotic zone and by the extraordinary ability of its endosymbiont Pedinomonas noctilucae to fix carbon more efficiently than other phytoplankton under hypoxic conditions. We contend that N. scintillans blooms could disrupt the traditional diatom-sustained food chain to the detriment of regional fisheries and long-term health of an ecosystem supporting a coastal population of nearly 120 million people.
Conference Paper
Full-text available
Abstract In arid environments, groundwater is an important and precious resource for agricultural, municipal and rural supplies, eco-environment maintenance, and social and economic development especially where no surface water is available. Sustainable and integrated management of groundwater resources along with other available resources is very important tool for water security. Understanding of the interactions between groundwater and human activities are crucial for sustainable water resources development and planning on regional and local scales. Abu Dhabi Emirate experiences a severe water shortage problem that threatens the sustainable development and hinders the national plans for human, industrial and agricultural development. The annual groundwater abstraction from the shallow aquifers is about 2200 million m3 which is about 63.6% of the total Emirate water production whilst the aquifer annual natural recharge ranges from 50 to 140 million m3. Most of this water is used for agriculture and forestry sectors. Historically groundwater was used for domestic use but recently all groundwater domestic fields were shut off. This paper presents and assesses the available groundwater resources the various alternative scenarios for sustainable and integrated management of these resources. A set of efficient solutions (alternatives), concepts are tested and evaluated to rank the alternatives and to assist decision makers in selecting a suitable policy among them, each of which is optimum with regard to its goal and the corresponding consequences.
Article
Full-text available
The hydrogeochemical processes that took place during an aquifer storage and recovery (ASR) trial in a confined anoxic sandy aquifer (Herten, the Netherlands) were identified and quantified, using observation wells at 0.1, 8 and 25 m distance from the ASR well. Oxic drinking water was injected in 14 ASR cycles in the period 2000–2009. The main reactions consisted of the oxidation of pyrite, sedimentary organic matter, and (adsorbed) Fe(II) and Mn(II) in all aquifer layers (A–D), whereas the dissolution of carbonates (Mg-calcite and Mn-siderite) occurred mainly in aquifer layer D. Extinction of the mobilization of SO4, Fe(II), Mn(II), As, Co, Ni, Ca and total inorganic C pointed at pyrite and calcite leaching in layer A, whereas reactions with Mn-siderite in layer D did not show a significant extinction over time. Iron(II) and Mn(II) removal during recovery was demonstrated by particle tracking and pointed at sorption to neoformed ferrihydrite. Part of the oxidants was removed by neoformed organic material in the ASR proximal zone (0 – ca. 5 m) where micro-organisms grow during injection and die away when storage exceeds about 1 month. Anoxic conditions during storage led to increased concentrations for a.o. Fe(II), Mn(II) and NH4 as noted for the first 50–200 m3 of abstracted water during the recovery phase. With a mass balance approach the water–sediment reactions and leaching rate of the reactive solid phases were quantified. Leaching of pyrite and calcite reached completion at up to 8 m distance in layer A, but not in layer D. The mass balance approach moreover showed that Mn-siderite in layer D was probably responsible for the Mn(II) exceedances of the drinking water standard (0.9 μmol/L) in the recovered water. Leaching of the Mn-siderite up to 8 m from the ASR well would take 1600 more pore volumes of drinking water injection (on top of the realized 460).
Article
The use of multiple partially penetrating wells (MPPW) during aquifer storage and recovery (ASR) in brackish aquifers can significantly improve the recovery efficiency (RE) of unmixed injected water. The water quality changes by reactive transport processes in a field MPPW-ASR system and their impact on RE were analyzed. The oxic freshwater injected in the deepest of four wells was continuously enriched with sodium (Na+) and other dominant cations from the brackish groundwater due to cation exchange by repeating cycles of ‘freshening’. During recovery periods, the breakthrough of Na+ was retarded in the deeper and central parts of the aquifer by ‘salinization’. Cation exchange can therefore either increase or decrease the RE of MPPW-ASR compared to the RE based on conservative Cl−, depending on the maximum limits set for Na+, the aquifer's cation exchange capacity, and the native groundwater and injected water composition. Dissolution of Fe and Mn-containing carbonates was stimulated by acidifying oxidation reactions, involving adsorbed Fe2+ and Mn2+ and pyrite in the pyrite-rich deeper aquifer sections. Fe2+ and Mn2+ remained mobile in anoxic water upon approaching the recovery proximal zone, where Fe2+ precipitated via MnO2 reduction, resulting in a dominating Mn2+ contamination. Recovery of Mn2+ and Fe2+ was counteracted by frequent injections of oxygen-rich water via the recovering well to form Fe and Mn-precipitates and increase sorption. The MPPW-ASR strategy exposes a much larger part of the injected water to the deeper geochemical units first, which may therefore control the mobilization of undesired elements during MPPW-ASR, rather than the average geochemical composition of the target aquifer.
Conference Paper
A project is under development at Padre Island and Mustang Island, Corpus Christi, Texas, combining desalination of brackish groundwater with ASR storage of treated drinking water, both utilizing brackish, confined sand aquifers and clay confining layers at depths of less than 250 in. The combination of these two technologies, referred to as "DASR," is a cost-effective water management approach that enables efficient, base load operation of desalting facilities at steady rates while meeting peak demands with water stored in ASR wells. The initial target yield of demonstration DASR facilities is 20 Ml/D peaking capacity, to be met with 4 Ml/D of desalination, 8 MUD of ASR capacity, and about 8 Ml/D of imported water supply from a pipeline to the mainland. In subsequent phases, capacity would be expanded to meet increasing demands. The project involves providing both brackish water supply and ASR well capacity using horizontal directional drilling (HDD) technology, in addition to vertical wells, since available site location opportunities are quite limited. Several wells would be located at each site, effectively developing high well yields from relatively shallow, thin, sand aquifers without risking subsidence due to excessive drawdowns beneath this low coastal barrier island. This will be the first use of HDD technology for construction of ASR wells, and one of the first applications of this technology for any water supply wells. Initial test well construction is under way, to be followed by construction and testing of full scale demonstration facilities. Completion of initial facilities is planned by about the end of 2005. ASR Systems LLC has been selected to provide consulting engineering and hydrogeological services as part of a team of companies led by Carollo Engineers PC.